How automation can help you manage your business finances

There’s no doubt that AI adoption is here and may be more widespread than you might think.

Research of Equals money of UK financial decision makers note this more than three quarters (77%) are already actively adopting or experimenting with AI in their processes.

What role can AI play in your business finances? A core value of AI lies in its ability to free up time by optimizing rudimentary tasks. Much of what the finance function does, like reconciliation for example, is repeatable and ripe for automation. Equals Money’s research shows that UK workers spend an average of 65 minutes a day on automatable tasks, including daily financial administration, which equates to a whopping 38 days a year.

AI seems to be the obvious solution to some of the productivity challenges that UK businesses currently face. However, there are a number of questions business leaders must ask themselves before and during AI adoption to not only achieve the desired performance, but do so in a safe and conscientious manner.

Concerns and how to experiment

Many companies are afraid to be the first to move, because if AI adoption goes wrong, it could pose a major reputational risk. Those considering adoption need to have a good foundation to start with. AI can help make a good company better, but using AI to solve core problems in a struggling company is where things can get dangerous.

You need to know your business inside and out, understand the processes 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 lifting from the start, but by guiding it to improve the good work you’re already doing.

In the loop, on the loop or out of the loop

When looking at a process that you think could benefit from an AI tool, ask yourself whether you want to be in the loop, on the loop, or out of the loop. For initial adoptions, it’s unlikely you’ll want to not be involved and let the AI ​​do its own thing. Being informed means that the AI ​​is allowed to operate freely, but the decisions it makes are regularly reviewed. Being aware means that while the AI ​​is doing most of the work, it cannot make active decisions, with all proposed decisions being reviewed by a human.

A finance team could use an AI tool for complex work, such as setting policy, and get a reasonably credible answer that is about 80% accurate. The human interpretation of that remaining 20% ​​is critical to ensure that the answer is not misinterpreted. While AI’s ROI may come from removing lower-level tasks, you still need experts who can scrutinize its responses to ensure credibility, especially in complex financial operations. AI will likely prove to be a fantastic asset, but I expect it to play that more complementary role for a significant period of time.

What about job security?

The concept of AI is a frightening thought for many people who think it will replace jobs, making their livelihoods redundant. Our research found that job security was cited as a barrier to adoption by a third (33%) of respondents. 85 percent of companies that have already implemented AI tools find that it has impacted workloads, while almost half (46 percent) claim it has freed up employee resources by reducing or eliminating certain tasks. However, 39 percent believed that some functions were at risk of becoming obsolete due to automation.

Transparency is critical in managing this change. As with any large-scale change project, you need to bring people along on your journey by reframing it as an opportunity to evolve. Finance leaders must help communicate this shift. By doing this, you can turn what seems like a threat into an opportunity for personal and professional growth. Likewise, with the right training or reskilling, leadership teams can ensure that as many people as possible retain meaningful roles in the evolving landscape.

Embracing AI automation is critical for finance leaders to gain a competitive advantage. We must be receptive to change and treat AI adoption like any other transformative project. The real risk lies in the fact that adoption is slow, allowing competitors to overtake us.

That doesn’t mean we should let AI work unchecked; it is our job as decision makers to ensure that the right level of oversight is applied to AI processes and that they are managed effectively. Not all processes need to be automated and it is crucial to understand which tasks can be entrusted to AI and which should be left to the experts.