Midmarket finance leaders in the UK perceive their departments as leaders in adopting artificial intelligence, yet a recent survey reveals a substantial disparity between the views of senior executives and operational staff. The study, which surveyed 250 finance professionals from midmarket firms, highlights significant differences in how AI adoption is perceived and measured within organizations.
The findings indicate that 83% of finance functions claim some level of AI adoption, with over half of Chief Financial Officers (CFOs) believing their teams have fully embraced the technology. However, fewer than one in five Financial Controllers (FCs) concur, reflecting a 32-point gap that underscores a disconnect between the strategic perspective of leadership and the operational realities faced by staff.
This confidence among senior leaders also influences their assessment of AI integration across departments. A large proportion of CFOs and Finance Directors believe the finance function is ahead of others—including HR, sales, marketing, engineering, and IT—in terms of AI adoption. In stark contrast, FCs express more cautious views regarding these comparisons.
While outward appearances suggest that AI is firmly embedded in finance departments, the internal landscape reveals a different story. Only 35% of finance leaders affirm full AI adoption, with nearly half reporting only partial integration. “CFOs are measuring AI adoption by whether tools are available and being used. FCs are measuring it by whether their day-to-day operational work has fundamentally changed,” remarked Rob Steele, CFO of iplicit. He emphasized that the 32-percentage-point difference signals that deployment and meaningful adoption are two distinct concepts.
Many finance teams still rely heavily on traditional processes, often spending considerable time preparing and validating data before utilizing AI tools for analysis or reporting. “CFOs see AI generating board commentary and dashboards, so the strategic view looks highly automated. But from an operational perspective, many FCs are still spending days producing the underlying numbers before AI can even begin its analysis,” explained Andy Jackson, Financial Controller at iplicit.
Mark Pullen, CEO of SoMax Finance, noted that this misalignment between leadership and operational staff is prevalent across the industry. “Senior leadership teams are convinced they’ve ‘done AI’ because dashboards and commentary look more automated. But when you get into the engine room with Financial Controllers and operational finance staff, the reality is very different,” he stated. Pullen added that many staff continue to export spreadsheets and manually rectify data before AI can be effectively deployed for analysis. “If the underlying processes aren’t automated, then AI isn’t genuinely live in your finance function – it’s just presenting the numbers faster.”
The research also points to foundational issues, such as fragmented systems and manual processes, that remain widespread within finance departments. “In truth, many finance teams haven’t adopted AI in any meaningful sense yet. What we often see is experimentation rather than transformation,” said Chris Harman, Director at Candura. He noted that most small and medium-sized enterprises are still grappling with basic challenges, such as inconsistent data and outdated manual processes. Until these issues are resolved, AI is likely to remain an ancillary tool rather than a transformative force in finance operations.
Despite high levels of reported confidence in AI among leadership, formal training in the technology is scarce. Only 32% of survey respondents indicated they had received structured guidance from their employer, with most relying on self-directed learning or informal experimentation to grasp and implement AI solutions. Steele highlighted that there’s understandable pressure on senior finance leaders to spearhead AI adoption, but the lack of formal training and partial implementations could lead teams to rush into transformation without adequate foundational measures.
This disparity between strategic ambition and operational readiness presents an opportunity for specialist advisers and technology partners to refocus priorities. “Channel partners have a critical role to play in slowing organizations down just enough to get the foundations right,” Pullen stated, emphasizing that discussions about data structure, governance, and workflow automation are becoming more prevalent than conversations surrounding AI tools themselves.
Harman added that harnessing modern technology to support tech-savvy finance teams can provide a significant competitive advantage. “AI presents an amazing opportunity for organizations willing to establish the necessary building blocks. Companies that exploit AI—even at a rudimentary level—can gain a considerable edge over their peers,” he noted. As the finance sector continues to navigate the complexities of AI adoption, Steele urged leaders to approach the technology with enthusiasm rather than panic, advocating for responsible adoption coupled with a clear understanding of its capabilities and limitations.
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