AI related news

Paul Redmond writes. Paul is the founder of RDA Accountants. A recognised voice in modern accountancy, Paul helps business owners and accountants achieve clarity, growth, and long-term impact through his frameworks on wealth, strategy, and advisory transformation. Introduction: a defining decade Every profession has defining decades – periods when technology and expectations force a complete reinvention. For accountants, this is one of those decades. We’ve already lived through three major shifts: from ledgers to spreadsheets, from desktop software to the cloud, and from static reporting to real-time collaboration. Each step freed us from manual drudgery and increased our efficiency. Artificial Intelligence (AI), however, is different. Unlike past shifts that digitised existing work, AI reshapes the work itself. It changes what accountants do, how we deliver value, and even how clients perceive us. Used poorly, AI risks reducing us to faster processors of compliance tasks - a commodity in a race to the bottom on fees. Used strategically, it gives us the power to become navigators of business success, guiding clients with insight, foresight, and clarity. The choice is ours. Why AI is arriving now AI’s rapid arrival in accountancy isn’t random. Four converging forces make this the perfect moment: Data overload: businesses now produce enormous volumes of data from e-commerce, CRM systems, banking feeds, and apps. Most of it goes unused because humans can’t process it all. AI thrives in this environment, ingesting and analysing vast datasets in seconds. Rising client expectations: Netflix predicts films, Google anticipates searches - our clients live in an AI-powered world. They now expect real-time insights, proactive guidance, and personalised advice from their accountants, not just year-end reporting. Margin pressure: Compliance work is being commoditised by cloud software and low-cost providers. To escape shrinking margins, firms must shift towards higher-value, insight-led services. Talent shortages: Fewer graduates are choosing traditional accounting. The repetitive nature of compliance makes retention difficult. AI offers relief by automating low-value work, freeing teams for more engaging, strategic roles. Together, these forces make AI not optional, but essential. Practical AI in today’s firm AI isn’t a distant future – it’s already embedded in tools we use daily. Here are six practical applications that are reshaping firms: Automated data capture: OCR and machine learning categorise invoices, receipts, and bank transactions with minimal human input (e.g. Dext, Auto Entry). Predictive forecasting: Dynamic models replace static spreadsheets, enabling scenario planning in real time (e.g. Futrli, Fathom). Plain-language reporting: NLP tools translate financial data into clear narrative commentary clients can actually understand (e.g. Microsoft Co-pilot). Workflow optimisation: AI analyses projects, reallocates workloads, and helps practices meet deadlines more reliably (e.g. FYI Docs with Co-pilot). Anomaly detection: Machine learning flags unusual transactions and potential fraud instantly. Knowledge management: AI assists with tax or compliance research, cutting hours from manual work and increasing confidence in advice. Key point: AI replaces repetitive effort, not accountants. It frees us to spend more time interpreting, guiding, and advising. Avoiding the trap: tech-first thinking One of the biggest mistakes firms make is starting with the tool instead of the outcome. Too often, a partner buys software after a slick demo, only for it to gather dust when it doesn’t fit real client needs. The better path is client-first adoption: Define the client result (e.g. “improve cash flow visibility”). Map the process to deliver it. Identify the AI that accelerates or enhances that process. When AI is embedded in a structured, outcome-driven workflow, it stops being a shiny toy and becomes a genuine profit driver. A client-first model for AI adoption Firms succeeding with AI often follow a five-stage rhythm: Discovery – data pull: AI-enabled tools gather a client’s full financial position in minutes, not hours, creating a rich foundation for advisory conversations. Clarity – turning data into insight: AI converts raw data into dashboards, benchmarks, and models, highlighting the top opportunities or risks without drowning clients in spreadsheets. Guidance – human + AI: Accountants interpret insights, ask deeper questions, and deliver recommendations. AI provides the analysis; humans provide wisdom and context. Execution – reliable delivery: Workflow tools automate follow-ups, deadlines, and task allocation so advice is consistently delivered. Continuous monitoring – always-on support: AI alerts accountants to risks or opportunities between meetings (e.g. low cash thresholds), enabling proactive contact. This model transforms advisory from one-off sessions into continuous partnership. Case studies – AI in action Manufacturing cash flow turnaround: A €2.8m family-owned manufacturer struggled with stock inefficiencies. Using AI forecasting, the firm modelled different reorder strategies. A just-in-time approach cut stock write-offs by 40% and freed €120k in cash, which funded new machinery and growth. Retail margin improvement: A retailer saw sales rising but margins falling. AI sales mix analysis revealed 12% of SKUs (Stock Keeping Unit) were unprofitable once marketing spend was factored in. Dropping these improved net margin by 2.5% annually. Result: In both cases, AI supplied clarity, but the accountant supplied confidence and strategy. Overcoming adoption barriers Even with clear benefits, adoption isn’t smooth. Common barriers include: Skills gap: Teams fear they lack knowledge. Fix: Run small AI literacy workshops on tools staff already use. Nominate an “AI champion.” Cost concerns: Licences feel expensive. Fix: Start with one high-impact use case, prove ROI, then expand. Cultural resistance: Staff fear job loss. Fix: Frame AI as support, not replacement – removing low-value work so people can focus on meaningful, engaging tasks. Data security: Clients worry about confidentiality. Fix: Vet vendors rigorously, demand compliance certifications, and communicate transparently about data use. Handled well, these barriers become opportunities to build trust. Redefining the accountant’s role AI doesn’t change what clients ultimately seek: trust, clarity, and strategic partnership. It simply enhances our ability to deliver it. The accountant of today – and certainly of 2030 – will be: A navigator: using AI insights as a compass to help clients chart their course. A translator: converting complex data into clear, empowering stories. A strategist: aligning financial insight with business goals, spotting opportunities, and mitigating risks. Future specialisms will emerge, from data accountants skilled in governance and analytics, to CFO-as-a-Service providers offering real-time strategic guidance to SMEs who can’t afford full-time CFOs. The automation of compliance gives us back the most precious resource: time. What we do with it defines our future. The ethical compass As trusted professionals, we must ensure AI is used responsibly. Four principles matter most: Bias: AI learns from historical data, which may carry hidden biases. We must question and validate outputs. Transparency: Black-box models can’t justify conclusions. Accountants must ensure advice is explainable. Governance: Clients deserve clarity on where data is stored, who can access it, and how it’s used. Accountability: No matter how advanced the AI, responsibility for professional advice rests with us. Our credibility depends not on how advanced our tools are, but on how responsibly we use them. Roadmap – bringing AI into your practice You don’t need a revolution overnight. A structured approach works best: Identify one high-value client outcome (e.g. faster invoice payments). Map your current process. Choose an AI tool to enhance it. Pilot with a small group of willing clients. Refine based on feedback. Standardise and roll out more broadly. Review quarterly to adapt and improve. This rhythm turns AI from an experiment into a consistent growth engine. Conclusion – leading the change AI will reshape accountancy whether we like it or not. The firms that thrive will not be the cheapest or the fastest at compliance, but those who combine AI’s scale with human judgment, trust, and empathy. We can remain record-keepers of the past - or become navigators of the future. That future is already here. The only question is: will you lead with it? This excerpt has been taken from the September 2025 edition of Practice News.

