What is AI’s impact on leadership?

My initial thought is that your POV on that topic will evolve as AI evolves. The foundation of the POV will likely stay the same (like the foundational principles and methods of leadership that stay consistent over time) but the details/application will change as AI’s integration into our lives deepens. That’s why the title of the article ends with “…” More to come after this article, but here are my current top five thoughts on the topic of AI’s impact on leadership:

Less Technical Skills: Given AI is technology, this seems counter-intuitive. AI’s primary value proposition is automating and speeding up technical tasks (yes, an oversimplification). Thus, your technical skills and experience are less important. The skills pie is good context. It is a useful leadership template (conceptual model) that summarizes skills as technical, conceptual, and interpersonal. Each role and level require a different mix of those skills. For example, a programmer might be 40% technical, 40% conceptual, and 10% interpersonal while a team leader might be 20% technical, 30% conceptual, and 50% interpersonal. In the realm of leadership, the technical slice of the team pie was already small. Now it arguably gets even smaller while the conceptual (which includes creativity) and interpersonal slices get even larger.

AI Agents & Rolled-up Sleeves: If you strive to lead in the midst of the AI revolution, you need to be an active participant. I have always felt that the best functional managers are the ones who stay up-to-date with the methods and technology of their team. For example, when I was a Programming Manger, I still programmed one-third of my time so that I could help members of my team debug code. It was critical in building and deepening my credibility. There is no standing on the sideline with AI. Thankfully, AI agents are making it easy to be hands-on. You just need to be willing to experiment…to play. Of course this means you need to set aside the time. One might object that using AI agents falls into the technical skill bucket. Given the rate of change and the low level of syntax required to use an AI agent, I view it as more closely aligned with conceptual skills.

Distributed Systems Rising: AI’s automation and streamlining is blowing up established processes. The world of standard operating procedures (SOPs) and even consistent operational KPI’s is the world of yesterday. This means rigid operational and organizational structures no longer do the job. I do not think the answer is decentralization (including self-managing teams). There are circumstances that Holocracy-like approaches work great, but in my view it is too dramatic a change for most companies (for example, there are no “leaders” in self-managing teams). Instead, I think distributed systems and teams is the right approach. It is basically 1-2 steps back from decentralization and 2-3 steps forward from rigid structure. It is setting vivid objectives with your teams (leveraging their minds in setting the direction), cascading those vivid objectives (working with individuals to articulate how they can directly impact the bigger picture), and then giving the team wider-than-ever guardrails to work (empowering them to be creative and innovative in building the path to the objectives). A critical guardrail and responsibility of the team leader is to gather feedback from the team, the company, and the market to challenge the current objectives to see if the direction needs to be adjusted. In my view, this approach has always been the right way to lead. AI is making it even more so.

Evolving Value Measurement: As I mentioned just above, legacy KPI’s likely no longer apply. How you measure the value added by your team is changing. Experimentation is more important than ever. Every book on innovation over the last 20 years discussed failing fast and rewarding the lessons of failure. Most companies talked about it, but few actually integrated it into their culture. With the AI revolution, the cost of not building a “test and learn” culture is greater than ever. The same applies to all the work on adapting to change. Change is officially becoming part of our day-to-day. In theory, the legacy productivity metrics of your team should skyrocket. If they do not, your team is not trying hard enough to challenge business-as-usual and break stuff.

Don’t Forget the Team: Availability heuristic keeping AI top-of-mind creates the risk that your team will get less of your time and focus. As someone who strives to lead a team, your team and the members of your team must always be your top priority. It will be tempting to offload too much conceptual work to your AI agents. AI agents are not a substitute for your team’s thinking. Use AI agents to create ideas for discussion with your team but not be the end of the discussion. Again, AI’s noise is and will continue to be a massive distraction from what is most important. Remember you are a servant leader first and an AI architect second. I think each of these five thoughts could be a blog post by themselves. I’m going to keep noodling the topic. What do you think? Do you agree with these five? Is there something I blatantly missed? Am I over-indexing on one of the topics?

Thank you for reading my leadership blog post. I hope you found it interesting and thought provoking.

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