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:

1. Summarise information.
2. Generate content.
3. Recommend actions.
4. 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