 Whether you’re applying for a new role in practice, industry, or financial services, your CV is your professional handshake and your sales document to get you in the door and to create an opportunity for you to speak to a prospective employer. It’s often the first impression you make with employers, recruiters and HR professionals. Artificial Intelligence (AI) tools can be powerful allies in refining and tailoring your CV—but only if used wisely. For members of Chartered Accountants Ireland, the challenge is to harness AI for efficiency while maintaining authenticity, accuracy, and professional integrity. ✅ DO: Use AI to polish structure and language : Streamline formatting for clarity and consistency - Applicant Tracking Systems (ATS) are widely used by employers and recruitment firms. AI can help ensure your CV is clean, consistent, and easy to review, reducing the risk of being overlooked. Instruct the AI to reformat your CV to be more palatable to an ATS. Refine bullet points to highlight achievements and value-add - Instead of listing duties and responsibilities, use AI to sharpen your phrasing around measurable outcomes. For example: “Delivered audit efficiencies resulting in a 15% reduction in fieldwork hours.” “Implemented ERP system migration across three subsidiaries, improving reporting accuracy.” Ask the AI to suggest and enhance these elements in your cv. Tailor your CV to each role - AI will help you align your CV with keywords in job specifications. Tip:  Feed the job spec to the AI and then and ask it to align your CV with the required skills and competencies in the role. If you are pivoting into a different area of career direction AI tools can reposition the terms and grammar in your CV to be more pointed and bring your transferrable soft skills to the fore.   ✅ DO: Let AI help with tone and grammar : Ensure professional, confident language AI can eliminate passive phrasing and sharpen your tone so that your CV reads as achievement-focused rather than task-oriented. Instruct it on latter iterations to ‘sharpen the tone and make the terminology more achievement focused’. Highlight quantifiable results: Employers value tangible outcomes. AI can help you reframe statements to emphasise your measurable impact: “I reduced monthly reporting cycle by 30%.” “I led the €5M budget planning process across multiple jurisdictions.” ✅ DO: Use AI for brainstorming: Generate strong action verbs - AI can suggest impactful verbs such as streamlined, negotiated, implemented, advised, or optimised—helping you avoid repetition. Identify transferable skills - Particularly useful if you’re pivoting from practice to industry or vice versa. AI can help you surface skills such as stakeholder management, regulatory compliance, or systems implementation that may not be obvious at first glance. ❌ DON’T: Fabricate qualifications or experience Avoid inflated claims - AI tools may suggest impressive-sounding credentials or roles. Do not overinflate your actual experience or core skills and expertise.  Misrepresentation can damage your personal brand and career prospects. Always carefully review the revised CV and check your level of comfort with it. ❌ DON’T: Submit without personal review Guard against generic output - AI-generated CVs can sometimes sound formulaic or misaligned with what an employer expects to see in a CV. Proofread, personalise and put your own stamp on it which may mean small rewrites in sections. Include specific context - Employers value detail such as: Client sectors (e.g., construction, agri-food, financial services). Company names where acceptable. Employer revenue and employee numbers to give scale context. Eg - Software proficiencies (Sage, Xero, SAP, Oracle). Eg - Regulatory experience (Irish GAAP, IFRS, FRS 102, Central Bank reporting). Size and scale of current company eg- Number of employees in the company. Number of people you directly manage. Detail re the turnover level of the company for context. ❌ DON’T: Overuse buzzwords Substance over style Phrases like “dynamic leader” or “results-driven” are acceptable only when backed by evidence. Employers prefer concrete achievements over vague descriptors. Let your outcomes speak for themselves - Replace generic claims with specifics: Instead of “innovative thinker,” write “developed a tax planning strategy that reduced liabilities by €200K.” ⚖️ Final thoughts AI is a powerful tool for members seeking to sharpen their CVs. It can enhance clarity, structure, and relevance, but it is not a substitute for authenticity! Your CV should reflect your unique career journey, values, and professional integrity. Make sure your personality and ambitions shine through in the document. Think of AI as your assistant, not your author. Use it to polish, but ensure the final document is unmistakably yours. If you’d like tailored support for your CV or career progression, reach out to your Chartered Accountants Ireland Careers Team—we can provide personalised guidance aligned customised to your individual situation.

Artificial Intelligence (AI) is increasingly being used in recruitment processes to modernise candidate screening, assess skills, and predict job fit. AI-driven interviews can include automated video assessments, chatbot interactions, and algorithm-based scoring. Preparing for such interviews requires understanding the technology, adapting communication strategies, and ensuring compliance with best practices. Understand AI in recruitment AI tools in interviews typically perform: Video analysis: evaluates facial expressions, tone, and speech patterns. Natural Language Processing (NLP): assesses word choice, clarity, and relevance. Skill testing: automated coding challenges or scenario-based questions. Predictive analytics: matches candidate profiles to job requirements. Tip: research the specific AI platform used by the employer. Prepare for video-based AI interviews Technical setup: Ensure a stable internet connection. Use a high-quality webcam and microphone. Test lighting and background for clarity. Presentation: Dress professionally. Maintain eye contact with the camera. Speak clearly and at a moderate pace. Practice: Record yourself answering common questions. Use AI-based mock interview tools to simulate the experience. Optimize communication for AI Structured responses: Use the STAR method (Situation, Task, Action, Result) for behavioural questions. Keyword alignment: Incorporate relevant industry and role-specific keywords. Avoid ambiguity: AI systems favour clear, concise answers over vague statements. Demonstrate emotional intelligence While AI may analyse tone and sentiment, authenticity matters: Show enthusiasm without exaggeration. Maintain a calm and confident disposition. Prepare for gamified or cognitive assessments Some AI-driven processes include: Problem-solving games. Personality assessments. Tip: practice logic puzzles and familiarise yourself with game-based assessments. Address bias and fairness Be aware that AI systems can have biases. If concerned, ask the recruiter about fairness measures and appeal processes. Post-interview follow-up Send a thank-you email to the recruiter. Reiterate interest and highlight key strengths. Conclusion AI-enhanced interviews require both traditional preparation and technical awareness. By understanding the tools, practicing structured responses, and ensuring a professional setup, candidates can maximize their chances of success.

Artificial Intelligence (AI) is no longer a science fiction, it’s a present-day reality redesigning recruitment practices across a variety of industries. One of the most significant areas of transformation is the job interview process. From initial screening to final interviews, AI is influencing how candidates are assessed and how employers make decisions. But what does this mean for hiring practices, candidate experience, and fairness? Let’s explore. AI-powered screening and scheduling Recruitment teams would traditionally spend hours reviewing resumes and coordinating interview schedules. AI tools now automate these tasks, using algorithms to: Scan resumes for keywords and skills aligned with job descriptions. Rank candidates based on experience and qualifications. Schedule interviews through integrated calendar systems. This efficiency reduces time-to-hire and frees recruiters to focus on strategic decisions. However, it also raises questions about whether keyword-based filtering overlooks unconventional but qualified candidates. This is one of the reasons why tailoring your CV prior to job applications is more important than ever. Video interview analysis AI-driven platforms are now recording interviews using machine learning. These systems assess: Tone and sentiment to gauge enthusiasm. Speech patterns for clarity, confidence, and pacing. Facial expressions and micro-gestures to infer engagement. While these understandings can help identify strong verbal communicators, critics argue that such analysis may disadvantage neurodiverse candidates or those from cultures with different communication norms. Also another potential pool of disadvantaged candidates are those who are speaking in their non-native language. Chatbots and pre-interview engagement AI chatbots are increasingly used to: Answer candidate FAQs prior to the interview taking place. Provide interview preparation tips. Conduct preliminary Q&A sessions. This creates a more responsive candidate experience and reduces recruiter workload. However, candidates often wonder whether they’re interacting with a human or a bot, which can affect trust, as many of us have experienced in when dealing with customer services chatbots. Bias reduction—or amplification One of AI’s core promises is reducing human bias by focusing on objective data. Yet, algorithms trained on historical hiring data can perpetuate existing biases, as those algorithms are developed and based on human process. For example: If past hires favoured certain demographics, AI may replicate that pattern. Language models might misinterpret dialects or accents as mentioned when discussing the AI screening process. To mitigate this, companies must implement ethical AI practices, including: Regular audits for bias. Transparent criteria for decision-making. Diverse training datasets. However, as it has been shown these types of audits can be difficult to conduct, as a company may not be willing to face that it has inherited biases. Candidate perception and trust Many candidates experience discomfort when they know an algorithm or AI system is evaluating them. This unease often stems from a few key concerns: Lack of transparency Candidates may not understand how the system works, what criteria it uses, or whether it’s fair. This uncertainty can feel intimidating. Fear of bias People worry that automated systems might reinforce biases or overlook qualities that a human interviewer would appreciate, such as personality or cultural fit. Loss of human connection Interviews are traditionally relational. When technology replaces or mediates that interaction, candidates can feel depersonalized. Perceived inflexibility Machines are seen as rigid—unable to interpret nuance, humour, or creativity the way humans can. The future of interviews AI will continue to evolve, integrating with: Virtual Reality (VR) for immersive job simulations. Gamified assessments to measure problem-solving and creativity. Predictive analytics to forecast long-term performance. Despite these advances, human reasoning remains essential for evaluating cultural fit, emotional intelligence, and nuanced communication, qualities that algorithms struggle to measure accurately. Key takeaways AI enhances efficiency but must be implemented ethically. Transparency and fairness are vital to maintain candidate trust. Human oversight will remain indispensable in final hiring decisions. AI cannot: Research the role and the organisation as effectively as you can. AI may provide information that is inaccurate or unrelated. You must research thoroughly yourself. If AI does offer information, be critical of this, can you check this is up to date? Provide personalised, informed feedback. AI output may be based on out-of-date information, it is often generic, and it can’t reflect on how your personal employability aligns with the role. Be aware that employers can use AI to see what information it generates about them. It is important that you do not directly copy material that AI produces. Implement your own insights. Final thought AI is not replacing interviews—it’s redefining them. Organisations that balance technological efficiency with human empathy will lead the way in creating fair, inclusive, and effective hiring processes.

