Artificial intelligence has become one of the most prominent productivity tools of modern work, with employees using AI to write code, analyse information, automate routine tasks and even make decisions.
That appetite for AI is reflected in Soldo’s latest Productivity at Work report, with almost nine in ten (88%) of employees saying AI tools have improved their productivity, while 83% of finance leaders think AI investment is important for achieving business goals.
However, despite this headline success, two-thirds (63%) of employees feel they’re expected to use AI without proper support, and 27% have purchased tools without approval.
“This friction imposes a kind of ‘cognitive tax’ on the workforce. Finance teams have a critical role in closing this gap, as many employees perceive finance as either an enabler or a catalyst for growth.” – Dr Naeema Pasha, Founder of The World of Work Institute, Henley Business School.
PwC’s 29th Global CEO Survey found that 56% of CEOs say AI has delivered neither revenue nor cost benefits, despite continued investment. It also raises the question of whether AI investments can be governed, measured, and defended at board level.
AI may help employees work faster, but if businesses cannot measure returns, govern spending, or connect AI use to business outcomes, productivity gains remain difficult to translate into business value.
The finance bottleneck
While AI is changing how people work, basic barriers to productivity remain.
Only a third of employees (31%) say company spending processes are straightforward, 29% say finance processes have delayed or slowed work, and 28% say approvals are too complex and time-consuming.
When processes are slow and cumbersome, quick fixes become more attractive and workarounds more likely. Six in ten employees (60%) say they frequently bend rules or find loopholes to access money. This is a warning sign that slow processes frustrate employees and weaken control.
“Productivity gains should be achieved by actively supporting workers on their AI journey, helping them build skills, removing friction, and enabling them to contribute at a higher value.” – Dr Naeema Pasha, Founder of The World of Work Institute, Henley Business School.
Shadow AI spend
Unlike traditional technology purchases, AI adoption happens incrementally through subscriptions, usage-based pricing models and departmental spending. The costs can become fragmented across teams, leading to duplicate tools, unmanaged renewals and unclear ownership.
In fact, only a quarter of finance leaders (27%) say clear policies and controls fully govern AI use and purchasing. Without visibility into what tools employees are using, businesses struggle to answer basic questions.
What AI tools are being used? Who owns them? What data is being shared? What are they costing? What business value are they creating?
The answer is to build governance into spending before money leaves the business, giving finance teams real-time visibility and control when decisions are made.
Why finance is central to AI governance
The finance function has quickly become central to business productivity, providing the strategy and infrastructure to help employees act quickly and responsibly while maintaining the right controls.
Soldo’s research found that nearly three-quarters (73%) of finance leaders say finance is responsible for overseeing AI investment and performance. Meanwhile, employees are equally positive about finance, with 41% describing the function as an enabler.
This reflects a broader strategic shift in the CFO role. Finance has the trust. It now needs systems and processes that keep pace with faster decision-making and decentralised spending as businesses harness new technology.
The next phase of productivity
AI is helping employees work faster, but faster work does not automatically lead to greater productivity. True productivity emerges when technology, processes and governance work together.
To achieve this, finance leaders should focus on enabling employees to access tools, maintaining robust controls, supporting ongoing training, and implementing real-time visibility into spending to prevent costs from becoming unmanageable.
Productivity is a governance challenge, and the businesses that can combine speed, visibility and accountability will be best positioned to turn AI investment into long-term value.
