There is no doubt that AI adoption is here and perhaps more widespread than you thought.
Search from Equals money of UK financial decision makers have found that More than three quarters (77%) It is already actively adopting or experimenting with AI in its operations.
So, what role can AI play in your company's finances? The primary value of AI is its ability to save time by improving rudimentary tasks. Much of what the finance function does, like reconciliation for example, is repeatable and ready for automation. Equals Money research found that UK employees spend an average of 65 minutes a day on automatable tasks, including daily financial management, up to 38 days a year.
AI seems to be the obvious solution to some of the productivity challenges that UK businesses are currently facing. However, there are a series of questions that business leaders must ask themselves before and during AI adoption to not only achieve the desired performance, but to do so in a safe and informed manner.
Fears and how to experiment
Many companies are concerned about being a first mover because if AI adoption goes wrong, it could pose a significant reputational risk. For those considering adoption, they should have a good foundation to start with. AI can help improve good businesses, but using AI to fix fundamental problems in a struggling business is where things can get dangerous.
You need to know your business inside and out, understand which processes are most likely to benefit from automation, and have the relevant skills to measure the impact of these changes. This is how you make AI work for you, not by expecting it to do all the heavy work from scratch, but by directing it to reinforce the good work you're already doing.
In the loop, in the loop or outside the loop
When looking at a process that you think could benefit from an AI tool, you should ask whether you want to be in the loop, in the loop, or out of the loop. For initial adoptions, it's unlikely that you want to be out of the loop and let the AI do its own thing. Staying informed means that the AI is allowed to operate freely but with regular reviews of the decisions it makes. Staying in the loop means that while doing most of the work, the AI will not be able to make any active decisions, as all suggested decisions are reviewed by a human.
A finance team can use an AI tool to do a complex task like policy formulation and get a fairly reliable response that is around 80% accurate. A human interpretation of that remaining 20% is vital to ensure the answer is not misunderstood. While the ROI from AI may come from removing lower-level tasks, you still need experts who can scrutinize its responses to ensure authenticity, especially for complex financial processes. AI will likely prove to be a great asset, but I expect it will play this complementary role for a long time.
What about job security?
The concept of artificial intelligence is a scary thought for many people who believe that it will replace jobs, making their livelihoods obsolete. Our survey found that job security was cited by a third of respondents (33%) as a barrier to adoption. 85% of companies that have already adopted AI tools found that they had an impact on workload, with nearly half (46%) claiming that they freed up employee capabilities by reducing or eliminating certain tasks. However, 39% felt that some job roles are at risk of being made redundant due to automation.
Transparency is key in managing this change. As with any large-scale change project, you need to bring people along on the journey by reframing it as an opportunity for growth. Financial sector leaders must help deliver this transformation. Doing so will help turn what seems like a threat into an opportunity for personal and professional growth. Likewise, with appropriate training or retraining, leadership teams can ensure that as many people as possible maintain a useful role in the evolving landscape.
Embracing AI automation is critical for financial leaders to gain a competitive advantage. We must be receptive to change and treat AI adoption like any other transformational project. The real risk is that adoption of these products will be slow, allowing competitors to overtake us.
This does not mean that we should let AI run unchecked – it is our job as decision makers to ensure that the right level of oversight is applied to AI operations and managed effectively. Not all processes should be automated, and it is important to understand which tasks can be assigned to AI, and which should be left to experts.