Members of Chartered Accountants Ireland based in New York and the surrounding region gathered at the Consulate General Ireland in New York on Monday evening for a panel discussion event on the impact of artificial intelligence (AI) on business and the accountancy profession. The event was hosted by Institute Chief Executive Rosemary Keogh, President Pamela McCreedy and Director of Members & Advocacy Cróna Clohisey together with head of the New York member chapter Conall McGonagle.   Building and strengthening relationships Deputy Consul General Katie Daughen opened the evening welcoming members, the Institute leadership team and guests, including visitors from the New York State Society of CPAs, members of American Institute of CPAs (AICPA) and the IDA. Recognising Chartered Accountants as trusted business leaders, she emphasised the vital role that members play in today’s uncertain economic times due to their understanding of current economic and business conditions. Katie spoke about the importance of two-way US-Ireland business. She highlighted the need for proper implementation of the EU-US Trade Agreement and how the influence and vigilance of Chartered members can contribute to this. She emphasised the enduring ties between the US and Ireland, which both countries seek to protect and grow, citing the 31 million Americans who claim Irish heritage, the 781 Irish companies employing 202,000 people in the US, and 972 US firms employing 245,000 people in Ireland. Panel discussion: Trusted Business Leadership in an era of artificial intelligence   The panel speakers (Gavan Corr – CEO of Pazithi Group; Stathis Gould – Director of IFAC and Cróna Clohisey, with moderator John McCourt, owner of RSM) shared updates, experiences and insights, encouraging members and guests not to fear AI but to embrace it. Panellist Gavan Corr observed that AI is only as good as the data that goes into it. Those with technical expertise – including Chartered Accountants – will still be essential to maximising its potential and for reviewing its outputs. Auditors, he said, will be more valuable as they will combine the understanding of business with a mastery of AI. The discussion reinforced that while technology is evolving rapidly, human expertise and deep understanding of business remain critical for success. Building connections, building trust In her comments, Chief Executive Rosemary Keogh acknowledged the work and commitment of the New York chapter and chapter head Conall McGonagle FCA CPA. She noted that this new member network is building connections across and between the US and the island of Ireland, and thanked them for their contributions to the US and Irish economies and for promoting the brand and profession. Speaking on the importance of trust and its position as the "north star" of the Institute's Strategy27, Rosemary noted that in the context of uncertain times and fast-moving technologies, trust is the most highly-valued currency. She cited that Chartered Accountants continue to rank among the world's most trusted professions according to Edelman DXI's Trust Survey, and maintaining and strengthening this position is a central focus of Strategy27. President Pamela McCreedy echoed these sentiments and the theme of the event, noting that three in four organisations already rely on Chartered Accountants to ensure data integrity. She commented that "AI is not just a technical revolution; it’s a human one. It challenges us to think differently about judgment, ethics, and purpose. The future of trusted business leadership will depend on how effectively we balance innovation with integrity – harnessing technology, while holding fast to the values that define our profession” Staying connected In her comments during the event, Rosemary Keogh encouraged members to connect with peers locally through their district society or global chapter network supported by Executive Head of Global Engagement Zara Duffy and District and Global Member Manager Gilllian Duffy. She highlighted the profession's global significance and reach and outlined the growth plans of Strategy27 supported by the Institute teams. You can view photos from the event here. Watch a short video here.

From the Professional Accountancy team…... The Apply AI Strategy was launched in October 2025 by the European Commission. It aims to harness AI’s transformative potential by increasing and supporting AI adoption and integration across key industrial and public sectors, especially among small and medium-sized enterprises (SMEs). The Strategy encourages an AI first policy where AI is considered as a potential solution whenever organisations make strategic or policy decisions, taking into careful consideration the benefits and the risks of the technology.  The European Commission has also launched the AI Act Single Information Platform and the AI Act Service Desk to support implementation of the AI Act and to provide resources and tools regarding the AI Act requirements.           

On Thursday 29 May, Chartered Accountants and Sia launched our new Virtual Reality training programme aimed at developing Professional Scepticism skills in junior and trainee auditors. The launch provided us with the opportunity to break down barriers and perceptions that exist around VR in Learning & Development and allowed us to demonstrate what is possible when you take a chance on innovation!  Trish O’Neill, Head of Member Innovation at Chartered Accountants Ireland said: “When you spend so much time working on the finer details of a project you can forget the importance and potential impact of the final result. For the past year I have worked closely with Aisling Mooney, Catherine O'Doherty, and Charles Lonjaret on developing our second Virtual Reality programme. On Thursday 29 May we had the pleasure of sharing our VR design experience with colleagues and members from Chartered Accountants Ireland and Sia”. Speaking at the launch, Aisling Mooney, Learning Design Specialist at Chartered Accountants Ireland, shared some insights on the benefits of learning through immersive technology, saying that it “gives learners a consequence-free space to make mistakes, get real-time feedback, refine their approach, and even test the outcome of a wrong approach. This promotes active skill application and helps learners build confidence in their skills, which is essential for a well-rounded professional accountant”. The atmosphere at the launch was full of positivity and excitement and it was a great reminder that what the team has created is quite exceptional. Gary O'Sullivan, Managing Partner UK & Ireland at Sia noted that "it is the only one of its kind in the world!". Eamonn Siggins, Chief Integration Officer at Chartered Accountants Ireland remarked that “teaching professional scepticism through immersion in virtual reality is innovation in action.” More about the programme: We have created an on-site audit simulation training programme designed to help junior and trainee auditors develop their Professional Scepticism skills. Through Virtual Reality, learners are immersed in realistic audit scenarios, allowing them to practice professional scepticism in a safe environment where they are able to make mistakes, learn from their mistakes, and try again without the risk of real-life repercussions. By combining cutting-edge technology with deep industry expertise, we’ve created a global first in professional accounting education. For anyone with trainee accountants looking to improve their Professional Scepticism skills, we would be delighted to bring this training experience to your organisation. You can contact Trish O’Neill on patricia.oneill@charteredaccountants.ie to learn more. This initiative was made possible thanks to funding from Skillnet Ireland and our Network Manager Niamh Sheehan.

Grit Young outlines 10 key strategies to help Ireland’s tech firms unlock real value from their investments in artificial intelligence Artificial intelligence (AI) deployments in technology companies often fall short of expectations due to a lack of preparedness for the level of change and costs involved. To succeed, tech companies must shift their focus from merely integrating AI into traditional business processes to fundamentally rethinking and reinventing their operations for an AI-first era. To help ensure success, companies in Ireland should seize the opportunity to explore 10 key areas that can drive AI value creation. 1. Turn potential into performance improvement Tolerance for low returns on AI spend has reached a breaking point as organisations across all sectors seek tangible yields from their investment in the technology. Tech companies need to establish clear frameworks to measure the operational and financial impact of any AI solutions they implement. This will help to demonstrate quantifiable business value and return on investment, thereby differentiating their offering in an increasingly crowded market. 2. Drive growth through an agentic AI future Agentic AI can execute complex tasks independently, potentially transforming how tech companies and their customers operate their businesses.   Tech companies must capitalise on the opportunities presented by agentic AI to secure an early mover advantage for themselves and their customers. The emergence of AI agents that can enhance an organisation’s workforce could provide a viable solution for Irish companies seeking to avoid relocating their headquarters to overseas locations, such as to the US, to attract a broader talent pool, as has occurred in the past. Consequently, these agents could enable Irish organisations to scale operations in Ireland, ultimately benefiting the domestic economy. 3. Adopt outcome-based pricing models Pricing needs to move from a purely software-as-a-service (SaaS) subscription model to an outcome-based model aligned with customer value expectations. Customers increasingly expect tangible results from the products they purchase. Simply providing access or usage will no longer be sufficient to justify a charge; a clear outcome will be required. The move to outcome-based pricing will not be easy. Demonstrating outcomes and communicating them to customers will require a major shift in current practices. However, tech companies will likely have no choice but to do this, given changing customer demand. 4. Tap into the power of the AI-first operating model The competitive advantage enjoyed by born-digital tech companies over legacy organisations is now being outstripped by AI-born companies and their distinct structures and operating cultures. Simply bolting AI onto an existing operating model will not be sufficient to bridge this competitive gap. Organisations will need to rethink and reimagine their structures and operating models to become more like this new wave of competitors.  5. Unlock the value of AI expertise Tech companies have an opportunity to position themselves as key partners in their customers’ AI transformation journeys by offering tailored solutions addressing both the infrastructural and operational aspects of AI adoption. Customers will increasingly ask for AI offerings that do not require the costly replacement of legacy IT infrastructure and architecture. This presents an opportunity for tech companies that can provide such solutions. 6. Develop new skill sets for the AI era Tech companies can help drive growth by equipping their workforce with future-ready skills through targeted training programmes. By embracing more immersive training and learning environments, such as virtual and augmented reality, tech companies can better assess skill gaps, provide on-the-job support and ensure employee capabilities are fit for purpose. Today’s employees are increasingly demanding continuous learning in and through the use of emerging technologies. Embedding generative AI in learning and development programmes will help meet these expectations. 7. Involve all business functions from the outset Changes in tax, trade and regulatory requirements should be anticipated and addressed up front. In a rapidly shifting global tax and regulatory environment, treating tax or local regulatory issues as an afterthought—particularly when pursuing a transaction or making an AI-driven change to your operating model—is fraught with risk. Finance, tax and legal professionals should be involved in the process from the outset, so that decisions can be made without the risk of giving rise to unforeseen financial, tax or legal liabilities. 8. Use AI to bolster cyber defences The EY 2024 Global Cybersecurity Leadership Insights Study found that AI delivered a 40 percent increase in cybersecurity teams' efficiency. The technology offers more effective and comprehensive cybersecurity through the automation of threat and vulnerability detection and response. The built-in learning and adaptation capabilities of AI can help organisations stay ahead of the next major threat. The same tools are available to bad actors, who can use AI to amplify their ability to identify vulnerabilities and penetrate systems by an order of magnitude. Thus, it is all the more important for organisations to meet heightened cyber threats by using AI to strengthen defences and maximise incident response when breaches do occur. While there are many good cyber education programmes in Ireland, widespread adoption of AI as a cyber defence tool remains rare. The Irish government is actively promoting cyber security programmes and Enterprise Ireland provides grants to client companies to help bolster their cyber defences.  9. Explore ways to free up capital for AI investment While investment in AI capabilities is driving higher valuations for many tech companies, the cost of such investments is placing many of the companies concerned under strain. The capital-intensive nature of AI investment may require tech companies to consider the divestiture of non-core operational elements and underperforming assets. Such sales can provide a fresh source of capital for AI investment and create more streamlined and profitable businesses.  The big technology companies constituting the foundation of Ireland’s foreign direct investment landscape have historically expanded through acquisition rather than divestiture. If these companies consider divesting, it could impact their operations in Ireland. How any new buyer decides to manage the business will depend on their overall strategy, which could prompt them to keep, expand or scale back their presence in Ireland. 10. Engage with regulators The European Union’s AI Act, Digital Services Act, and General Data Protection Regulation are just a few examples of the regulations governing tech companies in Europe. Governments around the world are also developing policies and regulations on topics that affect tech companies. Regardless of size, tech companies can seek to influence the regulatory direction of travel by collaborating with industry groups and national government agencies. The aim should be to seek a more harmonised global regulatory environment which supports innovation while protecting citizens and addressing societal concerns. Grit Young is Technology, Media and Entertainment and Telecommunications Industry Leader at EY Ireland

