The skyline of downtown Chicago reflected in the iconic sculpture “Cloudgate,” better known by local residents and tourists as “the Bean.” Appropriately, clouds swirl over the skyscrapers and are reflected in the sculpture. To me, Cloudgate resembles an elongated crystal ball and symbolizes a future of creativity and innovation. Photo by Skip Hidlay

Using AI to amplify and optimize a team’s work.

My epiphany about AI came in June 2024, near the end of a conference session for senior leaders.

“If you take nothing else away from today, please accept that AI is here, it’s growing and it’s here to stay. It’s not going away,” the presenter said.

“You owe it to yourself to learn how to use AI, and you owe it to your teams to help them upskill to learn how to use AI as part of their jobs. Why? Because AI isn’t going to take anybody’s job. But in the future, people who know how to use AI are going to take the jobs of people who don’t.”

Until that moment, I had been in denial. That spring, the headlines about generative AI were foreboding. The stories often focused on the thousands upon thousands of jobs that could vanish as the powerful new technology was deployed to increase efficiencies — and profits — in many industries, particularly service industries.

They gave me a sense of déjà vu dread. I had watched a new technology — the internet — hollow out newsrooms starting in the Great Recession of 2007-2009, wiping out thousands of journalism jobs and prompting me to pivot my career into health care marketing and communications.

Rather than increasing my anxiety, the presenter’s challenge inspired me to act. Instead of living in denial, I walked out with a new leadership focus: stop worrying about what AI might do to our jobs and start helping my team learn to use AI and figure out how it could enhance our work.

Half Right

Two years later, the presenter’s view of the future looks half right.

People who know how to use AI are pulling ahead in their careers. But leading CEOs, including those at Ford, Amazon, Salesforce and JPMorgan Chase, have said publicly that many white-collar jobs at their companies will soon disappear because of AI-powered efficiencies.

Hiring of younger workers has slowed in the occupations most exposed to AI. Many leaders are using AI to do the same work with fewer people.

I won’t pretend that course never makes financial sense, but new evidence suggests it may not be the right strategy. A 2026 survey by the enterprise AI company Writer found that 97% of executives say their companies deployed AI agents in the past year, yet only 29% report significant return on their generative AI investments. The gap between those two numbers isn’t a technology problem. It’s a leadership problem.

Starting With Permission

We began our AI journey in July 2024 with my marketing and communications team at the Ohio State Wexner Medical Center. Every team member went through basic AI training. We gave them access to AI tools and encouraged them to experiment. We began launching pilot projects to see how we could use AI to take over repetitive, routine tasks, such as resizing photos and ads, and give time back to team members to use for more complex, creative projects.

Progress wasn’t instantaneous. It took time for people to adjust to a new way of working and thinking — to begin using AI as a strategic thought partner, albeit a super-smart junior one that needed oversight and management.

Through 2025 and into 2026, our AI experiments and pilot projects began to compound. By the time I left in March, the team had built a set of AI agents that changed what we were capable of. A few examples:

Physician bios: Profiles for the health system’s Find a Doctor and Find a Researcher platforms used to move from writer to proofreader to marketing manager to the digital team and back again — a process that often took up to two months. Now an agent drafts the bio, a proofreader refines it and the digital team handles approval and publishing. The first projects finished in under 10 days.

UX research: The user experience team loaded an agent with patient-experience survey data, national hospital benchmarks, website heat maps and usability best practices, then primed it to think like a UX researcher. It helped design a user test and then helped analyze the results, surfacing pain points and user motivations the team could act on.

Brand compliance: One of the biggest time consumers for any marketing team is brand review, ensuring that every creative asset meets brand standards for design and style. Now, the brand compliance agent draws on the team’s AP style guide, voice-and-tone guidelines and naming standards to rapidly review Word documents, PDFs and images, so everything passing through the team stays on brand.

Safety reports: Midyear and annual safety updates keep leadership informed, but compiling them steals time from the people doing the work. Microsoft Copilot and Google Gemini now draft a snapshot from communication plans and security screening data. The internal communications team reviews and refines instead of building from scratch.

None of these agents replaced a person. Each one freed up time — hours, even days — for team members to focus on larger, more complex creative projects.

Where Brand Actually Lives

This matters beyond productivity because brands are built at the moments of contact between a person and an organization.

A physician bio is one of those moments. For patients choosing a doctor, it’s often the first time they meet the person who will care for them. Getting accurate, well-written profiles published in 10 days instead of 60 doesn’t just clear a backlog. It gives consumers faster access to the information they need to make choices about their health care.

Just as important, every hour AI agents saved my former team went back into the work only people can do: applying judgment, creativity and problem-solving to continue building Ohio State’s health care brand.

The Choice

Whether to use AI to enhance and optimize the work of existing teams or to eliminate jobs is a leadership choice.

Every leader eventually will face that decision point. You can aim AI at reducing headcount, or you can use it to enhance and amplify your team members’ work.

The technology works the same either way. What differs is the philosophy behind it and, over time, the type of organization you end up creating.

I made my choice in July 2024. I’ve never regretted it.