7. AI Is About to Change Change Enablement
For decades, Change Enablement has relied heavily on human judgement.
People review changes.
People assess risk.
People look for conflicts.
People decide whether something should be in approved.
People review what happened afterwards.
But what happens when AI can do much of the analysis? That's not a distant possibility. It's already becoming a practical opportunity.
Imagine a smarter change process
Imagine raising a change and having AI immediately analyse:
Similar changes from the past
Historical success and failure rates
Previous incidents
Known service dependencies
Potential customer impact
Conflicting changes
Implementation timing
Required stakeholders
Likely risk
Whether it resembles an existing standard change
It could then recommend: “This looks like a low-risk standard change.” or: “Changes of this type have historically created incidents in this environment.” That's potentially transformational.
From forms to intelligence
Today, many change processes capture enormous amounts of information. But how much of that information actually informs the next decision?
AI creates an opportunity to move from: recording change to learning from change.
Imagine a system that continuously learns from:
Changes
Incidents
Problems
Releases
Service requests
Customer contacts
Monitoring data
Post-implementation reviews
The change process becomes increasingly intelligent.
AI could reduce bureaucracy
This is where I think the opportunity is particularly interesting. AI shouldn't necessarily create another layer of governance. It could remove one.
For example, instead of someone manually reviewing hundreds of historical changes to decide whether a change should become standard, AI could identify patterns.
Instead of manually checking change calendars for conflicts, AI could flag potential collisions.
Instead of writing every implementation and rollback plan from scratch, AI could provide a starting point based on previous successful changes.
Instead of asking a change manager to read every ticket, AI could highlight the ones that actually need attention.
That's augmentation. And that's where AI can be genuinely valuable.
But there's a catch
If AI recommends that a change is low risk, who is accountable if it goes wrong?
If AI identifies a change as suitable for standard treatment, who owns that decision?
If AI drafts the rollback plan, who validates it?
This is where governance becomes critical.
AI can provide analysis.
It can provide recommendations.
It can identify patterns.
But accountability cannot simply disappear into an algorithm.
The danger of AI-powered automation
There is another risk. We could accidentally automate bad governance. If our existing change process is overly bureaucratic, putting AI on top of it doesn't necessarily fix the problem.
We might simply create: faster bureaucracy.
Before automating, ask: Is this a valuable control or just an existing step we've become accustomed to?
That's an important distinction.
A sensible starting point
Organisations don't need to introduce AI into every part of Change Enablement overnight. Start with areas where it can assist rather than decide.
For example:
Change classification - Recommend standard, normal or emergency.
Risk analysis - Identify potential risk factors.
Conflict detection - Highlight potential collisions.
Impact analysis - Identify potentially affected services and stakeholders.
Change documentation - Draft implementation, validation and rollback plans.
Post-change analysis - Identify patterns across successful and failed changes.
Then keep humans accountable for the decisions that matter.
The future isn't AI versus people
I don't think AI will eliminate Change Enablement professionals. It may, however, change what we expect from them.
Less time reviewing forms.
Less time checking repetitive information.
Less time chasing approvals.
More time understanding organisational risk.
More time improving change capability.
More time looking at outcomes.
More time helping the organisation change intelligently.
That is a much more interesting future.
The question isn't: “Will AI replace change managers?” The better question is: “How much better could our change decisions become if our people had intelligent assistance?” And perhaps the most important question of all: Are we ready to trust AI with analysis without giving it accountability?
Next in the series: The Future of Change Enablement—From Approval to Confidence.
Change Enablement - Beyond the Change Ticket.
Comments