Agentic AI could help close the gap between investment in AI and the low returns it offers businesses today. David Lee outlines its potential to future-proof growth and profitability The disconnect between the efficiency gains promised by artificial intelligence (AI) and its impact on corporate balance sheets is among most significant challenges facing businesses today. PwC Ireland’s latest CEO survey revealed that 94 percent of chief executives expect AI to be embedded in their workflows within three years. Less than a quarter can demonstrate any meaningful profitability improvements from their investment in AI, however. This gap demands attention as organisations move beyond AI experimentation. With close to one-third of Irish CEOs believing their organisation won’t exist in its current form 10 years from now, there is greater pressure to deliver higher returns from AI investment. Agentic AI—technology capable of autonomous decision-making and actioning—could offer the requisite bridge between personal productivity improvements and enterprise-wide transformation. The state of AI adoption AI sentiment around boardroom tables presents a striking paradox. Despite operating in unparalleled macroeconomic conditions, 93 percent of Irish business leaders maintain a remarkably positive outlook on revenue growth, according to PwC’s CEO Survey. This optimism exists alongside a profound recognition of the need for internal transformation, however. Close to 30 percent of Irish CEOs do not believe their organisation will exist in its current form within a decade. This creates a strong case for AI investment as business leaders race to reinvent their organisations. Six-month trends reveal an acceleration in structured AI implementation, with the proportion of Irish organisations kickstarting formal plans and active projects jumping from 50 to 70 percent. Herein lies the central challenge. While efficiency improvements are widely evidenced, only a quarter of these organisations have translated such gains into profits. This value leakage—from potential to profit—demands explanation. Agentic AI to the value gap If conventional AI has delivered incremental benefits without proportional financial returns, Agentic AI could offer a more compelling proposition. The distinction is not merely technical but fundamental to how value is created and captured. Agentic AI—systems capable of autonomous decision-making, action-taking and process optimisation—represents a shift from what might be termed “intelligent data manipulation” to “intelligent workflow execution”. This transition is the difference between personal productivity and enterprise productivity; between automating discrete tasks and reimagining entire processes. Diverse applications from all areas of the business can be united in their focus on end-to-end processes, rather than isolated tasks. This is precisely the shift needed to bridge the gap between efficiency and profitability. Strategic implementation framework Translating Agentic AI’s potential into sustainable financial returns requires a deliberate approach that strikes a balance between innovation and pragmatism. The following framework offers a pathway. The progression from conventional to Agentic AI implementation is evolutionary rather than revolutionary. The most successful organisations establish proof points through targeted deployments before attempting wholesale business model reinvention. This approach creates the reference experiences necessary to build internal confidence and stakeholder support. Successful and sustained AI adoption must also address obstacles simultaneously. A sequential approach—solving technical challenges before addressing governance concerns, for example—invariably creates impediments to scale. The most effective organisations pursue parallel workstreams that address technology implementation, organisational capability building, governance development, stakeholder engagement, cybersecurity and security enhancement. Particular attention should be paid to the behavioural change requirements. The adoption curve for AI follows predictable patterns—early enthusiasts, the pragmatic majority and reluctant laggards. Effective adoption strategies account for these different constituencies, rather than designing exclusively for the enthusiasts. The behavioural shifts required to support Agentic AI extend beyond initial adoption to continuous learning as capabilities evolve. This differs from the “train once” deployment models of traditional technology implementations. Implementation must also proceed at a pace that maintains trust across all stakeholder groups. Trust, once compromised, requires disproportionate effort to restore—a calculation that justifies measured progress over hasty deployment. Balancing innovation and pragmatism The value gap between AI’s promised benefits and its profit delivery represents the central challenge for business leaders navigating the current wave of technological disruption. With nearly a third of Irish CEOs questioning their organisation’s future in its current form, the imperative to bridge this gap has never been more acute. Agentic AI offers a pathway from incremental improvement to fundamental transformation by shifting focus from isolated task automation to orchestrated process reimagination. Organisations demonstrating measurable financial returns have moved beyond the “faster horses” mindset to rethink how work itself should be structured and executed. Yet, technology alone cannot close the value gap. Successful implementation requires simultaneous attention to business case development, organisational capability building, governance structures, stakeholder trust and security considerations. The most effective approaches strike a balance between innovation ambition and implementation pragmatism, building reference experiences before attempting wholesale business model reinvention. The most valuable lesson from early adopters is perhaps counterintuitive: the strongest financial returns often come, not from cost reduction through displacement, but from capacity expansion through augmentation. As organisation’s progress from experimentation to enterprise adoption, they would do well to remember that AI is not just a “new tool”. Rather, it represents a fundamental shift in how work is conceived and executed. Those who approach it merely as a means to do existing things more efficiently will find themselves with faster horses in an age that demands flying cars. David Lee is Chief Technology Officer at PwC Ireland

From the Professional Accountancy team…... The Irish Department of Public Expenditure, NDP Delivery and Reform has recently published a webpage containing Artificial Intelligence Resources. It contains information and links on a range of resources and practical tools designed to support the adoption of AI in the Public Service. This includes Guidelines for the Responsible Use of Artificial Intelligence in the Public Service and a tutorial dedicated to the AI Guidelines to assist participants in applying the guidelines in their own workplaces.   This information is provided as resources and information only and nothing in these pages purports to provide professional advice or definitive legal interpretation(s) or opinion(s) on the applicable legislation or legal or other matters referred to in the pages. If the reader is in doubt on any matter in this complex area further legal or other advice must be obtained. While every reasonable care has been taken by the Institute in the preparation of these pages, we do not guarantee the accuracy or veracity of any resource, guidance, information or opinion, or the appropriateness, suitability or applicability of any practice or procedure contained therein. The Institute is not responsible for any errors or omissions or for the results obtained from the use of the resources or information contained in these pages.          

From the Professional Accountancy team…... In May 2025 the European Commission published a Q &A page on AI literacy. Article 4 of the EU AI Act requires providers and deployers of AI systems to ensure a sufficient level of AI literacy for their staff and any other users who are interacting with AI systems. It entered into application on 2 February 2025. Most readers are likely to be AI deployers meaning users of AI. Questions and answers are provided such as what is literacy for Article 4 and what should be the minimum content to consider for an AI literacy programme complying with Article 4.   This information is provided as resources and information only and nothing in these pages purports to provide professional advice or definitive legal interpretation(s) or opinion(s) on the applicable legislation or legal or other matters referred to in the pages. If the reader is in doubt on any matter in this complex area further legal or other advice must be obtained. While every reasonable care has been taken by the Institute in the preparation of these pages, we do not guarantee the accuracy or veracity of any resource, guidance, information or opinion, or the appropriateness, suitability or applicability of any practice or procedure contained therein. The Institute is not responsible for any errors or omissions or for the results obtained from the use of the resources or information contained in these pages.  

