Picture this scenario: a brilliant marketing director freezes during an AI training session. When asked to try ChatGPT for campaign ideas, she says, "I didn't get into marketing to have a machine do my thinking." Across the room, a junior analyst is already using AI to automate data reports, wondering why everyone seems so nervous.

This divide isn't unusual. Artificial intelligence is reshaping industries and workflows faster than many people can adapt. Yet despite rapid adoption, the real challenge isn't technical—it's deeply human. AI asks us not just to learn new tools, but to rethink what it means to create, decide and contribute.

As Gary Grossman highlighted in his VentureBeat article "When progress doesn't feel like home," AI challenges long-held identities, values and professional norms. To navigate this successfully, organisations must move beyond technical rollouts and treat AI adoption as a human transformation.

Based on Grossman's research, there are five distinct groups in this "cognitive migration." Each needs a completely different approach—and getting this wrong costs time, talent, and trust. Here's how to support them.

1. The enthusiasts: your AI champions

Who they are: Early adopters who experiment with AI tools and push boundaries. They see possibilities rather than problems and often frustrate colleagues with their enthusiasm.

What they need: Guidance, best practices and an environment to innovate responsibly without alienating others.

How to support them:

  • Offer advanced learning paths: Go beyond basics. Provide deep dives into prompt engineering, bias awareness and ethical considerations.
  • Create innovation hubs: Give them safe "sandboxes" to test ideas and showcase results internally without disrupting daily operations.
  • Turn them into AI mentors: Leverage their enthusiasm to bridge gaps between tech possibilities and human concerns. Train them to translate AI benefits into language that resonates with sceptics.

2. The reluctant adopters: building confidence

Who they are: Professionals whose roles now require AI skills, but who feel unprepared or uneasy. They're adopting because they must, not because they want to.

What they need: Confidence, clarity and practical integration support that connects to their existing expertise.

How to support them:

  • Deliver role-specific training: Focus on real tasks, not abstract concepts. Show the accountant how AI helps with expense categorisation, not how large language models work.
  • Explain the 'why' clearly: Make adoption meaningful by linking AI use to their professional goals, rather than portraying it as a compliance exercise.
  • Encourage peer learning: Create forums for sharing tips and experiences. When people hear success stories from colleagues in similar roles, adoption feels less threatening.

3. The principled sceptics: honouring values

Who they are: Often in empathy-driven roles—teachers, counsellors, healthcare workers—or those who see AI as fundamentally undermining human values and authentic work.

What they need: Respect for their professional identity and concrete reassurance that AI can complement, not replace, their essential human contributions.

How to support them:

  • Listen first: Host open conversations about concerns and boundaries before mandating any AI use. Their objections often reveal genuine ethical considerations worth addressing.
  • Show complementarity, not replacement: Highlight cases where AI reduces administrative burden, freeing time for human interaction. A teacher using AI to grade multiple choice tests has more time for one-on-one student support.
  • Guarantee ethical use: Provide complete transparency on data handling, decision-making processes, and safeguards against bias or misuse.

4. The unaware: future-proofing without fear

Who they are: Individuals in sectors that haven't yet felt AI's impact or who remain unaware of its growing relevance to their work.

What they need: Gentle awareness-building and practical skills to future-proof their careers without sparking unnecessary anxiety.

How to support them:

  • Introduce AI through familiar tools: Start with voice-to-text, language translation, or smart scheduling before moving to more complex applications.
  • Offer accessible "AI 101" sessions: Keep these practical and jargon-free. Focus on "AI is already helping you when..." rather than technical explanations.
  • Frame opportunity, not threat: Position AI as a tool for empowerment and efficiency, not job replacement. Show how it can make their current work more interesting, not obsolete.

5. The disconnected: ensuring inclusion

Who they are: People without reliable digital access, literacy, or resources—often due to socio-economic factors—who risk being left behind entirely.

What they need: Infrastructure, resources and culturally appropriate training to ensure the AI revolution doesn't deepen existing inequalities.

How to support them:

  • Provide accessible entry points: Partner with tech providers for subsidised tools, broadband access, and device lending programmes.
  • Run community-based training: Libraries, community centres and local organisations can deliver essential digital skills in trusted environments.
  • Demonstrate immediate, practical benefits: Show how AI helps in daily life—translation for non-native speakers, assistive technology for disabilities, or simplified government service access.

Universal principles for success

Regardless of which group someone belongs to, certain strategies work across all contexts:

Transparency builds trust: Be completely clear about what AI will—and won't—do within your organisation. Hidden AI implementations breed suspicion and resistance.

Keep humans at the centre: Position AI as a tool that enhances human creativity, judgement and connection, not something that erodes them. This framing matters more than the technology itself.

Create shared stories: Use real examples and success stories from within your organisation. Abstract benefits feel threatening; concrete improvements from trusted colleagues feel possible.

Measuring your progress

You'll know your approach is working when:

  • Voluntary AI adoption increases across all groups
  • People start sharing AI wins in team meetings
  • Questions shift from "Do I have to?" to "How can I?"
  • Resistance conversations become optimisation conversations

The bottom line

AI adoption will be hindered when organisations treat it as a technology rollout instead of a human transformation. The companies thriving with AI aren't just the ones with the best tools—they're the ones who recognised that behind every algorithm is a person asking, "What does this mean for me?"

Answer that question first, and the technology follows. Lead with empathy, not just efficiency, and you'll discover that progress doesn't have to feel like leaving home—it can feel like expanding it.