Empowering finance with AI: why a bottom up approach is key to business success

Despite widespread investment in AI, we are still seeing the adoption of superficial AI initiatives that are failing to deliver tangible value where it matters most. This is particularly true when AI strategies are imposed from the top down, overlooking the insights of those closest to a company’s daily operations.

Enthusiastic individuals might experiment with “shadow AI” tools, increasing risk, while others disengage completely due to a lack of clarity, confidence, or belief. This prevents the kind of scalable adoption that truly transforms a business. For the finance function, which thrives on process and measurable outcomes, this fragmented approach to AI carries significant risks and can make finance teams feel as though their needs areen’t being met, leading to tools that lack value and impact.

So, how do we bridge this gap and ensure AI truly enhances high performance within finance?

The power of the frontline in AI adoption

Effective AI adoption, especially within the finance department, must begin by first understanding the needs of the people doing the work. Rather than simply imposing new AI tools, a bottom up approach involves engaging teams early, encouraging AI experimentation, and fostering a shared understanding of what successful AI adoption looks like.

Finance professionals are uniquely positioned to identify specific, localised problems that AI can solve. They understand the nuances of data, the bottlenecks in processes, and where automation can genuinely boost productivity and efficiency. According to our research, finance employees strongly believe that financial software and real-time data are essential for high performance. AI platforms that provide real-time data and analytics can automate repetitive tasks, analyse data faster, and uncover key insights crucial for agile business decisions.

When these tools are adopted from the ground up, they help bridge the disconnect between finance employees' focus on immediate outcomes and leaders' broader view of operational excellence, such as efficient processes and quick decisions. This is why leaders must provide their finance teams with permission to challenge legacy processes and experiment with AI solutions.

Establishing the right AI foundations

For the finance sector, two pillars are critical for successful bottom up AI adoption: education and governance.

It’s vital for business leaders to support finance teams with the knowledge to understand precisely what AI is, what it isn’t, and how it applies to their specific financial context. This enables them to distinguish between genuine innovation and “shiny new tech”.

Secondly, governance cannot be overstated in finance. Organisations must set clear parameters for which AI tools are trusted, how sensitive financial data is managed, and how AI outputs are validated. Without these foundations, there is a risk of poorly governed tools becoming embedded into the way the workforce operates, which for finance could lead to significant strategic and compliance risks.

Adopting practical approaches to AI

Organisations serious about bottom up AI adoption demonstrate this commitment through actions such as a consistent investment in research and development to stress-test AI across different business functions, identifying meaningful use cases directly from teams, and scaling only what genuinely works.

This ensures that AI adoption is not treated as a standalone innovation project but as a day-to-day operational shift, supported by education, cross-organisational alignment, and strong governance at every level.

Unlocking long-term high performance isn't just about implementing the latest technology – it’s about aligning people, technology, and culture towards a common goal. By empowering finance professionals to identify and implement AI solutions from the bottom up, business leaders are choosing to blend the finance department’s essential caution with a healthy degree of innovation and a willingness to learn from experimentation.

As the finance function unites around a common vision for AI, it helps develop a workplace culture where success is judged not only by results, but by a shared drive to innovate and adapt.