Readers may be interested in the Massive Open Online Course (MOOC) which the Law Society will be running on Artificial Intelligence. The course will run over a period of 5 weeks from 10 June until 8 July. It is free and is open to everyone and anyone who has a general interest in learning more about AI developments. To find out more about the course and to register you can click here https://mooc2025.lawsociety.ie/    

Artificial intelligence is rapidly becoming an integral part of daily life, but many organisations have yet to fully grasp its potential, limitations and associated risks, writes David O’Sullivan The introduction of the European Union’s Artificial Intelligence (AI) Act means organisations are now legally required to ensure that employees using AI, as well as those impacted by its outputs, possess adequate AI literacy. AI literacy is the ability to understand, evaluate and interact effectively with AI systems. It encompasses recognising risks and opportunities, interpreting AI outputs and making informed deployment decisions. Ensuring AI literacy within an organisation isn’t just about compliance – it reduces risk, fosters innovation and drives competitive advantage. For businesses seeking to enhance their AI literacy, the European Commission offers detailed guidance, accessible in their online library: AI Literacy Learning Repository. Leading organisations integrate AI literacy into AI governance frameworks, ensuring clear roles, responsibilities and key performance indicators. Here are the six most effective strategies. 1. Tailored training for different levels of expertise A one-size-fits-all approach to training rarely works. Successful organisations provide: Foundational courses for employees new to AI; and Advanced technical training for developers and data scientists. 2. Hands-on learning with practical applications The best way to understand AI is to use it. Companies should offer their employees: Workshops, case studies and simulations to demonstrate AI’s practical impact; and AI sandbox environments for employees to test and experiment with AI safely. 3. Role-specific AI training Different teams utilise AI in different ways. Finance teams, product managers and engineers all interact with AI in various ways. Tailored training can help to ensure employees receive the relevant knowledge necessary to integrate AI into their workflows effectively. 4. AI mentorship and cross-department collaboration Encouraging knowledge-sharing between AI experts and employees helps bridge skill gaps. Some companies establish AI mentorship programmes where experienced employees guide their peers in AI adoption. 5. Embedding responsible and ethical AI practices Many organisations are integrating responsible AI principles into their training, focusing on transparency, fairness and compliance with AI regulations such as the EU AI Act. In Ireland, the Government introduced principles for public sector organisations early in 2024, and these are still relevant today. 6. Continuous learning AI is evolving rapidly. Training should be ongoing with regular updates and refresher sessions to keep pace with advancements. The impact of AI literacy When AI literacy programmes are effectively implemented, organisations experience significant benefits, including: Increased AI adoption and engagement: Companies have seen an increase in employee participation in AI training and a higher usage of AI tools in daily tasks. According to the AI Literacy Learning Repository, one organisation that implemented an AI literacy programme reported a 30 percent increase in AI training participation and a 65 percent rise in AI tool utilisation. Improved workforce confidence and innovation: Employees who are comfortable with AI use it effectively, leading to better decision-making and new ideas. Operational efficiency gains: AI literacy helps automate repetitive tasks, streamline workflows and boost productivity. New AI-driven offerings: Some organisations have leveraged AI literacy training to upskill employees, leading to new AI-driven products and services. Greater consumer trust: Companies that prioritise transparency in AI usage – and educate affected individuals – see higher trust levels. Some businesses even involve clients in AI training sessions. Making AI literacy a business priority Organisations cannot afford to overlook AI literacy, given our rapidly changing world and the requirements of the EU AI Act. Investing in education, practical training and ethical AI practices equips employees with the skills they need to work effectively with AI and allows leadership to make informed decisions on deployment and controls. By addressing challenges and leveraging the best strategies, companies can build an AI-literate workforce that drives innovation, enhances efficiency and ensures responsible AI use while meeting compliance objectives. AI literacy isn’t just about understanding how AI works; it’s about ensuring businesses and employees can utilise AI effectively to create meaningful and positive outcomes. If your organisation hasn’t yet prioritised AI literacy, now is the time to start. David O’Sullivan is Director of Privacy, Digital Trust & AI Governance at Forvis Mazars

A new report from Chartered Accountants Worldwide (CAW) reveals significant enthusiasm about the use of AI in the profession, with 85% of respondents expressing willingness to use AI tools - and 91% of those aged 18–24 already using the technology. Members of Chartered Accountants Ireland were surveyed alongside respondents from 13 other Chartered bodies around the world, with the findings showing that AI is increasingly integrated into business processes and that the profession is actively embracing change. Chartered Accountants Ireland is the largest professional body on the island of Ireland, representing almost 40,000 members and educating 6,600 students. Key findings: AI is reshaping the profession - 85% of respondents are willing to use AI tools. This rises to 91% among 18–24-year-olds and is accompanied by strong understanding (59%) of the potential uses of AI in accountancy.   AI is already in use - 83% of 18–24-year-olds use AI tools weekly - mainly for general productivity, data entry, reconciliation of accounts, and financial reporting. While 80% of 18–24-year-olds feel confident using AI in their roles, only 47% of those aged 55+ share that confidence. The most used tools are Gen AI chatbots, Microsoft Copilot and business intelligence tools. 45% say AI is already helping them to work more effectively and efficiently. 31% say they are already using traditional AI in their job. 29% are already using generative AI (GenAI) in their job.   Barriers to adoption - 52% of those surveyed state that the biggest barrier to AI adoption is insufficient skills and training. 30% also cite data security concerns as a reason they do not use AI more frequently.   Upskilling is essential - despite a high willingness to use AI, there is a skills gap and feeling of unpreparedness for the changes AI will bring. 30% have participated in AI-related training through their organisation, but 92% are likely to participate if offered the opportunity. 65% expect to receive AI-related training from their professional body, while 32% expect it from employers. Commenting Barry Dempsey, Chief Executive of Chartered Accountants Ireland, said “It is really encouraging to see strong early adoption and enthusiasm in the profession. It is clear from the research, however, that current usage is largely focused on general-purpose productivity tools, rather than technical work, with much of the momentum driven by individual initiative and self-directed learning. “Only 30% have participated in AI-related training through their organisation, and among those that have not engaged in training, 61% say it is because it is not offered. There is a high employee willingness to engage, with 92% saying they are likely to participate if offered the opportunity, so bridging this gap will be crucial to unlocking the further potential of AI for the profession. Smaller practices and businesses may not have the resources to deliver tailored AI training, so it’s essential that professional bodies like ours step in to bridge that gap. There is also an opportunity for the government to play a role in supporting widespread digital upskilling, particularly for SMEs, to ensure no part of the profession is left behind as AI reshapes the business landscape.” AI is an opportunity, not a threat There is consensus in the findings that AI will augment, rather than replace, the Chartered Accountant’s role, with human intelligence remaining at the heart of the profession. Chartered Accountants will continue to rely on core skills, and the training priorities of respondents reflects this: Critical thinking (77% rate this as a priority) Data privacy and security (71% rate this as a priority) AI ethics (66% rate this as a priority) Barry Dempsey continued: “Priorities such as critical thinking, an emphasis on data privacy and security and AI ethics go to the very heart of chartered accountants as trusted business leaders. Critical thinking will continue to be crucial in scrutinising and applying AI insights to provide effective advice to business/clients. Similarly, with increased AI use, it's even more important to ensure structured, effective training to use technology ethically and protect data responsibly. “56% of respondents agree that incorporating AI makes accountancy more attractive as a career choice and we remain committed to equipping the next generation of Chartered Accountants with the skills and mindset to lead in a world shaped by innovation, from their first steps as students to their roles as future business leaders.” Read the report in full CAW_AI-in-Accountancy-web.pdf  Read media coverage Chartered accountants confident about adoption of AI in their work, survey finds – The Irish Times 

From the Professional Accountancy team …..CCAB-I  has prepared Technical Alert TA01-2025  containing some pointers for firms to consider in their use of artificial intelligence (AI). All firms should be considering putting a policy in place whether it’s just to cover basic points such as if your trainees (or other employees) are permitted to use AI in the office or whether you need more extensive provisions. The pointers in our technical alert and links included in it may be of use to members.   This information is provided as resources and information only and nothing in these pages purports to provide professional advice or definitive legal interpretation(s) or opinion(s) on the applicable legislation or legal or other matters referred to in the pages. If the reader is in doubt on any matter in this complex area further legal or other advice must be obtained. While every reasonable care has been taken by the Institute in the preparation of these pages, we do not guarantee the accuracy or veracity of any resource, guidance, information or opinion, or the appropriateness, suitability or applicability of any practice or procedure contained therein. The Institute is not responsible for any errors or omissions or for the results obtained from the use of the resources or information contained in these pages.    

