By Gerard Pietrykiewicz and Achim Klor
Achim is a fractional CMO who helps B2B GTM teams with brand-building and AI adoption. Gerard is a seasoned project manager and executive coach helping teams deliver software that actually works.
AI adoption gets stalled by leadership gaps: confusing policies, employee fear, and leaders who say “go” but don’t show how. If this feels a bit like Groundhog Day, you’re not alone. We’ve seen similar adoption challenges with desktop publishing, the Internet and World Wide Web, and blockchain. The technology is ready, but organizations stumble on the people side. This article looks at what leaders can do right now to remove those barriers and make adoption a little less stressful.
Jim Collins, in How The Mighty Fall, describes how once-great companies decline: hubris born of success, denial of risk, and grasping for silver bullets instead of facing reality. AI adoption sits at a similar crossroads. Companies that wait and assume their past success buys them time risk sliding down a similar path.
Reset (5 min):
Decisions today (10 min):
Guardrails (10 min):
Metrics (5 min):
Employees avoid tools they don’t understand. If your AI usage rules look like a legal brief, adoption will stall.
Large corporations often have the budget, legal teams, and even their own data centers to set up AI policies and infrastructure. That gives them speed at scale.
Smaller companies are technically more nimble, but without sufficient resources, they often default to over-restriction, sometimes banning AI entirely out of fear of risk. That means lost productivity and missed learning opportunities.
Opportunity: Make policies visual, clear, and quick to navigate. The goal isn’t control. It’s confidence. Guidance like the NIST AI Risk Management Framework shows how clarity enables trustworthy, scalable use (NIST).
Employees fear what they don’t understand. And one-size-fits-all training doesn’t help.
When people see AI applied to their specific role (automating a report, simplifying customer emails), that fear turns into enthusiasm.
Pilot programs work. Early adopters can demonstrate real use cases, and their wins spread fast inside the org.
Opportunity: Treat those early adopters as internal champions. Prosci’s research shows “change agents” accelerate adoption (Prosci). Then turn those wins into short internal stories and customer-facing examples. That’s how adoption builds brand credibility, not just productivity.
When executives hesitate, teams hesitate. The reverse is also true: when leaders use AI themselves, adoption accelerates.
Research on organizational change is clear: active, visible sponsorship is a top success factor (Prosci). It signals that experimentation is safe and expected.
And there’s an external benefit too. Leaders who show their own AI use give customers and partners confidence. It’s a market signal.
Opportunity: Leaders can’t delegate this. They need to be participants, not just sponsors.
To make AI adoption successful, leaders must create an environment where experimentation feels safe and useful.
The parallels to earlier waves of tech adoption are uncanny: the ones who figured this out first didn’t just get more efficient. They were remembered as the ones who defined the category because they were more effective adopting the tech.
The risk of waiting isn’t just lost productivity. It’s losing the perception battle before you even start. Credible stories and visible leadership shape buying decisions and long-term trust (Edelman–LinkedIn).
Leaders: simplify, experiment, participate, and share your wins. Your teams and your customers will thank you.
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This article is AC-A and published on LinkedIn. Join the conversation!
