A few weeks ago, a good friend of mine started a new role as the Head of AI for a multinational company. I was excited for his career move, building on over two decades of product, industry, and AI experience, and to lead the company’s AI transformation. “How would you structure your 90-day plan in this role?” he asked after sharing a bit about the challenges and opportunities ahead in the new organization.
The other week, I caught up with another friend who has just started her Chief AI Officer role at a global manufacturing company. With a background in management consulting and innovation management, she’s advised dozens of organizations on setting up their AI program. “What do you think my first priority project should be?” she asked.
Here is what I shared with each one individually, and what I would do if I were new in an AI leadership role. If you find yourself moving into a new AI leadership role, this will give you more clarity on the key priorities.
The First 30 Days
Welcome to the new role! You’re officially in the information gathering phase. Ask as many questions as you can. Ask the stupid questions while your new colleagues are more forgiving to you for asking them. Learn as much as you can. Meet your manager, your team, your peers, your manager’s manager, your top-level executive, and key stakeholders across the business. Every piece of information they share is valuable.
Build rapport and try to understand the dynamics of the organization. Take it all in; don’t filter it (yet). Take a tour of key sites like a plant or store to understand what the business really does (beyond what you have seen on the website and during your interview rounds). Get a sense for the culture and what people are revealing to you about it. Does the senior leadership team embrace innovation? Do they lead by example? (Or is it just lip service?)
Finally, try to learn what’s been tried before and what worked (or didn’t). For example, ask these questions consistently and capture the different responses:
What are we doing?
What did we do (or try)?
What should we do?
By the end of the first 30 days, you will have dozens of little puzzle pieces that you can group and cluster as you move into the next phase.
Let’s make it concrete:
My CAIO friend shared how the company’s CEO has been introducing her as the new AI leader to the entire company, raising high expectations of addressing, solving, and fixing what has not had any structure or direction thus far. Let’s also not forget about the expectation of seeing results quickly.
Without a team or AI-savvy resources in place (yet), we talked about three things:
Set up a lightweight program: The CAIO owns AI across the company, but they rely on other subject matter experts to come up to speed to contribute. That means legal, IT, procurement, HR, and the respective business functions need to step up.
Establish an intake process for new AI projects: Bring structure to the chaos of letting each department “do AI.” Ensure governance without stifling innovation.
Manage expectations: Four weeks into the role, share with the CEO what you’ve learned and present an initial plan of key projects and milestones. The sooner you bring clarity to the situation that this transformation takes time, buy-in, and resources, the better.
The First 60 Days
You’re in month two now. Start looking for common themes and patterns in the answers you’re getting and in the questions others ask you. What’s going on at an organizational level, and what are the unspoken beliefs?
Find allies among the leadership team. Find out who is excited about the topic, who’s genuinely excited, and who’s ready to put their money where their mouth is. Keep listening, but test a few ideas that people with influence socialize with you. Are these ideas really going to move the needle, or do they seem to be more of a distraction to your core objectives?
You’ve landed here for a reason. Share your industry best practices and paint the “target versus gap” state, so you can build the roadmap for reaching that goal. Be respectful, objective, collaborative, and assertive. (That’s a lot to ask, but it’s a core challenge of any AI leadership role.)
By the end of this period, you should have:
Clarity about 1-3 quick wins that build momentum, show action, and don’t bog you down.
An understanding of the technical architecture, data and AI literacy, and the AI maturity of the company.
One or two allies who are willing to invest alongside you.
Your goal isn’t so much to create FOMO as it is to pick up speed. It’s very hard to get that assessment right when you are new to the company or organization.
Let’s make it concrete:
My Head of AI friend shared an example of a sales leader in the new company who has been pushing an idea for agentic sales support. While the project ticks the box for finding an ally, the circumstances seem more complicated than what would make it a quick win: Inconsistent data, multiple systems, data privacy requirements in a global organization, etc., etc.
While it might be a prestige project for the sales leader, my friend (and the few resources he has) would likely be consumed without a clear path to value or success.
Thank you for reading The AI MEMO. Feel free to share it with your network.
Organizations are racing to deploy Agentic AI, yet few are ready for the risks that emerge when employees use AI without structure, standards, or oversight.
The HUMAN Agentic AI Edge offers leaders a practical blueprint for building accountable AI-ready teams that consistently produce high-quality results. Drawing on real-world knowledge and insights from interviews with more than 50 AI leaders and experts, Andreas Welsch shows how to combine human judgment with Agentic AI capabilities to reach the level of performance many organizations expect but rarely achieve. This book prepares you to shape the next generation of AI-ready teams delivering high-quality results with high accountability.
Month three has just started. Slowly but surely, it’s getting harder to get away with asking stupid questions. You’re expected to know things now. For the last two months, you’ve listened. You’ve formed hypotheses. Now, it’s time to build your plan. What do you want to achieve within the next 90 days and within the first year of your new role?
Your biggest risks are trying to do too much yourself and getting pulled in ten different directions by various people, with little to show for it at the end of month three (or six, nine, or twelve). That will reflect on you and your performance, not theirs.
By the end of your first 90 days, you will have a strategic roadmap to establish and organize the company’s AI program, core processes for intake, governance, and validation, and the first few proof points that let you build further momentum. You have also identified a few additional areas and opportunities based on your previous experience and what you’ve learned from your interviews and getting to know the company better from the inside.
Conclusion
Despite several years of AI innovation, many organizations are only now establishing a central AI leadership role. Professionals and leaders moving into these roles often have their hands full establishing governance processes and consensus across the company and fellow leaders. Structuring your onboarding as an AI leader around a 30/60/90-day plan provides additional clarity and makes expectation management easier.
Depending on the history of how your new role has come to be and why you were selected to lead this effort, your stakeholders will have very high expectations. Manage these expectations softly, but firmly, and seek to build bridges. If now isn’t the right time to collaborate (for you or for them), revisit it in a quarter or two.
Join my bi-weekly podcast for leaders. Each episode features a different guest who shares their AI journey and actionable insights. Learn from your peers how you can lead artificial intelligence, agentic AI, generative AI & automation in business with confidence.