The AI revolution is well underway, driving unparalleled progress in business and finance. Microsoft Ireland CFO Áine Nolan shares her experiences and insights Artificial intelligence (AI) represents a valuable opportunity for Ireland to enhance our productivity and solidify our digital leadership in Europe.  This is according to Áine Nolan, FCA and Chief Financial Officer with Microsoft Ireland, who spoke at the recent Chartered Accountants Ireland Technology Conference, about how AI is revolutionising the finance function and driving unprecedented efficiencies.  “We have a thriving tech scene in Ireland, a highly educated workforce and really smart government policies. We can really become a hub for AI advancements,” Nolan said. The potential is significant, driven by the rapid emergence of AI as a commercial proposition and its popularity with users in both their lives and work. “The rate of AI adoption currently is somewhat unprecedented,” said Nolan. “Generative AI is capturing, distributing and democratising intelligence for everyone and that is a powerful concept.”  AI uptake in Ireland Microsoft Ireland recently partnered with Trinity College Dublin Business School to conduct research into the uptake of generative AI in the Irish market. Published in March 2024, the Generative AI in Ireland 2024 report found that 49 percent of respondents were already using the technology in some form in their organisation. “This research is less than a year old and already out of date, which just shows you how fast the rate of uptake is. We are due to release new research in March this year, which shows that adoption rates have since risen to about 70 percent,” Nolan said. Despite its proliferation in Irish workplaces, not all employers are, as yet, fully equipped to manage the implications of the AI age. “Through our research with Trinity, we have found that employees are bringing their own AI to work, with or without their employer’s consent. This ‘shadow’ gen AI culture creates risks for employers who really need to have guardrails in place,” Nolan said. “There is also sometimes a view that AI is just an add-on productivity tool you can slot into your existing workflows, but this fundamentally underestimates the magnitude of behavioural change and organisational transformation needed to unlock its value.” It will take time and a great deal of change management to integrate AI successfully as a new dimension of work, Nolan said. “People often make the mistake of simply asking how they can apply AI to their existing processes, but, fundamentally, they should be asking what they need AI to do and how it can make their processes more efficient or facilitate innovation—even creating a new service for our customers, for example.” The dawn of the AI agent Although many people currently use AI as a kind of “virtual assistant”, helping with everyday tasks, such as organising their work calendar or automating note-taking during meetings, the technology is set to assume a far more prominent and proactive role. “In the future, AI will operate on your behalf—as an agent—allowing you to eliminate tasks from your plate altogether,” Nolan explained. “This might mean making autonomous decisions for your IT helpdesk and, eventually, managing your full device refresh, from examining your POs right through to ordering new devices, checking your budgets and getting the necessary human approvals at the end of the process.  “A more complex example might involve AI looking after lead generation for your business by sourcing and emailing potential customers or acting as a customer support agent in a much more complex way than a chatbot, where it is actually making decisions on behalf of your organisation.” Microsoft and AI in finance Already, Nolan and her finance team at Microsoft Ireland are reaping the benefits of the organisation-wide implementation of the software giant’s AI technology. “Our global CFO Amy Hood consistently challenges our finance team to use our own technology to improve our processes. Her mantra is really clear—by adopting innovative technologies, finance will strengthen its business leadership through compliance, accuracy and efficiency.” And, as CFOs across all organisations assume an increasingly strategic business role, AI will become even more fundamental to their work day-to-day. “The role of the CFO is changing rapidly and, as finance leaders, we need to play a lead role in developing a clear AI strategy, ensuring our organisations have the necessary capability, technology and stakeholder buy-in. The rate of AI adoption is unprecedented and we need to be ready,” Nolan said. “In the last 12 months alone, I have seen big changes in how our own AI at Microsoft has been able to generate intelligent comments for us, as we work through our balance sheet and P&L variance analysis,” Nolan said. “We have had a big win in the efficiency of our contract review process, where we once had a full revenue recognition team analysing all of our contracts to account for them. “Now, we have AI reading 10,000 contracts a year and sorting them into low-, medium- and high-risk categories for us.” This means the revenue recognition team is only required to review high-risk contracts manually.  “We’ve had other big wins in journal entry anomaly detection, which has helped reduce risk on our financial statement—and our AI is now able to produce the first draft of the statement, reducing time spent on this work by about 15 percent.” Microsoft’s generative AI is creating models that recognise patterns in the financial planning and analysis data used to predict outcomes. “We’ve moved from bottom-up to top-down budgeting, reducing time spent on budgeting analysis from six months to six weeks,” Nolan said.  “This means we have much more time to think strategically and analytically—and to have a seat at the table in terms of our influence in the wider organisation. For us, AI is well and truly here.”

Liam Cotter charts the road ahead and critical importance of data for Irish organisations preparing for the AI revolution Right now, many organisations are experiencing caution, confusion—or both—in relation to artificial intelligence (AI). They are unsure about generative AI (GenAI), how it differs from previous AI iterations, and whether it can add value for them. With the first milestones of the European Union’s AI Act due to come into force in February 2025, focused on prohibiting AI systems posing unacceptable risk, organisations are concerned about falling foul of regulation. They are keen to ensure that any AI model introduced to help their business, undergoes rigorous testing to ensure it is fair and doesn’t have bias baked in. There are also more generalised fears regarding the cost of moving too quickly and developing the wrong solutions, however, as well as the “opportunity cost” of moving too slowly and thus failing to capture the benefits of the right opportunities. Data-based decisions Regardless of what stage an organisation has reached in its adoption of AI and GenAI, one thing holds true: the key to success is data. The only way to ensure quality AI outputs is to provide quality inputs. The way we manage and store data for the AI age differs from how we have done so in the past. Thus, even though the same fundamental rules apply, your data capture and entry systems may not be robust enough to handle AI demands and this could put you at a competitive disadvantage. Part of the problem with readying your data for AI transformation is the sheer amount of hard work involved, which may not appear not to offer a lot of value. This is because this work involves run-of-the-mill data generated from day-to-day operations. The key to the successful adoption of AI tomorrow is ensuring everybody in your organisation is aware of data management today. It is about ensuring everyone is measuring the quality of their data right across the organisation so they can stand over what it presents. For organisations that previously placed little value on the data they generate, this shift will require a culture change. It may also require different parts of the organisation to pool data—such as combining sales and stock databases rather than keeping them siloed, for example. In companies involved in mergers and acquisitions, it means ensuring you fully understand your data's lineage. The time to act is now The past 12 months have seen a growing realisation among organisations of the potential importance of AI as a lever for competitiveness. It is increasingly viewed as a valuable tool to drive digital transformation, enabling them to become more flexible, be faster to market, provide a better customer experience and more. Most of what AI will do has yet to be “dreamed up”. To put its scale in context, somewhere in the world, a data centre—the building block that powers the AI revolution—opens every two days. Organisations need to act to keep up. The first step is understanding the regulations and timeframes that are being rolled out under the EU AI Act. Next, identify use cases and develop them. Experiment—and if you are going to fail, fail fast. Get involved and discover the value in AI. People-powered data Understand the behavioural risks, too.  A lot of the work involved isn’t about technology at all. It’s about people. You can introduce the best technology in the world, but it's useless if staff don’t collect, curate and manage their data correctly. Everyone in your organisation must be able to stand by the accuracy of their data, which means good data practices must be applied to all business processes. In many organisations, this means investing in data capabilities, including staff training, and appointing a Chief Data Officer responsible for driving data literacy and good data management practices throughout the organisation, from the bottom to the top. To succeed, data management must be seen as a core, valuable component of what everyone does, regardless of their role. Break down the barriers Barriers to achieving effective AI readiness include an organisational culture that hasn’t yet caught up with the importance of data, allied to poor systems and processes that ensure people don’t understand the implications of getting it wrong. The real barrier is, however, that all of this takes work. Readying your data systems for AI is a pain, and sometimes, people can see no value in it. Once you can stand over your data, knowing it is of good quality and understanding its lineage, your organisation will likely be in pretty good shape because you can then move on and digitise your key business processes with confidence. The AI revolution starts and ends with data. Don’t underestimate the effort required to get good quality, well-managed data. It is the foundational work that cannot be avoided. Equally, don’t underestimate the impact. Once you have good data systems in place, you can confidently move forward and capture the full breadth of AI benefits that await.  Liam Cotter is Technology Practice Lead at KPMG

Data use is skyrocketing, raising ethical concerns beyond regulatory compliance. Colm McDonnell explores how embedding digital ethics ensures fairness, transparency, and accountability in organisations Data has become an integral part of modern life, and its usage is growing exponentially. From businesses to governments, organisations are collecting, storing, and analysing vast amounts of data to gain insights, make decisions, and develop new products/services. However, with great power comes great responsibility. The more data organisations process, the bigger the spotlight on them, not only to ensure regulatory compliance but also to focus on the significant ethical concerns resulting from data collection and its use. Furthermore, the growing use of technology, including artificial intelligence (AI) and robotics, stems concerns about the extensive use of data and the potential for misuse. What is digital ethics? Doing the right thing, regardless of legislation, takes you into the field of ethics. Organisations usually focus on various regulatory obligations that they must comply with, but organisations also have a responsibility to their stakeholders, including their employees, customers, vendors, and investors. This goes beyond regulatory compliance. Accountability can be complex to define and demonstrate, often leading organisations to set out some principles they should adhere to such as privacy, fairness, non-discrimination, transparency, and more, while processing data. Embedding digital ethics into an organisation involves promoting the moral values of the organisation through the alignment of data processing practices and processes with those values. Digital ethics refers to a set of principles and moral values that guide the responsible and ethical use of data. The following eight guiding principles define an approach to AI and digital ethics. Code of digital ethics All organisations should establish a code of digital ethics that sets out their commitments to ethical data practices. Digital ethics by design should be considered right from the outset of any product development, product enhancement or any proposed processing of data. Periodic training and awareness programmes should be rolled out to promote awareness of ethical data processing practices. This will eventually build a culture of trust, transparency, and safety within the organisation. Human oversight and determination Organisations must make sure AI systems do not take the place of human accountability and responsibility. There needs to be human oversight and safeguards in place to prevent misuse of data. There should be cross-functional stakeholder collaboration and effective governance. Proportionality, do no harm, safety and security AI systems should only be used as much as is required to accomplish a valid goal. Risk assessment should be utilised to prevent any potential harm from these types of applications. Fair and transparent algorithms Organisations must ensure that their decision-making and algorithms are fair and impartial. This can be achieved through ongoing monitoring and periodic testing. Transparency and explainability Data should be collected and used with transparency, so individuals understand how their data will be utilised thereby allowing them to make informed decisions about whether to share their data. Further, where deemed necessary, before collecting data, organisations should seek consent from individuals. This consent should always be freely given and be fully informed. Inclusion Unconscious or conscious bias can affect inclusivity in an organisation. Organisations should take the necessary steps to ensure the processing of data does not result in or hide discrimination or bias. Vulnerable data subjects who are the most susceptible to negative consequences of processing require additional consideration. Autonomy, freedom, respect, privacy, and dignity Individuals must be able to make their own decisions, take their own actions, and make their own choices. Processing of data should not constrain human beings in how they want to live their lives. Autonomy for individuals to control how their data is processed should be ensured. The processing of the data should be respectful of human values. Specifically, when the processing is carried out through AI, the outcome should not dehumanise individuals. Sustainability AI innovations should be evaluated to consider their effects on the environment and their ability to sustain through periods of time. These innovations should align with the organisation’s sustainability goals. Colm McDonnell is Partner of Risk Advisory at Deloitte

