Build Trust Before You Build Adoption
Create understanding before asking for change
E1 | Explain
WHAT IT MEANS Before asking anyone to change how they work, give them an honest account of why. Explain the business case for AI adoption, the specific ways the organization plans to use it, and what it means for experienced workers specifically. Name the fears the room is already carrying rather than waiting for them to surface as resistance.
What it looks like in practice: A direct, leader-led communication, not a slide deck from IT. It should address three questions workers are already asking:
How will this impact our team?
What does this mean for my job?
What support will I have?
The answers don’t need to be perfect. They need to be honest and human.
The organizational principle: Workers who understand the why before they encounter the what are significantly more likely to engage constructively. Clarity reduces anxiety, and anxiety is the enemy of adoption.
E2 | Engage
What It Means Move from informing to involving. Engagement means actively soliciting the perspectives, concerns, and ideas of your experienced workforce before decisions are finalized. This isn’t a courtesy, but a genuine input into how AI gets implemented.
What it looks like in practice: Dedicated listening sessions built around your 50-plus cohort, either as standalone forums or as broader sessions that deliberately invite their voices forward.
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Standalone formats work better for workers who are newer to AI or feel behind the curve; they need space to ask basic questions without feeling social pressure from tech-fluent colleagues.
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Integrated formats work better for the segment already experimenting and ready to share what they've learned.
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Either way, questions should surface what they already know about their workflows, where they see opportunity, and what they're worried about. Treat their institutional knowledge as an asset to be leveraged in the design of AI adoption, not a habit to be overcome.
The organizational principle: The best ideas for how an organization should use AI often come from the people closest to the work, not from the top or center of the org chart. Engagement turns experienced workers from passive recipients of change into active co-architects of it.
PUT IT INTO PRACTICE
The First 30 Days | Explain and Engage
Theme: Create the conditions for trust before asking for adoption.
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Conduct a candid workforce assessment
Survey your experienced workers on AI awareness, current use, and concerns, not to measure performance but to signal that their perspective matters. Design the assessment to surface what people are already doing with AI (usually more than leaders expect), what they’re worried about, and where they see opportunity. This data shapes everything that follows and prevents you from designing an adoption program for workers you imagined rather than the ones you have.
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Solicit specific insights from 50-plus workers
Ensure your 50-plus employees have dedicated space to speak. Whether through a standalone session, a structured team-level conversation, or a targeted survey with follow-up, send a clear message that you’re seeking their input. The format matters less than the signal; the message is that this cohort’s perspective is being actively sought, not passively tolerated. Research consistently finds that employees are three times more likely to already be using AI than their C-suite leaders expect. [01] This session will surface that activity and reframe it as an asset.
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Address the fear directly and on the record
Don’t wait for resistance to organize itself. Communicate explicitly: what AI will be used for, what it won’t be used for, who retains decision authority, and what support the organization is committing to. The EY Work Reimagined Survey found that positioning AI adoption as a collaborative learning opportunity—and not just an individual technical skill—can strengthen organizational culture. [02] Clarity is not a soft consideration. It is an adoption lever.
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Identify your AI ambassadors
Look specifically among your experienced workers for early adopters. They are curious, credible, and respected by peers. These are not necessarily the most technically proficient employees. They are the people whose enthusiasm will carry social permission into the rest of the organization. McKinsey identifies ambassador networks as particularly powerful in AI adoption, precisely because everyone—at every level—is still learning, and authority flows from credibility rather than hierarchy. [03]
30-Day Success Signals -
Experienced workers can describe what the organization's AI adoption effort is for and what it means for them specifically.
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A small but visible ambassador cohort is in place.