From AI Awareness to AI Leadership: What an Executive Job Seeker Needs to Know

Key Takeaways

• Senior executives don't need to become AI experts, but they need to understand how AI is changing their function.
• Hands-on experience with AI is more valuable than simply saying you are "AI savvy."
• Executives should connect AI to real business problems, measurable results, and leadership decisions.
• Your resume, LinkedIn profile, and interview stories should show how you are adapting to AI rather than simply mentioning AI as a skill.

AI is Moving Into the C-Suite

There are some big numbers behind this change.

IBM's 2026 CEO study found that 76% of surveyed organizations now have a Chief AI Officer, compared with 26% in 2025. The study surveyed 2,000 CEOs and equivalent senior leaders across 33 geographies and 21 industries.

IBM also found that 85% of respondents believe functional leaders need to become technology experts in their own areas of the business. That doesn't mean every VP suddenly needs to become an IT expert. It means technology is becoming part of the job for leaders who used to leave most technology decisions to someone else.

That's an important difference if you’re currently in an executive job search or planning one for 2027.

AI isn't just a technology department issue anymore. It's showing up in operations, finance, marketing, human resources, healthcare, customer service, and just about every other part of a business.

For a senior executive who is looking for a new position, that creates a new expectation. You may not be expected to know everything about AI, but you should be able to explain how you are learning about it, where it can help your organization and how you would lead people through the changes it creates.

Start With Your Own Job Function

If you're trying to figure out how much AI you need to learn, I'd start with a simple question: What is AI changing in your part of the business?

Let's go back to that Chief Medical Officer. She doesn't need to start by taking a course on machine learning. She should start by looking at what is happening in healthcare and asking where AI is already affecting the work she is responsible for:

• Is AI changing clinical documentation?
• Is it affecting physician workflows?
• Is it being used to analyze medical information?
• Is it changing patient communication?
• Is it being used in quality, research, scheduling, or administrative work?
• What are the privacy, compliance, and patient safety questions?

These are the things a CMO should understand.

The same approach works in other functions. A CFO might look at forecasting, financial reporting, fraud detection, and analysis. A CHRO might look at recruiting, workforce planning, employee development, and skills analysis. A COO might look at process automation, forecasting, quality and productivity.

You don't have to learn AI in the abstract. Learn what it means for the work you already know. That gives you a much better place to start.

Then Start Utilizing AI

The next step is to actually use an AI platform. This is where I think a lot of executives make the process harder than it needs to be. They start looking for the perfect AI course, the perfect certification, or the perfect list of tools they need to master.

You don't need all of that to get started. Pick a few real problems from your own work and see what AI can do with them.

Use it to summarize a long report. Ask it to help organize information for a meeting. Give it a problem you're trying to think through and see what questions it raises. Use it to compare two approaches. Ask it to help you prepare for a difficult conversation. Then, check the answers. That's an important part of learning AI. You need to see where it is useful and what AI can't do for your executive job search.

You will also find that the quality of the answer depends a lot on the quality of the question and the information you provide. You start learning how to give better instructions, when to trust the output and when to question it, and where human judgment still matters.

This is what practical AI fluency looks like. You aren't trying to become an AI engineer. You're learning how to work with a tool that is becoming part of the business.

Your Goal Is to Solve Problems, Not Talk About AI

This is where the difference between AI awareness and AI leadership becomes important.

An executive can say, "I'm very interested in AI." That's fine, but it doesn't tell a prospective employer very much. A stronger conversation sounds more like this:

"I discovered our physicians were spending a lot of time on administrative work, so I started looking at where AI might be able to help. We identified a few areas to test, involved the people who needed to be involved, looked at the risks, and measured what happened."

Now you're talking about leadership. The technology is part of the story, but it isn't the whole story. You identified a problem, looked for a solution, and involved the people affected. You considered risks and tested something. You measured the result. That's what a senior executive is supposed to do.

IBM's research makes this point differently. The study found that 83% of surveyed CEOs believe AI success depends more on people adopting it than on the technology itself.

Implementing AI is going to require people to change how they work. Senior leaders have to understand that part of the job too.

You Need Enough Experience to Ask Better Questions

One of the biggest benefits of actually using AI is that it changes the questions you ask.