GenAI is evolving rapidly and has the potential to enable CFOs to deliver valuable new strategic insights and predictive analysis to their organisations, writes Vickie Wall Almost every aspect of the finance function has benefited from technological advances in recent years. Those advances include artificial intelligence (AI), natural language generation (NLG), and optical character recognition (OCR). Automation has freed up time to move beyond financial reporting and engage in the provision of strategic business insights and forecasting for the entire business. Many large organisations have been using machine learning and related technologies to assist in areas like fraud and anomaly detection, transaction processing, business forecasting and customer management. However, we are now on the cusp of a potentially transformative leap forward due to the advent of generative AI (GenAI). This technology can democratise data science and analytics and put coding skills in the hands of just about everyone with the ability to interact with it. It will no longer be necessary for a CFO or finance team member to be skilled in specific programming languages or database query skills. Once they can explain in plain language what they want GenAI to do, the technology should do the rest. AI will be able to take structured and unstructured data from within the organisation and external sources to provide various outputs like trend analyses and forecasts, with numerous variations based on factors like seasonality or user-defined future events. Having done so, it can offer best, mid and worst-case scenarios to aid C-suite decision-making. This capability, which was formerly the sole preserve of skilled data analysts and programmers, is now in the hands of everyone with access to GenAI and who has received basic training on how to interact with it and is willing to experiment. Understanding data science Certain skills are required no doubt, not least of them the ability to understand accounts and financial reporting standards. Beyond that, CFOs and finance teams will need to become familiar with data science, at least to a small extent. This will not necessarily present a major challenge as finance professionals have been using business intelligence systems for many years. However, they will have to develop a much deeper understanding of the topic if they are going to uncover the next layer of value which lies within the data at their disposal. Having the tools to carry out the analysis on your behalf is just one-half of the equation. Knowing what you want to achieve through the analysis is the other. The importance of “prompting” and the ability to do this well will become a key skill in extracting the most from these tools. Currently, GenAI is viewed as a separate tool that operates independently of other software systems. That will remain so for certain general applications, but increasingly it will become an integral part of the software systems used every day in organisations. In future, CFOs and finance professionals will use AI to interact with those systems in different ways. They will use natural conversational language to create reports, run analyses, and produce forecasts. The skill will lie in knowing what questions to ask and recognising where the data’s potential value might lie. The need for knowledge beyond AI A new approach to data gathering will be required when it comes to GenAI. CFOs will need to look beyond finance to other functions and departments to source data for use in forecasts and strategic guidance, as well as to understand those departments’ key needs. That will require knowing where data gets sourced from, how it flows from one system to another, where the bottlenecks lie, where data is leaking or getting lost, and what issues need to be addressed to improve data availability. Having access to that data from across and outside the business in the form of external market reports will be paramount to realising the benefits of GenAI in the finance function. GenAI is far from faultless, however, and trust is a major issue. For example, no CFO will be willing to sign off on financial statements if the finance team does not know how to check the GenAI outputs they are based on. Explainability is another challenge. If a certain system is being used to produce statements or reports, the CFO must be able to explain how it works and how it comes to its conclusions. And therein lies another issue: inconsistency. At present, you can ask GenAI the same question 50 times and get a different answer on each occasion. That may be acceptable for marketing content, but it certainly will not work for financial statements and forecasts, where trust and data integrity are of utmost importance. Fortunately, GenAI developers and organisations integrating the technology into other software systems are addressing these issues and the technology is improving at a rapid pace, but it is still not at a stage where it can be fully relied on. Humans will need to be always kept in the loop to verify the outputs and ensure that the systems are not hallucinating or being creative when they should not be. The use of GenAI by CFOs and finance functions to support strategic decision-making in their organisations will soon be a competitive differentiator. This means that even if they are not currently using GenAI in their organisations, CFOs need to experiment with it and understand how it works, what it can do, and the value it can bring to the business. More importantly, they need to help instil an experimental culture within the organisation where employees at all levels are encouraged to bring forward ideas for use cases without fearing repercussions for aborted pilots or lack of investment. CFOs who fully embrace this early-stage trial and error will ensure that they are not left behind when the technology evolves to a point where it can be trusted, is consistent in its outputs and is fully explainable. Transforming finance functions GenAI has the potential to transform the way finance functions operate and the strategic insights and guidance that CFOs can bring to their organisations. To realise that potential CFOs will need to understand the business needs across different departments, gain access to data from across the organisation, develop basic data science skills, and perhaps experiment with the technology to understand how it works, how to interact with it and how it can deliver value to the business. Vickie Wall is Financial Accounting Advisory Services Leader at EY

The ethical use of AI and how it is governed today and as it continues to evolve in the years ahead is top of mind for many in the profession. Accountancy Ireland asks three Chartered Accountants for their take on the ethics of AI Owen Lewis  Head of AI and Management Consulting KPMG in Ireland It is crucial for all of us in the profession to ensure the integrity and transparency of solutions driven by artificial intelligence (AI).  We must audit and validate AI algorithms to ensure they comply with regulatory standards and ethical guidelines. Monitoring systems for biases and inaccuracies is also crucial to ensuring that financial data and decisions remain fair and reliable. By providing independent oversight, we can help to maintain trust in AI-driven financial processes and outcomes for clients.  Where AI is used to inform large-scale decisions, it should be supplemented with significant governance measures, such as explainability, transparency, human oversight, data quality and model robustness and performance requirements. This technology is continuing to advance rapidly, and we need to be open to both its current and potential capabilities.  By putting the correct governance mechanisms and controls in place – beginning with low-risk test applications and building from there – organisations can adopt AI safely and obtain real benefits from its use. I am working with organisations to help them think through what AI means for them, develop strategies for its adoption, put the necessary governance and controls in place, scale solutions sensibly and ensure business leaders get real value from their investment.  Whatever their goal may be – more efficient operations, accelerated content generation or improved engagement with stakeholders – we help organisations decide if AI can help, and if it can, how to use it in the right way. >Bob Semple Experienced Director Governance and Risk Management Artificial Intelligence (AI) is one of the most misunderstood, yet transformative, technologies impacting the way we work today. Here are 10 essential steps Chartered Accountants should take to navigate the landscape of AI effectively. Take a leadership role – If we don’t take the lead, we risk missing the golden opportunity AI presents. Conduct an AI “stocktake” –According to a recent Microsoft survey, 75 percent of employees are already using AI. Identifying current AI usage within your organisation is essential. Assess the downside risks of AI – Legislative and regulatory requirements are exploding (e.g. NIS 2, the AI Act, DORA and more) and risks abound (AI bias, explainability, privacy, IP, GDPR, cyber security, resilience, misuse, model drift and more). Organisations must act on their AI responsibilities. Conduct a dataset stocktake – Just as the Y2K challenge was about identifying IT systems, today’s challenge is to catalogue all datasets, as these are crucial for AI functionality. Draft appropriate policies and procedures – Establish clear responsibilities and accountability for AI initiatives. Pay special attention to how AI impacts decision-making processes. Strengthen data curation – Implement new processes to improve how data is collected and used. Identify opportunities for the smart use of AI – Brainstorm and prioritise AI use-cases that can drive efficiency and innovation. Provide training – Ensure that board members, management and staff are all adequately trained on AI principles and applications. Manage the realisation of benefits – Safeguard against excessive costs and subpar returns by carefully managing the implementation of AI projects. Update audit and assurance approaches – Seek independent assurance on AI applications and leverage AI to enhance risk, control and audit processes. As we adopt AI, it is critical that we pay particular attention to distorted agency – i.e. giving too much agency to, or relying unduly on, AI outputs and doubting our own agency to make the most important decisions. Exercising professional judgement is the key to minimising the risks associated with AI and realising its benefits, and that surely is the strength of every Chartered Accountant. *Note: GPT4 was used to assist in drafting this article.   Níall Fitzgerald Head of Ethics and Governance Chartered Accountants Ireland Artificial intelligence (AI) is proving to be transformative, impacting competitiveness and how business is done.  Chartered Accountants Ireland has engaged with members working in various finance and C-suite positions, including chief executives, chief financial officers and board members, to understand how AI is impacting their day-to-day work.  One thing is clear. AI is being used in some shape or form in many businesses across the country.  In 2023, the Institute’s response to the UK’s Financial Reporting Council proposals on introducing governance requirements for the use of AI noted several governance mechanisms that are likely to be impacted by AI currently or in the very near future in many organisations.  We highlighted the focus on corporate purpose and how market forces, emerging threats and opportunities driven by AI, may challenge the purpose of an organisation and its long-term objectives.  AI may impact how organisations decide on their strategic focus in terms of how they deliver their product or service and, indeed, how their product or service is designed in the first instance.  It may also impact these organisations’ values as they consider how to deploy and use AI in an ethical manner. The EU AI Act, which enters into force on 1 August 2024 over a phased basis, introduces requirements for the development of codes of conducts, risk and impact assessments and staff training to ensure adequate human oversight around the use of AI systems within organisations. This has specific resonance for Chartered Accountants who are members of a profession bound by a code of ethics governing objectivity, confidentiality, integrity, professional behaviour and competence and due care. Chartered Accountants must now ensure that they understand how AI uses, analyses and then outputs data.  Organisations must ensure that any AI-driven information they share, and how they deploy the technology itself, satisfies principles of integrity, honesty and transparency.  Chartered Accountants are well-positioned, with their ethical mindsets, to ensure the integrity of AI systems, and their use within organisations.

