Change Management Is the Most Underfunded Part of Every SAP Migration

The more interesting number in SAVIC's research isn't the deflection rate. It's what adoption intensity does to measured productivity. Deployments reaching 60% or higher weekly-active adoption produced three to four times the measured productivity improvement of low-adoption deployments using the same underlying tools. The AI copilot itself doesn't generate that value. Getting enough of the workforce to actually use it, consistently, does. And that puts change management back at the center of the picture instead of the periphery.

SAVIC's research also offers a specific, actionable number here: high-performing implementations allocate 15–25% of their total AI programme budget specifically to change management, nearly double the average share Prosci found across ERP programs generally. There's a reason for that. It's the closest thing in this research to a direct causal link between change management investment and realized value from AI-assisted tooling.

the productivity improvement seen in deployments with 60%+ weekly-active adoption, compared to low-adoption deployments using identical AI tooling. (SAVIC Technologies, citing SAP data)

An always-available AI copilot can quietly become a crutch instead of a bridge to real capability, if it's the only investment a program makes in adoption. A user who can always ask a chatbot how to complete a transaction may never build the underlying process fluency the organization needs, particularly for less routine scenarios the copilot hasn't seen enough of to answer well. The programs getting this right use AI copilots to absorb the high-volume, routine question load. That frees a genuinely well-resourced change management team (trainers, champions, super-users) to focus on the harder work: building real capability and handling process changes that need more than a quick answer.