You probably don’t know how an AI system was built. In most cases, you don't have to. You do need to be able to ask whether the system is solving the right problem. Questions about using AI in your role could include:

• What information is it using?
• How will we know whether the answer is accurate?
• What happens when it gets something wrong?
• What information should never be put into the system?
• Where does human judgment remain necessary?
• How will we measure whether this actually helped the business?
• Who is responsible for the result?

These are executive questions that should be asked. In fact, your value as an executive may be knowing which questions need to be asked before your organization spends a lot of money or changes the way people work.

That's one reason I wouldn't tell an executive to chase every new AI tool. The tools will change. Your ability to evaluate a business problem, learn something new, lead people, and make good decisions is much more important.

This Changes How You Present Yourself in a Job Search

This is where AI becomes part of your career story. If you're a senior executive looking for your next role, your resume and LinkedIn profile should show that you're keeping up with changes in your field.

This doesn't mean adding "AI" to every section of your resume. It also doesn't mean calling yourself an AI strategist if you haven't actually done that work. Instead, look at what you've accomplished.

• Did you introduce a new technology?
• Did you automate part of a process?
• Did you reduce the amount of time your team spent on repetitive work?
• Did you use data to make better decisions?
• Did you lead a team through a technology change?
• Did you evaluate a new technology and decide not to use it because the risks or costs weren't worth it?

That last one can be just as valuable as implementing something. Good executive leadership isn't about adopting every new technology. It's about knowing where technology can help and where it doesn't make sense.

Your interview stories should tell the same story. If you're asked how you're using AI, don't give the interviewer a definition of generative AI. Talk about something you've actually done or something you have studied closely in your function.

Explain what problem you were trying to solve, what you learned, what you would do differently, and how you would approach it in a new organization. That's a much more credible conversation.

Don't Try to Become Someone You're Not

If you've spent 20 or 30 years building expertise in healthcare, finance, manufacturing, sales, or another field, you don't need to throw that experience away because AI has arrived. Your experience is still valuable, but adding AI knowledge and use to your skills will help you set you apart from other executive job seekers.

A Chief Medical Officer who understands medicine, knows how physicians work, understands patient care, and can also use AI to identify opportunities and evaluate risks has something valuable to offer. The same is true for a CFO who understands finance and can use AI to improve forecasting or analysis.

You don't have to compete with the person who built the technology. You have to understand enough about the technology to lead the people and business decisions around it.

LinkedIn's 2026 research found that 90% of C-suite leaders surveyed say their own roles require continuous skill building to keep up with change. That's a useful way to think about this. You aren't trying to finish learning AI. You're building the habit of learning it and using it in your role.

What I Would Tell That CMO

If that Chief Medical Officer were sitting across the table from me, I wouldn't tell her to go spend six months becoming an AI expert. I'd tell her to start with her own work.

Identify three or four areas where AI is already affecting healthcare. Pick one or two tools and use them yourself. Find people who are already using AI in ways that are relevant to your field. Ask questions and perform tests. Pay attention to what works and what doesn't.

Talking with people who are already using AI in your field can also help you understand where the technology is headed. Networking is especially important because many executive opportunities never reach the public job boards. Our guide to the hidden job market explains why networking matters so much in an executive search.

Then start thinking about how those experiences fit into your leadership story. You may discover that you don't need to know nearly as much about AI as you thought, or you need to learn more than you expected.

Either outcome is useful. The important thing is to start.

Because when you're interviewing for your next executive position, saying that you're interested in AI isn't going to tell an employer much.

Being able to explain how you’ve learned to use it, how you think about its risks and opportunities, and how you would help an organization apply it to real business problems is a much stronger story.

That's what a senior executive should be working toward in their executive job search. You need to become an executive who knows how to lead in a business that uses technology differently than it did a few years ago.

If you're preparing for an executive job search and you're not sure how your experience, skills, and current knowledge translate into the market today, that's exactly the kind of conversation we have with clients at Endeavor Agency. We help executives clarify their value, strengthen their personal brand, prepare for interviews, and build a job search strategy around the opportunities they want to pursue. Contact Endeavor to talk with us about your executive job search.

Sometimes the first step isn't learning everything. It's figuring out what you actually need to learn.

Frequently Asked Questions About AI Leadership for Senior Executives