AI is revolutionising accountancy by automating routine tasks, enhancing data analysis and providing valuable insights for strategic decision-making. Conor Flanagan explains how Artificial intelligence (AI) has emerged as a transformative force across various industries and accountancy is no exception. As AI technologies advance, they are reshaping the accounting landscape by enhancing efficiency, accuracy and strategic decision-making.  The emergence of AI can be traced back to the 1950s when pioneers like Alan Turing began exploring the concept of machine intelligence.  Turing’s famous “Turing Test” proposed that a machine could be considered intelligent if it could engage in conversation with a human without being distinguishable from a human interlocutor. Since the 1950s, AI has continued to evolve through different phases, including the notable period in the 1970s known as the “AI Winter” when there was a significant fall-off in funding and interest in the technology.  Since then, and coinciding with advances in computational power coupled with the development of machine learning algorithms, interest in AI has been reignited, with breakthroughs in natural language processing, computer vision and data analytics paving the way for more practical applications.  This progress, although impressive, has been somewhat dwarfed by the advent of Generative AI in recent years, with companies like OpenAI and its now infamous ChatGPT platform sparking widespread interest in the technology and its potential.  Generative AI has given rise to exciting new systems now capable of performing complex tasks, such as image recognition, language translation and content creation. And for the sceptics among us – no, this article was not written by ChatGPT. The Microsoft experience AI is revolutionising accountancy by automating routine tasks, enhancing data analysis and providing valuable insights for strategic decision-making. At the recent Chartered Accountant Technology Conference, held in January 2024, Daragh Hennelly, Senior Finance Director with Microsoft in Ireland, shared the story of how the company is unlocking business value through AI-enabled outcomes in finance. Microsoft began its AI journey over seven years ago, leveraging traditional AI to create models that could recognise patterns in data and use this to predict and act on potential outcomes, driving significant efficiency gains. Some examples include: Task automation and content creation Microsoft is using AI to automate tasks such as setting up purchase orders and logging expense reports. Streamlining processes and reducing risks Invoice approvals: AI assigns real-time risk scores to automate more than one million low-risk invoices and cuts the manual effort required for the rest by 50 percent, resulting in 125,000 hours of time saved for finance team members who can now use that time to focus on more strategic tasks. Journal entry anomaly detection: Machine learning algorithms have been built to review thousands of journal entries to detect anomalies with the aim of reducing reporting risks or misstatements.  Enhancing contract review efficiency: AI reads and scores thousands of contracts, reducing the time needed for manual review by 50 percent and allowing finance professionals to focus on high-risk contracts. The recurring theme in all these examples is how AI can be deployed to either automate manual tasks previously carried out by Microsoft’s finance team or unearth and present anomalies requiring additional review.  This demonstrates how AI can create efficiencies in finance functions and processes, but as accountants, we still need to be professionally trained to make decisions based on a smaller and more focused sample base.Over the past 18 months, in particular, the opportunity to transform business and finance processes has accelerated with the roll-out of Generative AI and its ability to create original content – such as text, images, video, audio or software code – in response to user prompts and requests. Today, Microsoft is adopting Generative AI to further enhance processes and unlock business value. This opportunity can be categorised across four main areas: Summarise information. Generate content. Recommend actions. Simplify tasks. 1. Summarise information Recap meeting transcripts to capture key points and assign actions. Distil collection agents’ call notes into actionable plans. Flag key terms in contracts related to payments, pricing and discounts. Synthesise complex workflow documents to highlight handoffs and commonalities. Summarise earnings scripts to identify significant trends and highlights. 2. Generate content Draft financial close decks and write analytical comments and insights. Write contractual language based on simple notes. Draft collection calls and follow-up emails in different languages with payment plan details. Write initial internal audit reports and investor relations earnings call scripts. Produce market sentiment analysis using transcripts from corporate earnings calls and central banking authorities. 3. Recommend actions Analyse financial close variances and recommend areas of the business to investigate variance drivers. Define collection strategy based on customer payment history. Evaluate audit workpapers and resolution disputes against audit controls.  Guide users in setting up purchase orders, invoices, expenses and payments. Recommend policy adherence within workflows. 4. Simplify tasks Accelerate financing requests by automating credit checks and policy reviews. Review sourcing contracts to ensure compliance and reduce human error.  Automate Sarbanes-Oxley Act (SOX) operational controls and summarise insights. Prioritise collection emails, tag disputes and identify resolution owners. Streamline tax and customs procedures by identifying compliance obligations from different global jurisdictions. Central to the success of this transformation of finance at Microsoft is a strong culture of encouraging and rewarding employees to leverage new technologies to transform finance processes. As Amy Hood, Microsoft’s Executive Vice President and Chief Financial Officer, puts it, “by adopting innovative technologies, finance will strengthen its business leadership through compliance, accuracy and efficiency.”   Microsoft is at the forefront of the Generative AI wave, advancing ideas of what is possible and investing in AI solutions such as CoPilot. CoPilot is integrated into Microsoft’s applications (Word, Excel, PowerPoint, Outlook and Teams), working alongside the user with the aim of helping them to work more creatively and efficiently.  It is also enhancing business application products such as Power Platform, Business Central and Dynamics Sales, facilitating advanced data analytics and the creation of complex workflows using natural language that would previously have required the intervention of a developer.  AI’s other early adopters Outside Microsoft, there are other examples of organisations that have successfully implemented AI in their accounting processes, demonstrating the technology’s practical benefits in our field.  HSBC The multinational banking and financial services company has implemented AI to enhance its fraud detection capabilities. HSBC’s AI system analyses transaction data in real-time, identifying suspicious activities and flagging potential fraud cases. This has resulted in a substantial reduction in fraudulent transactions and improved security for customers. Xero The cloud-based accounting software provider uses AI to automate bookkeeping and financial reporting tasks for small and medium-sized businesses. Xero’s AI-driven platform can categorise transactions, reconcile bank statements and generate financial reports, saving time and reducing the risk of errors for business owners. AI and ethical risk While AI offers numerous benefits to the accounting profession, it also raises some ethical concerns. These issues must be carefully considered to ensure the responsible use of AI in accountancy. Data privacy and security AI systems rely on vast amounts of data to function effectively. This raises concerns about data privacy and security, as sensitive financial information may be at risk of unauthorised access or misuse. Organisations must implement robust data protection measures to safeguard against data breaches and ensure compliance with privacy regulations. Bias and fairness AI algorithms are only as unbiased as the data they are trained on. If the training data contains biases, the AI system may produce biased or unfair outcomes. This is particularly concerning in areas such as fraud detection and financial forecasting, where biased algorithms could lead to discriminatory practices. It is essential to ensure that AI systems are trained on diverse and representative datasets to minimise bias and promote fairness. Transparency and accountability AI systems often operate as “black boxes,” making it difficult to understand how they arrive at their decisions. This lack of transparency can be problematic in the context of financial reporting and auditing, where accountability is crucial. Organisations must strive to develop explainable AI models that provide clear insights into their decision-making processes. AI and the work of the accountant The automation of routine accounting tasks through AI has raised concerns about job displacement and the future of the accounting profession.  While AI can handle repetitive and mundane tasks, it cannot replace the strategic thinking and judgment accountants bring to the table.  That said, accountants may need to adapt to new roles and develop new skills to remain relevant in an AI-driven landscape. Like electricity, the roll-out of AI will have a major impact on every industry and many professions, but only those who embrace it will learn to harness its power. Accountants must be prepared to adapt to the changing landscape by acquiring new skills and knowledge. Continuous learning and professional development will be essential for accountants to thrive in an AI-driven world. This includes gaining proficiency in data analytics, machine learning and other emerging technologies. Rather than viewing AI as a threat, accountants should embrace it as a valuable tool that can augment their capabilities. By leveraging AI to handle routine tasks, accountants can focus on higher-value activities, such as strategic planning, financial analysis and advisory services. AI is undeniably transforming the field of accountancy, offering numerous benefits in terms of efficiency, accuracy and strategic decision-making.  From automated data entry and fraud detection to financial forecasting and auditing, AI is revolutionising traditional accounting processes. Its widespread adoption also raises important ethical questions, however. To fully realise the potential of AI while addressing this challenge, organisations must prioritise ethical considerations while also investing in reskilling and upskilling their people and fostering collaboration between humans and AI.  By doing so, the accounting profession can harness the power of AI to drive innovation and deliver greater value to clients and stakeholders. If you have found this article interesting, join us for the next Chartered Accountants Ireland Technology Conference on Friday 24 January 2025. Conor Flanagan is ERP Lead with Storm Technology and a member of the Technology Committee of Chartered Accountants Ireland