AI Adoption Requires Leadership, Not Just Licenses

Lack of a clear AI strategy from leadership is hurting AI adoption across organizations. Leadership purchases AI tools, sets goals for usage, and waits for success. The team doesn’t fully understand how to use the tools, doesn’t understand the expectations, or what success means. They understand there is a mandate and metrics are being tracked. AI usage becomes performative and adoption lags. Leadership ends up frustrated with the team and infers a lack of interest or motivation. It’s mixed signals for everyone which feeds a culture of fear and frustration with the tools.

This is the most important of the readiness categories I’ve identified for an organization. It is the reason an AI adoption strategy will succeed or fail. As a leader:

• What’s been your messaging?
• How are you using it?
• What are your expectations?
• Do you have metrics for them? Does your team understand them?
• Are you honest with your own usage and understanding of the tools?
• Are you investing in your team alongside paying for the licenses?

Leadership must be front and center on this journey. You are the one that determines the expectations, changes in work & roles, and provides the culture to share lessons, stumbles and wins.

So, why are AI adoption strategies and rollouts failing?

AI accelerates everything and it’s accelerated the disconnect a team feels from their senior leadership.

When AI is just a tool investment without a communicated and lived strategy, the team creates their own story and ideas on the intent. This leads to confusion, performative usage, and even resentment. 

There is an expectations mismatch.

Leadership is expecting a return on their investment. However, the team is not positioned to determine what that means and will infer their own intent. Is the expectation:

• Productivity increases?
• Quality of work improves?
• Common workflows are automated?
• A reduction in staffing needs?

Leaders need to define their expectations and provide consistent communication on how work is changing to guide the team towards those outcomes. It's a collaborative process between the team and leadership.

There are a ton of marketing headlines and real uses cases on the transformative power of AI. However, each organization is unique so understanding how to apply these transformative tools and the expected outcomes can only come from within the organization. It’s important that clear communication happens on these changes in work or it is just going to feel like more work to the team.

I’ve connected with many people that have told me they get long AI generated dissertations on how to do a task and a solution from their leadership. See how easy it is! The observation is that on top of trying to manage the immediate task, they now have to sort through a very long, often incorrect, solution from the leadership side. This approach generates immediate frustration and resentment towards AI tooling.

Another gap I see is the disconnect between how leadership uses AI and how the team uses it. The use cases for someone in a senior leadership or executive position are different. In reality, each of us is going to use these tools differently. The opportunity we all have is we can use these tools to close our own gaps. It’s going to look a little different for everyone.

Leaders think they are helping adoption showing the ease in which they use the tools but the team is frustrated. They feel it’s causing more work, and trust is lost.

In my leadership and executive roles, I am using AI daily as a note taker, a research assistant, and to make sure my communication is clear. Just to name a few. A major gap in my capabilities is my ability to design anything. It is seriously laughable how poorly I can draw. Using AI, I am able to work with the tools to generate a concept to communicate my ideas to people better equipped to handle the work. It allows me an option to speak closer to a designer's language.

The point is that leveraging AI is role and people dependent. Everyone is going to leverage it a little different in their day-to-day work. There are different benefits based on each person’s unique skillsets and capabilities. It’s not a one size fits all model for individual users.

Here are some ways to overcome these pitfalls:

• Develop a clear AI strategy with your team. Communicate it. Then live it.
• Leadership should bring their team into their AI usage. If AI has helped generate some ideas, bring your people into that discussion. Each of the major AI tools have the capability to collaborate on a discussion and share the output. You’ll help your team understand how you’re using it and bring them into the solution.
• Create a collaborative, sharing focused environment. People need to feel safe sharing what works and what doesn’t. Cross-role sharing is important because it will help the team find ideas they hadn’t even considered.
• Leadership needs to share their mistakes and learnings. This is the most impactful way to help your team get on board. Jump in alongside the team. Share what you’re doing. If you show your mistakes, the team will feel less pressure to have everything figured out on day 1 and share their own lessons.

If your AI rollout has slowed, these practices are a good way to get it back on track.

The leadership team has the ability to make or break their AI adoption. The technology selection and the team’s willingness to engage matter but not as much as leadership learning alongside their team.

If you’re working on your AI rollout and have hit a wall, let’s discuss what success looks like for your organization to improve your AI rollout strategy.