The AI-Ready Finance Team: What It Looks Like and How to Build One

There’s a lot of noise around AI in finance. But from what we’re seeing across iMultiply (talent) and FIN (AI & automation), the biggest gap isn’t technology. It’s readiness. Because being “AI-ready” isn’t about tools, it’s about how your team thinks, works, and adds value.

What an AI-Ready Finance Team Looks Like

Across the teams we see, the work is starting to shift. Less time is spent gathering data and more time interpreting it. The focus moves from understanding what happened to deciding what to do next.

From a talent perspective, the demand isn’t for AI specialists. It’s for people who are commercially aware, curious, adaptable, and confident challenging outputs — including AI-generated ones. Strong technical foundations still matter, but mindset is increasingly the differentiator.

From an AI and automation perspective, the most effective teams don’t treat AI and automation as a project. It’s continuous. Repetitive work is actively reduced, processes are designed for efficiency, and teams adapt as tools evolve. The reality is most teams are earlier in this journey than they think.

One of the biggest blockers we see across both sides is data trust. Many teams want AI but don’t trust their own numbers. AI-ready teams understand where their data comes from, have clear ownership, and spend more time using data than validating it.

Leadership is where this comes together. In teams making real progress, value is no longer measured by output alone, but by insight, speed, and impact on decision-making. This is where talent and automation intersect.

How to Build an AI-Ready Finance Team

• Start with friction, not tools. From both a talent and automation perspective, the starting point is the same — where is time being lost, repeated, or overly reliant on individuals.
• Redefine roles. Don’t layer AI onto outdated job specifications. Shift expectations towards insight and influence, then reflect that in hiring and structure.
• Build capability, not just headcount. Hiring alone won’t solve this. Upskill existing teams, hire for mindset, and create space for learning.
• Start small with automation. Focus on areas like reporting, forecasting, and variance analysis. Prove value, build confidence, and then scale.
• Align leadership early. Be clear on what finance should deliver and what will stop, not just what will start.

Where Teams Get Stuck

Across iMultiply and FIN, we consistently see the same challenges. Organisations jump to AI before fixing fundamentals, hire for outdated roles, underestimate the mindset shift, and treat transformation as a one-off project.

Final Thought

The AI-ready finance team isn’t defined by tools. It’s defined by the intersection of talent and automation. Get that right and everything accelerates. Miss it and even the best technology won’t land.