The use of AI across finance functions is soaring as it quickly becomes a key tool for getting the job done.
As such, businesses are investing heavily and spending continues to rise, meaning adoption has more than doubled since 2024.
But governance isn’t keeping pace, as almost half (49%) of UK finance leaders admit their organization has gaps in its AI governance strategy.
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Head of Business Solutions, Soldo.
That’s a concern for two reasons. One, because governance is a compliance exercise, and two, because it underpins how confidently businesses can adopt AI at scale.
Without clear guardrails, employees will naturally start making their own decisions about which tools to use and how to use them – creating ripe conditions for Shadow AI to emerge and thrive.
The widening adoption-governance gap
I speak from experience when I say that AI is and will continue to be transformative for the finance function.
And for an industry that is largely accepting of the tried and tested status quo, it’s genuinely encouraging to see how positively leaders in the finance space view AI. Our research showed that 8 in 10 (83%) believe it will play an important role in helping them achieve their business goals.
What’s less encouraging, and somewhat worrying, is that almost a quarter (23%) say they have little to no AI governance measures in place. And that disconnect really matters.
Too often, governance is viewed as something to tackle only once adoption of new technology is well underway. But it has to be built alongside adoption. There’s often a fear, not always unfounded, that governance can slow innovation. But that’s not always a bad thing, because the point of governance is to make sure innovation happens safely and in a way that business can measure and trust.
Without it, AI adoption can quickly become fragmented, increasing a business’ exposure to compliance and security risks that will only intensify as AI becomes more deeply embedded.
When processes create friction, people will find another way
While governance gaps are directly linked to organizational risk, they also shape employee behavior. If approved tools are difficult to access, limited, or policies aren’t clear, people will look for another way to get the job done. Employees as a whole want to embrace the productivity benefits of AI and won’t let a lack of formal guidance stop them.
And that’s exactly what research tells us.
More than a quarter (27%) of UK employees admit to purchasing AI tools for work without approval in the last year. More broadly, 67% say they regularly bend rules or find loopholes to access company money, while 27% report missing business opportunities because of delays accessing spending.
These findings aren’t suggestive of employees deliberately trying to undermine company policy. More often, it’s a sign that existing processes aren’t keeping pace with the way people want to work.
That’s where shadow IT starts to emerge.
Shadow AI is a symptom of a wider governance problem
It’s easy to think of Shadow AI as the problem itself. But in reality, it’s usually a symptom of something bigger.
The concern is that this unchecked use of AI can lead to data leakage, compliance failures, poor record-keeping and inconsistent decision-making. So, it’s an important problem to nip it in the bud before it spirals out of control.
When employees feel they need to work around approved processes to stay productive, businesses quickly lose visibility over which AI tools are being used and how company data is being handled. Finance teams can quickly lose track of where money is being spent.
That creates a practical challenge for finance leaders, while businesses can find themselves managing duplicate tools, fragmented AI adoption, unmanaged spend and inconsistent governance. Exposure to scrutiny and compliance risks can also increase exponentially.
The longer those issues go unaddressed, the harder they become to unwind.
Good governance enables AI
The goal is never to slow AI adoption or place unnecessary barriers in front of employees. When governance is implemented well, it makes the approved route the easiest and best way to support employees in new, more productive ways of working.
It means making sure employees have access to tools that help them work effectively, putting clear policies in place for how to use them, and making it clear what’s expected.
When governance supports productivity and innovation, helping employees to address areas of friction in their roles instead of adding to it, they’re far less likely to look elsewhere for solutions.
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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
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