AI offers vast potential to boost productivity and efficiency across various functions such as finance, procurement and supply chain, marketing, human resources, product development and design, risk management, manufacturing and operations, and customer engagement and sales.

To set the profession up for continued success, it is essential to understand the implications and opportunities AI presents.

With the growth in availability of data, and technological tools to transform data into useful information as well as meaningful insights for decision making, accountants can focus their attention on interpreting complex data, identifying the support that business operations need and tailoring internal and potentially external reporting for these purposes. Accountants who use these tools well will be more capable of supporting the business in making effective decisions across their organisations.

AI tools can process and analyze large data sets in real-time. This allows accountants to offer more sophisticated, value-added services. Predictive analytics, for instance, enables users to forecast future trends, identify potential risks, and provide strategic advice on financial planning and risk management. The profession is well placed to exploit these tools and embrace the benefits of this technology.

Internal and external reporting have historically had a focus on the past. While undoubtedly statutory obligations mean past results will always be important, there is necessity to act on current information and to utilize predictive tools to help gauge future possibilities through scenario analysis.

AI tools also offer great capability for tailoring advice, reporting and dashboards to the needs of organisations and clients. This can be a game-changer for small and medium-sized enterprises (SMEs) and small and medium-sized practices (SMPs).

Historically, such capability required either expensive in-house tool development or substantial admin time. In some ways, generative AI (in its freely available iterations at least) could therefore help level the playing field, as the ability to provide more nuanced, data-driven insights is increasingly becoming available to all, sometimes at little cost. At the same time, larger organisations will seek to exploit this technology through their ability to invest heavily in developing enterprise specific tools and through partnering with large organisations active in this space.

“Traditional” AI automates repetitive tasks and performs specific tasks intelligently based on a specific dataset – “pattern recognition”

• Classification – categorise input data into categories based on predetermined variables
• Prediction – Predict future events or outcomes based on historical data
• Optimization, trends/driver analysis, anomaly detection

Generative AI

• Generative AI assists in language-based tasks and creating content (text, images, music, computer code etc.) – “pattern creation”
• Summarisation/synthesis – generates summary of large volumes of text or other media
• Generation of content and translation
• Communication between a user and computer system
• Knowledge management – highlights information and insights embedded into all data types (docs, emails etc.)

• Automation of routine finance tasks – data entry, invoice processing, reconciliations
• Data analysis and forecasting
• Data modelling and scenario planning
• Market trend analysis
• Supply chain finance, optimizing working capital including through payment timing
• (Read more on how the digitalisation of procurement and supply chain operating models are changing the role of finance functions, see pages 10 – 12 of the IFAC report: Enabling purpose driven organizations)

• Tax planning through analysis of data against tax laws to identify potential savings and issues
• Evaluation of potential mergers, acquisition and other transactions through data analytics and broader assessments of strategic fit

For more examples and use cases of AI, click below

Accountants also play key roles as stewards of data and experts in processes and internal control, helping to ensure the reliability and accuracy of information.

Many professional accountants are already seeking training in data analysis and this pattern will likely grow in the future. Requirements in relation to computer literacy may experience similar growth and increasing specificity as AI literacy, prompt development and general technological adaptability become increasingly valuable.

Rapid advances in technology require a real commitment to continuous learning and adaptation from professionals, accounting firms and professional accountancy organisations. In many smaller organisations, individual accountants may be charged with ensuring the benefits of AI are being harnessed in their organisation, and this may be similar for practitioners in SMPs providing services for SMEs. This creates a responsibility to continually monitor and implement latest AI developments and best practice and interpret their implications for organisational processes. (Read more on The Uses of Artificial Intelligence for SMPs | IFAC).

The start of this journey to ongoing education is as much about developing a mindset open to innovation and change as it is about acquiring technological knowledge. Professional development programs will need enhanced focus on topics such as data interpretation, ethical AI usage and application of AI in strategic decision making. This is the only way AI can be leveraged effectively and responsibly.

There will be a high demand for capable talent. Technology companies, with their vast resources, may become greater competition when technological capacity becomes as important as financial expertise in the profession. The role of professional accountancy organisations will become increasingly important in this environment, as the development of requisite skills in-house will be imperative. Training programs and the education standards that underpin them will need to accommodate these future changes. Specialised AI and data analytics modules on accounting syllabuses or standalone courses will be a must. Considering the increased specialisation, it would not be unexpected to see closer collaboration or partnership with technology experts too.

• The initial costs of adoption, though freely available resources negate what the impact of entry cost might otherwise be. However, their use can be challenging as confidential data cannot be fed into free systems.
• Ongoing costs on implementation, including the costs of training staff and developing interfaces to use data effectively with these systems.
• Potential resistance to change in businesses and practices.
• Ethical considerations such as security and the risk of bias within learning models. Accountants will need to keep ethical principles in mind, using relevant guidance from the IESBA Code and its principles.

• Start small and scale up.
• Identify the “quick wins” – simple AI tools that can be incorporated into existing systems (e.g., tools such as Microsoft co-pilot) vs the more disruptive transformations.
• Obtain an in-depth understanding of the business and key end to end processes that could be streamlined using AI.
• Understand the business case – just because something can be automated, doesn’t mean it should be! Need to consider aspects such as speed, cost savings, and competitive differentiation.
• Prioritize key initiatives that will have the potential to create the most value.
• Develop use policies and procedures – protect company data.
• Accelerate internal capabilities to build talent and expertise needed.

As AI becomes more ingrained in the profession, new roles and specialisations may emerge. For instance, ‘AI in Accounting’ specialists or advisors can help bridge the gap between technical AI capabilities and strategic business applications. The relationship between AI and the accountant could shift from task automation support more towards strategic partnership. A system where AI provides real-time insights and accountants use their judgment and expertise to make informed decisions. This leaves great potential for both enhancing the efficiency and accuracy of accounting practices and opening opportunities for new innovative financial strategies and solutions.

The accountants of the future will be empowered to contribute significantly to business strategy and decision-making if AI technology is harnessed appropriately by the profession. A proactive approach to skills development and a readiness to embrace new technologies is needed now to foster the changes that will benefit future accountants. This provides exceptional opportunities for professional growth, improving retention and the profession’s attractiveness.