As accountants, we must embrace artificial intelligence (AI) into our profession.
AI isn’t just the latest innovation. It is a disrupting technology that changes how we do things. It is not necessarily going to reduce us — indeed, we should grow as a result.
We can now automate the mundane and spend more time analysing the meaning of it all. This has vast implications for accounting, auditing, assurance, forecasting, and tax. We must leverage AI and view it as a collaborative colleague — not the enemy.
Let me try to convince you. Remember, the following points are all made assuming you consider the integrity of the underlying data and that it is the most appropriate data (challenge AI by demanding it provides references and check them).
The following is not an exhaustive list, but it sets out examples of how AI can help you and your colleagues in the various aspects of our profession:
Accounting
- Automated data entry: We have had Power Query/Get & Transform for years, but the new AI-powered tools can further handle data entry and transactional processing without necessarily spelling out all the repetitive tasks. Forget M code, DAX, and Python.
For example, AI can categorise transactions, reconcile bank statements, and flag anomalies. This lets you focus on the added-value work, such as quality reporting, financial analysis, and justifying business recommendations. - Real-time reporting: AI can generate real-time financial reports, providing immediate insights. You can interpret the data, reflect, and make strategic recommendations in more accurate and timely ways.
- Continuing professional development: By learning how to use these tools effectively, you can become the key accountant who can train others, implement new systems, and function as a conduit between AI, other automative technology, and business needs. Your business will need you.
Auditing
- Better data analysis and auditing techniques: This is where AI has truly set out its intentions. Traditionally, audits have relied heavily on sampling, since there is simply too much data to review it all. That world has moved on: AI now allows for the analysis of entire datasets (something previously seen as unimaginable) and detecting anomalies, patterns, or fraud with far greater accuracy. Specialising in tools like Aleph, MindBridge, VenaAI, and similar will be very helpful here.
- Continuous external and internal auditing: AI can monitor on an ongoing basis rather than periodically. This means you can provide value-added assurance to management and other key stakeholders that controls are working effectively in near real time. Relying on improved audited data, critical business decisions can be made with far less risk than previously.
Assurance
- Enhanced risk assessment: AI can process huge volumes of data to assess external and internal risk factors for the entire business. For example, AI can analyse supplier transactions to identify related parties, potential conflicts of interest, or compliance risks, which can then be successfully solved by you as you interpret the results.
- Scenario modelling: AI-driven assurance and modelling tools can simulate different business situations and scenarios, providing more robust assurance regarding business continuity and resilience. This will help you make more-informed decisions and optimise scarce resources.
- Interpretation: By understanding these new AI assurance methodologies and being able to interpret their results, you will be able to differentiate yourself by highlighting to your colleagues and/or clients how to take advantage of salient risk-mitigation strategies.
Financial planning and analysis (FP&A)
- Predictive analytics: AI can forecast any manner of KPIs, cash flows, revenues, and expenses by analysing historical data and external variables. For example, AI models can predict seasonal sales trends or the effects of economic, environmental, or political changes on client portfolios.
- Scenario planning: Using simple AI models, you can model best-case, worst-case, and most-likely financial outcomes, helping clients interpret their data and assisting in making informed decisions.
- Sensitivity analysis: Another approach is to allow AI to identify the most likely factors of change for a particular output. A skilled accountant can review the data changes and their impact on key outputs to determine how the business should be managed and which areas may be better outsourced, for example.
Tax
- Automated compliance: AI tools can prepare, estimate, and review tax returns; identify deductions; and flag compliance risks. This minimises errors and lets the busy tax professional focus on complex tax strategies and salient client advice.
- Real-time regulatory updates: AI systems can keep you up to date with the latest tax law changes, ensuring your advice is current, relevant, and accurate.
The successful 21st-century accountant will recognise the need to develop their data literacy and digitisation and analytical skills. No more thankless tasks: AI has just made your job more interesting and will provide you with countless opportunities to add value.
Whilst resilience rather than resistance is paramount, the focus for the proactive, engaged, AI-savvy accountant will be to learn the essential soft skills. Those who will succeed will need to be able to communicate — both through effective prompt engineering with their AI tools of choice and to strike accord with their colleagues and clients.
But that’s not all.
The successful accountant will need to understand the challenges that AI presents as well. Developing a specialism and a healthy scepticism in one or more of the following areas will make you an essential part of the AI process:
- Cybersecurity will become paramount. Every day, we hear of more and more cyberattacks, data breaches, and privacy violations. Criminals have many opportunities for automated fraud, such as sending phishing emails or fraudulent invoices. A specialist accountant can work with IT professionals to implement adequate security controls, suitable encryption, and sufficient internal controls, checks, and balances. Internal audit has never been more important.
- Privacy is still a top priority for businesses. A top accountant needs to ensure compliance with regional (and possibly international) privacy laws, ensuring that finance teams only collect the data necessary for the task and clearly comply with related retention and destruction policies. A proactive accountant can enhance both their personal and company’s reputation — and that is much more than just a survival technique.
- Ethics — Ultimately, accountants remain responsible for many ethical considerations including the integrity of financial information, regardless of automation. The AI-ready specialist must ensure appropriate oversight of AI tools and take responsibility for the outcomes. They must actively identify fairness in reporting and mitigate/prevent biases, as well as remain critically independent, always challenging AI-based conclusions. Professional scepticism is a necessary skill: You should always challenge AI’s data (both for appropriateness and integrity), sources, and conclusions.
The modern professional needs to thrive to survive.
If you want to ensure an exciting future, adopt a growth mindset. A commitment to lifelong learning, championing change, and adding value will stand you in good stead.
And be confident enough to recognise that AI augments your abilities — it doesn’t threaten them.
— Liam Bastick, FCMA, CGMA, FCA, is director of SumProduct, a global consultancy specialising in Excel training. He is also an Excel MVP (as appointed by Microsoft) and author of Introduction to Financial Modelling and Continuing Financial Modelling. To comment on this article or to suggest an idea for another article, contact Oliver Rowe at Oliver.Rowe@aicpa-cima.com.
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