Artificial intelligence

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.