Stakeholder Alignment and Change Management

You've got your use cases selected. Now comes the bit that trips up most technical teams.

People.

Technology implementations rarely fail because the technology doesn't work. They fail because nobody got the right people on board. Months later you're left with expensive shelfware and a team still doing things the old way.

AI amplifies this challenge. People have feelings about AI that they don't have about a new reporting module. Some are excited. Some are convinced their jobs are disappearing. Some think it's overhyped nonsense. You need to address all of that before you go live.

Who Actually Needs to Be in the Room

Executive sponsors provide air cover and funding. They need business outcomes, not technical details. Keep them informed at the right level and they'll protect your project when politics get difficult.

Data owners control the information your AI will consume. If they're uncomfortable with how data flows through the system, they can block progress with a single email. Get them onside early.

Workers councils matter in some regions. If AI affects how employees work, you may need formal consultation. Check your local requirements. Discovering this late is painful.

The people who'll actually use it are often forgotten until rollout day. Service desk agents, operations staff, HR teams. They determine whether this succeeds or fails. Their concerns deserve attention, not dismissal.

The Conversation Nobody Wants to Have

People worry about their jobs. They've seen the headlines. Telling them AI will "augment not replace" sounds like corporate speak for "we're automating you out."

Be genuine instead. Summarising incident histories isn't the fulfilling part of anyone's job. Helping users solve tricky problems is. Show how AI shifts the balance toward work people actually enjoy doing.

Be honest about limitations too. AI hallucinates. It needs human oversight. It gets things wrong. People feel better knowing they're still essential. And they genuinely are.

Champions Beat Mandates

You can't personally convince everyone. Nor should you try.

Find people who are curious about AI. Give them early access. Let them experience benefits firsthand.

When someone's colleague says "this saves me twenty minutes per incident", it lands differently than when management sends another email about "embracing digital transformation." Peer influence beats policy every time.

Invest in your champions. Extra training, direct feedback channels, recognition for their role. They'll carry your change management on their shoulders.

Communication That Doesn't Get Ignored

Most project communication disappears into the void. Lengthy emails nobody finishes. Intranet posts nobody finds.

Keep messages short and specific. Tailor by audience. If people worry about job security, address job security directly. Silence on difficult topics gets filled with rumours.

Once you have wins, share them properly. A sixty second video of a real colleague explaining how AI helped them beats any slide deck you'll ever create.

Teaching People to Think, Not Just Click

Standard system training covers where to find buttons. AI training needs to cover judgement.

How do you know when output is trustworthy? What should you verify before using a summary? When should you override suggestions? These questions matter more than navigation.

Provide ongoing support after launch. Quick guides. A place to ask questions without feeling foolish. The real learning happens when people start using this for actual work.

Knowing Whether It's Working

Track genuine usage, not vanity metrics. Are people using AI features more than once? Or trying them, shrugging, and reverting to old habits?

If teams struggle, support them rather than blame them. If features aren't landing, find out why before assuming user resistance.

Adoption determines whether your investment delivers value or becomes another failed initiative. Treat it accordingly.

Right, people sorted. Now let's talk about the rules you need to follow.