Driving AI Adoption, From Resistance to Results

Driving AI Adoption, From Resistance to Results

If you’re reading this, it’s likely that you’ve encountered people that are resisting the adoption of AI tools and services into their daily work. Resistance to change is a natural human instinct, but in the AI era, clinging to the old way of doing things could be detrimental to your business.

Some of this resistance is down to lack of interest in diverting from the norm, some of it is lack of interest in learning something new, and some of it is fear their jobs will be replaced by AI. Whatever the reason, business leaders have to find ways to drive AI adoption in their companies, while bringing employees along on the journey.

AI transformation change management is the process of guiding people, processes and technology through the cultural shifts needed to move from “nice to have” experiments to real, sustained business impact. Let's look at some approaches to countering the hesitancy among your teams.

Define Your AI Strategy

The best place to start is to define and clearly communicate that the company strategy is to adopt AI. This top down approach is effectively mandating that all teams and roles adopt AI into their ways of working. This involves updating roles and responsibilities and linking AI related goals to performance reviews, making engagement a part of future career growth and compensation.

Some CEOs, from well known companies, have taken this approach, and in some cases their internal emails have been shared publicly.

This approach by itself will not cover all bases, a subset of people will embrace the challenge and get stuck in while others may say; “I’m too busy and don’t have time to learn about this new technology”, or “I tried it and it didn’t get it right”.

It may feel like there’s no time, but even with minimal effort anyone can get a return on the investment of their time, even if it’s a simple case of using AI to draft an email. The “didn’t get it right” point can be frustrating. If someone enters a poor prompt it’s unlikely that AI will “get it right”. A certain amount of trial and error is required to learn how to write a good prompt. So yes, there is a learning curve, and some people will need guidance to get them through it.

Apply a Structured Change Framework

To take it to the next level, a structured change management framework can be quite effective. Let’s look at how we can apply Kotter’s 8-Step Model, with some practical examples at each stage:

  1. Create a Sense of Urgency
    • Share hard-hitting stats and news headlines about competitors’ AI wins.
    • Create a sense of “FOMO” by sharing internal success stories i.e. “Team X cut development time by 60% by using an AI agent”.
  2. Build a Guiding Coalition
    • Launch a Community of Practice (CoP) composed of cross-functional AI champions. This group should meet weekly and run initiatives to share knowledge amongst their teams.
    • Run “Train-the-Trainer” sessions so each department has its own AI expert.
  3. Form a Strategic Vision
    • Define a clear roadmap i.e. “AI in 6 months”: from quick-win email drafting to agentic process automation.
    • Tie the vision to business KPIs such as; time saved, products delivered, customer satisfaction, revenue uplift etc.
  4. Communicate the Change Vision
    • Send out weekly updates with success stories, links to micro-learning videos, blog posts etc.
  5. Empower Action by Removing Barriers
    • Publish an internal guide explaining which tools can be used for each use case.
    • Purchase AI service licenses for defined roles, where applicable.
    • Instruct managers to schedule in dedicated time for teams to work with and learn about AI tools.
  6. Generate Short-term Wins
    • Identify low-hanging use cases:
      1. Documentation: AI drafts the first-draft of new documentation.
      2. Slide decks: Copilot generates key talking points and visuals.
    • Celebrate each milestone, consider rewards like “Earn-a-Day-in-Lieu” to reinforce behavior.
  7. Sustain Momentum
    • Include AI updates as a standing agenda item on all-hands meetings
    • Host hackathons that are open to everyone, with at least one non-technical participant per squad.
  8. Institute Change
    • Include AI-usage metrics in performance reviews and career-path conversations.
    • Update processes, job specs and onboarding materials to reflect “AI-first” ways of working.

AI Governance

Don’t forget about AI governance. Establish an AI Governance Group to define policies and standards, to assess risks, and promote ethical use of AI.

More on this topic here: AI Governance & the Journey To ISO 42001

Conclusion

There is no one shot way to get past the resistance of AI adoption, it takes time and repeated reinforcement. The “rule of seven” suggests that people need to hear a message at least seven times before they take action or remember it, so keep working at it!

By framing your AI adoption efforts in a structured change management model, backed up with real metrics, and arming your teams with knowledge, tools and incentives, you’ll move from resistance to real momentum, and ensure the AI driven mindset becomes a permanent way of working.