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Home Business Insights Digital Transformation

Unique considerations on AI in accounting

FutureCFO Editors by FutureCFO Editors
September 25, 2024
Photo by cottonbro studio: https://www.pexels.com/photo/red-and-white-striped-textile-4669625/

Photo by cottonbro studio: https://www.pexels.com/photo/red-and-white-striped-textile-4669625/

As finance professionals continue to navigate around technological advancements, the considerations on how digitalisation can affect the function and the organisation as a whole seem almost endless.

In a recent report by the Association of Chartered Certified Accountants, they identified 'unique' considerations towards artificial intelligence, conceding that AI in accounting encompasses various technologies.

Such technological advancements include machine learning (ML), computer vision (CV), natural language processing (NLP), and generative AI (GenAI), wherein each present distinct capabilities and risks in use.

ACCA says both the type of AI technology and its application need to be approached with due consideration. For example, applications where predictive capabilities are intended to make decisions that could impact individuals are particularly sensitive – and may have inherent flaws and acknowledging policies around scope of use, control of data inputs, and standards and accountability around use of outputs.

The role of finance in championing a collaborative approach to strategy

ACCA's The Smart Alliance: Accounting expertise meets machine intelligence report highlights the critical role of finance in shaping AI and data strategies across organisations.

The study found that finance teams are increasingly taking on advisory roles (56%) or even ownership (20%) of these strategies, putting them in a position to champion a more collaborative approach to AI adoption.

While powerful, GenAI also has distinct limitations. The capabilities of these models are still developing, necessitating constant monitoring and oversight to understand the impact on outputs and types of error that can be produced.

In general, ACCA says outputs cannot be fully relied upon for accuracy – and that is a crucial consideration when determining the correct use case. There may well be valuable uses for GenAI within strict and limited circumstances – but not without serious consideration of the potential for inaccuracies, biases, or misleading references that proliferate harm or reputational damage.

Organisations also need to think about implications for information security around use of public models. Organisations should understand these limitations and implement appropriate safeguards – such as human oversight and validation processes – particularly for tasks requiring high accuracy.

As data becomes central to organisational success, ACCA says finance departments are well placed to foster cross-functional collaboration, bridge the gap between organisational strategy and day-to-day operations, and ensure AI initiatives align with business objectives.

The report further suggests that the finance team can lead in creating flexible, collaborative models for data management and AI implementation – moving towards co-ownership roles with other departments.

This collaborative approach is key to identifying AI innovation opportunities and ensuring broad organisational support for AI initiatives.

Related:  Webinar: Align finance & operational plans accurately & effectively
Tags: ACCAAImachine learning
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