Overcoming the Human Problem > How Small Cultural Changes Can Help Finance Embrace AI

For most finance teams, artificial intelligence is brand new. Even though some companies have been using machine learning forecasts for a decade or longer, 80% of those working in finance have less than two years’ experience with AI, if any at all. While there are great ambitions and opportunities for AI and data science to change the way we work, many teams struggle to unlock AI capabilities because some finance professionals are stuck in old mindsets and ways of working.

AI cannot succeed without a culture that accepts it. While formal change management initiatives are easier to sell to leadership, grandiose initiatives are often rejected by staff. Sustainable culture change is more gradual, so to win with AI, cultural barriers need to be reckoned with in smaller increments.

Understand the culture that will succeed with AI

The common challenges of AI adoption usually fall under four key cultural concerns: failure, familiarity, fatigue and fear. For most finance teams, there is little or no room for failure or experimentation in our performance expectations. With at least 30% of AI pilot programs projected to fail by the end of 2025, organisations need a finance culture that possesses energy and passion for experimentation in the right places.

Lack of familiarity or comfortability with AI further feeds the concern of failure. But there also needs to be a willingness to support organisational change. When examining HR practices and change management success, Gartner found that willingness to support organisational change has decreased from 74% of employees in 2016, to just 43% in 2022. One reason for this is change fatigue, which can potentially reduce teammates’ contribution and effort, eroding their responsiveness, trust in leadership and intent to stay with the organisation.

But the final cultural barrier to AI success is fear. Gartner found that 44% of finance professionals expressed concern about being replaced by AI and fearful individuals are rarely open to change and new ideas. Moreover, cultures that perceive they are under threat or changing too rapidly are not only highly resistant to change, but often double their efforts to enforce social norms within the group to ensure survival, rather than experimenting or innovating.

This combination of fear, fatigue, lack of familiarity and failure creates a static finance culture where merely plugging AI into current processes will never gain the returns needed to stay competitive. But small shifts to identify and gradual work to modify habits can unlock cultural change.

Create a culture that embraces AI

How do we generate these shifts in culture? Small pokes and prods to encourage new habits, also known as “culture hacks,” create a gradual change that reinforces acceptance without creating a resistance response. Office cultures are primarily comprised of habits, and habits comprise three components –trigger, routine, and reward – which create a formula for understanding culture.

• Trigger – an event that prompts action or reaction.
• Routine – a learned series of actions or emotions in response to triggers.
• Reward – an outcome that reinforces routine.

To get started on culture hacking, create a roadmap to identify the target culture state they aspire to create, and the behaviours that are counterproductive to the target state culture. From there, identify the friction points or barriers that negatively affect the trigger, routine or reward and create hacks that disrupt them.

For example, if a manager is discouraging innovation by frequently refocusing staff on core tasks rather than innovative work, leadership has several options. Either eliminate the trigger by creating a central review process for innovative ideas to remove the manager’s influence, hack the reward by incentivising managers to promote innovation or hack the routine by changing the guidance on desired balance between core and innovative work. Implementing all of these ideas at once is likely to trigger a resistance response as the change may be too significant, but implementing just one (or one at a time over a period of time) is less likely to be rejected.

After executing hacks, the results should be assessed to create a constant feedback loop of small, low effort, easy hacks that can have big impact over time. These small-scale hacks also prove to be harder for the cynics to identify and try to derail. Slower, more subtle changes create a culture that is less skeptical and more receptive to deploying AI.

Reframe and structure AI use cases over time

Organisations that look to boost productivity are three times more likely to achieve ROI than those looking for headcount reductions. In fact, finance leaders expecting large headcount reductions are likely to be disappointed due to the limitations of AI’s intelligence. Gartner expects that less than 10% of finance functions will see headcount reductions by 2026.

Purchasing software is a good way to see quick AI value returns, but this path struggles to deliver long-term, strategic value. On the other hand, developing homegrown AI tools can deliver strategic value, but requires spending time upskilling staff. A third path, which Gartner has dubbed “the Golden Path of AI Adoption,” blends the two approaches to deliver immediate uplift with long-term strategic impact. This path, in turn, can be delivered through a series of culture hacks. 

For example, starting with outside ideas, finance leaders can use workshops to provide team members a base knowledge and start organising use-case competitions. From there, communities of practice can give deeper education and eventually, make use case identification a regular part of how teams work with various innovations or mandates.

Whatever the path, finance leaders should recognise the opportunity to hack the habits that are preventing team members from becoming more familiar with AI and the art of the possible.

While changes as comprehensive as AI adoption and team culture would seem to require robust and highly layered change management plans, the plans and paths to achieve success do not need to be monumental, and certainly should never feel monumental to staff. Instead, CFOs and finance leaders must acknowledge that small, unassuming and gradual changes are no less substantial or worthy, and in many cases, are more impactful. In the end, the human habits and thought patterns, along with a new way of gaining reward, will reinforce AI’s value and use among finance teams.

Author –

Clement Christensen is a Senior Director Analyst in Gartner Finance practice, and will be presenting on AI adoption and cultural change at the Gartner CFO & Finance Executive Conference in Sydney on 24-25 March 2025.