How to Prepare Teams for AI Through Change Management

Across all finance functions, AI adoption has outpaced workforce readiness, and the gap is widening rather than narrowing.

A 2026 global study of business and technology leaders found that only 23% say their workforce is AI-ready, down from the previous year, even with continued growth in AI spending. Organizations that are excelling distinguish themselves by their ability to restructure how they work and manage change.

For Finance, Accounting, and Risk teams, this readiness gap carries particular weight. These functions operate under SOX, audit, and control obligations that leave little room for ambiguity about who is accountable for an AI-assisted outcome.

Implementing a new tool without preparing the people who will use it not only slows adoption but also creates operational and compliance risks that finance leaders cannot afford to absorb.

Why do AI implementations stall because of people, not technology?

It's tempting to treat AI implementation the same way organizations treat most enterprise technology launches — by selecting the tool, configuring the platform, training users on the interface, and going live.

Recent research suggests that this instinct is precisely what limits returns. Organizations that adopt a technology-centric approach to AI, which emphasizes the tool at the expense of the people who use it, are approximately 1.6 times more likely to not get a return on investment in AI compared to organizations that put people at the center of the transformation.

What does deliberate change management look like in practice?

The same 2026 research identifies a small group of organizations, approximately one in ten, that consistently outperform others in AI outcomes. What sets them apart is not budget or access to models. The difference is that they do three things well:

• They restructure functions around AI, rather than simply adding AI to existing functions;
• They implement change management so that the workforce understands the new operating model and the guidelines that govern it;
• They deliberately invest in workforce preparation, rather than assuming it will come naturally from access to the tool.

Corporate AI transformations should be designed from the outset, along with the new workflow and governance model, so that when an AI agent goes live, the people operating it already understand their new role in it.

The Emotional Layer That Finance Leaders Cannot Ignore

Every AI implementation in Finance carries an emotional layer that technical training alone does not address. FP&A, Accounting, and Controlling professionals are questioning what happens to their roles if AI produces the analysis they used to do.

Effective change management addresses this layer explicitly, rather than assuming that a training session will solve it.

This means naming what changes and what doesn't, being transparent about how roles will evolve, and giving people a credible answer to the question "what's in it for me?" before asking them to change how they work. Leaders who model the use of AI, visibly and imperfectly, contribute more to building trust than any policy document.

Training is not change management, but it should be structured as if it were

We believe that training that functions as change management:

• is specific to each role and use;
• is practiced in daily workflows;
• incorporates the governance and control context that finance professionals already work with.

In this way, training becomes the mechanism that brings change management to work in practice, and not a separate initiative that happens before the change begins.

Notes

Developed by Quantum Rise and CrossCountry Consulting not as a one-off AI literacy session, but as a structured day that treats change management as a design principle from the first module. In the next post in this series, we'll take readers inside this workshop and follow a finance professional through each module. Stay tuned!

This post is part of a joint thought leadership series developed by CrossCountry Consulting and Quantum Rise. Together, the two firms deliver the AI for the Office of the CFO, a hands-on AI workshop designed specifically for Finance, Accounting, and Risk professionals. CrossCountry Consulting brings deep finance domain expertise and a dedicated AI transformation practice, including the AI Innovation Lab and the CrossCoreAI agentic platform. Quantum Rise brings enterprise AI transformation methodology and a track record of deploying AI inside Fortune 500 operating models. To learn more visit crosscountry-consulting.com/ai and quantumrise.com/ai-training-academy.

References

• Kyndryl. 2026 People Readiness Report. Kyndryl, 2026. https://www.kyndryl.com/us/en/insights/people-readiness-report-2026
• Deloitte. Finance Workforce Strategy in the AI Era. Deloitte, 2026. https://www.deloitte.com/us/en/what-we-do/capabilities/finance-transformation/articles/finance-workforce-strategy-ai-era.html