Change management in AI projects is the structured approach used to help teams, processes and systems adapt to the introduction of autonomous technologies. In finance, it ensures that the transition from manual execution to AI-driven operations happens smoothly, without disrupting controls, compliance or daily workflows. AI does not only change how tasks are performed, it changes who performs them. That shift requires clarity, training and a progressive adoption framework.
Effective change management begins with transparency: explaining why AI is being introduced, what problems it solves and how roles will evolve. Finance professionals must understand that AI is not replacing expertise, it is taking over repetitive, labour-intensive tasks so teams can focus on oversight, decision-making and strategic analysis. This reduces resistance and builds trust in the new operating model.
The second pillar is process re-engineering. AI agents execute work differently from humans; they are faster, consistent and follow deterministic rules. Finance teams must therefore redefine workflows, escalation paths and controls to integrate this new digital workforce. Clear ownership models, who supervises the agent, who validates exceptions, who approves adjustments, are crucial.
Training is the third component. Teams need to learn how to supervise AI systems, interpret their outputs and provide structured feedback that strengthens model reliability over time.
Phacet supports this transition by deploying autonomous AI agents that integrate progressively, starting with targeted workflows. This incremental rollout allows teams to build confidence, measure early wins and expand adoption at a manageable pace. With proper change management, AI becomes not a disruption but a catalyst for higher performance, stability and operational clarity across the finance function.
