New paths to productivity through AI

A recent Deloitte survey put the UK’s poor productivity at the top of CFOs’ worry list, preceded only by geopolitical risks. This could be seen as an opportunity. After all, if you can work smarter in your organisation while others lag behind or need to work harder to grow their businesses, you should be able to gain a competitive advantage.

New tools with which to do this are available, and if we exploit them judiciously we could be on the cusp of a productivity revolution which would be good news for everyone. At AICPA & CIMA we looked at this topic in a recent research project, where we interviewed finance leaders from around the world to see what they are doing and identify best practices.

Throughout history, the key driver of productivity gains has been applying new technology. The hot topic of today is the potential for Artificial Intelligence (AI) to be the technology which drives the next significant productivity leap. We are at an interesting transition stage with this technology. Finance professionals everywhere are starting to use it in their everyday work, but we are still ‘feeling our way’ a bit.

While it is exciting, the experimentation stage of a new development can be difficult (and expensive) to navigate. That said, we can begin to discern some general principles to guide us. Here are a few ideas to focus on when you are incorporating AI into your processes to help you get the maximum benefit from it.

• Translate activities into tasks and rank them based on their potential for AI performance. This gives you a systematic starting point for planning and designing the use of the technology in your organisation.
• For tasks that could be performed by AI, consider whether it is advisable to replace manual effort. The technology cannot make judgement calls and should really be thought of as a tool for enhancing and augmenting a manual effort rather than replacing it. AI is good at repetitive and routine tasks, freeing up people to work on the higher end jobs which add more value.
• It follows that you need to be thinking about upskilling and motivating employees to collaborate and actively participate in AI-driven productivity initiatives. Employees have a critical role in guiding, managing, and training the system and mitigating its risks, and as with any change, you will need to take people with you if it is going to be a success.
• AI does not ‘think’, it learns from existing data. That means you need to have confidence in the data that it is learning from. Traceability is key, so keep an audit trail. Trustworthy sources of data enable the trust required to make AI a useful technology for informing decision-making.
• Think about how to measure progress. As with any change, a dip in productivity is to be expected during implementation, so you need a wide range of indicators and a timescale over which you expect to see improvements.
• AI is a new field, and ethics are paramount. You need to have a proactive strategy in place to sustain the ethical stance of your organisation when using this type of technology. Data security and protection and EDI (Equality, Diversity, and Inclusion) and lawfulness are key areas of concern.
• Set realistic expectations. AI will not magically raise your organisation’s productivity rate. It is a new tool which may do so if deployed and monitored effectively. Approach it as finance professionals do – with scepticism, while regularly monitoring and evaluating how it is performing and adjust your strategy if need be. In other words, apply good management practice as you would with any other capital investment.

With adopting AI, we are probably beyond the stage where the question is “should we do this” and on to the “how do we do this” question, for the simple reason that even if you don’t, the chances are that your competitors will. Hopefully I have made some suggestions which will help you think about how to explore the potential of the technology in a way which enhances

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