Optimistically Scared: What Fortune 500 Execs Really Think About AI

A view from the front lines

What’s it like to be a business executive in the age of AI? Last week I hosted twenty Directors, VPs and CEOs from companies including Google, Walmart, Kimberly-Clark and Accenture for an honest discussion about AI. They shared how they are navigating a period of intense disruption without a map.

One executive put it perfectly: “I’m optimistically scared S***less.” Today’s leaders are making million-dollar decisions without proven case studies, balancing urgency and risk, and deciding which of 10,000 AI startups to bet on.

Here’s what they said.

A Leadership Squeeze

“AI is a business imperative but a failed project could ruin my career”

Less than 1% of employees make it to the director level or higher of a Fortune 500 company. Whether the culture is collaborative or cutthroat, executive circles are competitive. Mistakes are magnified and few companies reward failure, even when there are valuable lessons.

Now add AI into the equation. Last month, Starbucks’ stock rose 2% just for announcing plans for an “AI Barista”. The market rewards even the promise of AI adoption, competitors are moving fast and boards want to see results.

Leaders face pressure from both sides: Move too slowly and you’re accused of falling behind on AI, or move too fast and risk a high-profile failure.

Flying Without Instruments

“We’re building the plane while it’s in the air”

A theme throughout the day was how new everything is: new technology, new solutions, new vendors, new ways of working.

Traditional software decisions follow a predictable path: case studies, expert consultants, structured RFPs. But with AI, case studies are rare and best practices change every quarter. The deepest domain experts often have two years of experience or less.

Basic decisions like “buy vs. build” have become much more complicated. Instead of an Oracle vs. Workday bake-off, companies face new questions: Will an AI startup deliver features I can’t get elsewhere? Can I build exactly what I want for less? Will these choices change in 6 months when the technology improves again?

One leader captured the frustration with waiting on established vendors: “What happened to software product roadmaps?” Plans that used to span 3-5 years are now as short as 6 months, making it hard to predict when features will arrive or whether they’ll meet your needs.

Pilot Season

“Pilots help us decide what is actually worth scaling”

Without case studies or roadmaps, leaders are turning to pilots to manage risk. These are short, 3-6 month experiments with a small group of users. Teams iterate through multiple rounds of testing and use success criteria to decide on what to deploy to the full company.

Pilots aren’t perfect, but they let teams evaluate solutions on real company data without betting the farm. The best companies leverage a learning agenda: a library of questions and outcomes that grows over time into a rich base of experience across technologies, vendors, and use cases.

The Human Problem

“How do I get people to give up Excel?!?!”

AI tools are powerful, but they only work if employees use them. And why would someone embrace a technology that could cost them their jobs?

The Excel quote captures a deeper challenge. Employees have spent years mastering tools with hotkeys, shortcuts and workarounds that make them hyper-efficient. For these power users, AI offers limited benefits while threatening to diminish their expertise and possibly their careers.

Trust compounds this problem. Research shows that people are less forgiving of computer mistakes than of human ones, and co-workers think less highly of peers who use AI. Deploying an AI solution that makes mistakes doesn’t just hurt adoption, it also creates longer-term credibility issues.

The board believed the best approach was candor. AI projects will impact jobs, but falling behind is the bigger risk. Employees who resist learning don’t just hurt their company’s competitiveness, they become the most vulnerable if cuts are made.

The Talent Crunch

“I have more AI projects than people to execute them”

While the board was split on AI’s impact on hiring, they were unanimous on one thing: finding talent with AI skills is hard.

Leaders want people who are AI-native and could apply these tools to business processes like accounting, customer service, or marketing. But they also place a premium on raw talent over specific skills. Roles are changing so fast that current expertise becomes obsolete in months.

Human skills like proactivity, problem solving, courage and collaboration were seen as essential. In a world where raw intelligence is available at our fingertips, the ability to adapt and execute matters more than what you know today.

Chaos in the Fast Lane

“Why do things move slower when I push them? Because it sparks a thousand fire drills instead of focused efforts.”

One final irony: The race to move fast on AI creates a chaotic mess of initiatives that makes things slower.

CEO mandates, ambitious teams and eager vendors have led to a torrent of overlapping initiatives. Leaders are drowning in pitches from Google, Anthropic and OpenAI plus hundreds of startups and consultants offering free pilots to get their foot in the door. It’s great to have options, but the sheer number creates decision-making paralysis.

While leaders envied the agility of smaller companies, they were realistic that it takes governance to operate organizations with thousands of employees. Governance isn’t fun, but the hard work of aligning across teams and making tough decisions is essential to move effectively.

Leading Through the Chaos

“I’m optimistically scared S***less”

At the start of the day we asked the leaders for one word to describe their AI mindset. Half chose “Optimistic”, with “Revolutionary” and “Excited” close behind.

AI is creating an array of new challenges for leaders, ones that barely existed just a year ago. But while the technology is new, the questions aren’t. How do I deploy uncertain technology while protecting my customers? How do I find the right talent and motivate them? How do I focus my team on what matters most?

Our group didn’t have all the answers. No one does. But that’s a leader’s job: build a strategy, filter out the noise, develop great talent, and make the tough calls.

AI can and will change the tools we use but it won’t change the job of a leader.

Dad Joke: Why did I keep the agenda moving? So the board wouldn’t get… Bored 🤦

Thanks for reading!

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