But it will expose the bad ones.

Artificial intelligence is getting better every day — faster than most organizations are prepared for. You can already prompt tools like ChatGPT to write a change strategy, build a stakeholder analysis, or draft a training plan. It’s tempting to think, If AI can generate the work, what’s the point of an organizational change manager?

The answer: AI won’t replace change managers. But it will expose the bad ones.

The AI Temptation: Fast ≠ Good

Let’s say someone inexperienced in organizational change types “create a change management strategy for an ERP implementation,” along with details of the change, into an AI tool. In seconds, they’ll get a clean-looking plan. But scratch the surface, and you’ll see red flags:

• Vague stakeholder groups. AI might list generic groups like “employees,” “executives,” and “vendors.” Or, if it does name the right key groups, it might miss critical subgroups like informal influencers, front-line supervisors, or hybrid workers who will experience the change differently.

Example: A federal agency rolled out a new digital records system. The AI-generated plan lumped all users together, ignoring that contractors, field staff, and union members had vastly different access needs and security protocols. Adoption tanked.

• Generic resistance strategies. You’ll often see suggestions like “hold town halls” or “communicate early and often” with no tie to the actual sources of resistance or past organizational dynamics.

Example: A manufacturing company facing automation fears got an AI-suggested plan full of emails and Q&A documents. What it needed was face time with supervisors and a forum for employees to express job security concerns directly. Trust eroded fast.

• Fuzzy metrics. AI loves to include success measures like “improved engagement” or “stakeholder satisfaction,” without defining what those mean, how they’ll be measured, or what’s considered a success.

Example: A utility company used AI to set KPIs for a change effort. The dashboard showed high “awareness,” but field crews were particularly confused about new protocols. That group saw no behavior change — just pretty charts.

• Activity without impact. Plans might include training sessions, change agent networks, or communications tactics that check the box but don’t connect to real behavior shifts.

Example: A retail chain launched a DEI initiative with AI-generated deliverables: monthly newsletters, mandatory training, team charters. All were executed, but without a change story, leadership modeling, and accountability mechanisms, nothing stuck.

In short, AI can mimic change management strategies and plans. But without practitioner judgment, it can’t deliver a robust, custom, and nuanced roadmap.

That’s where the divide will sharpen. Unqualified practitioners may think they can “outsource” the work to AI, and their results will suffer. Good practitioners will use AI to do better, faster, smarter work.

AI as a Force Multiplier for Good OCM

The heart of change management plan that works is an understanding of the people involved.

The job of a change practitioner is not to churn out templates, but to shape strategy, coach leaders, and spark behavior change in real human systems.