How to Build an Organization Where Creativity Actually Thrives

On April 16, 2026, Wharton Human-AI Research (WHAIR) continued its AI Horizons webinar series with a conversation on one of the most pressing challenges in business today: how to build organizations that are genuinely creative in an age of AI. Host Kartik Hosanagar, faculty co-director of WHAIR, was joined by Yoram (Jerry) Wind, Lauder Professor Emeritus and professor of marketing at the Wharton School, and Margherita Pagani, professor of AI for Business and funding director of the SKEMA Center for Artificial Intelligence. What follows are the key takeaways from that conversation on how leaders can design environments where creativity not only survives AI, but is amplified by it.

Creativity is not a talent, it’s a discipline. AI can accelerate every part of it.

One of the most persistent myths in business is that creativity belongs to a select few. Wind pushes back firmly: “I believe that creativity is a discipline. People use the numerous approaches that can enhance their creativity, and each one of them can be turbocharged by using AI.” His research identifies 12 sets of approaches to building creative capability, all of which can be strengthened through intentional AI use. For leaders, this reframes the conversation entirely. Creativity isn’t something you hire for, it’s something you build.

The leader’s job is to be the architect of a creative environment, not necessarily the source of creative ideas.

Wind describes the manager’s role as “the architect, the orchestrator of the environment.” That means creating psychological safety so people feel comfortable proposing ideas, breaking down silos that prevent interdisciplinary thinking, and building a culture that rewards experimentation and taking risks. In a world where yesterday’s approach is almost guaranteed not to work tomorrow, the organizations that continuously challenge their own mental models will be the ones that stay ahead.

There are three ways to use AI as a creative partner and the most powerful one is often overlooked.

Pagani’s research, drawn from interviews with AI artists and business managers, identifies three distinct modes of AI use in creative work: as an efficiency tool, as a lens to expand the range of possibilities, and as a collaborative colleague that challenges your thinking. That third mode is where the real value lies, but it requires deep knowledge of your own domain. As Pagani put it, working with AI as a colleague “obliges me to know perfectly the task and the different steps of the task, and then I collaborate so it challenges my view.”

Human-first collaboration design is the key to unlocking AI’s creative potential without losing diversity.

Hosanagar’s own research offers a striking finding: when participants were given AI tools without a structured process, the average quality of creative output went up, but the diversity of ideas went down dramatically, and top performers actually got worse. The fix was a “human-first round,” requiring people to ideate on their own before engaging AI. Satisfaction, ownership, and output quality all improved. The implication for business leaders is clear: it’s not enough to give your teams AI tools. You must design how they use them.

You can measure organizational creativity

Pagani outlines three dimensions for evaluating whether an organization is truly becoming more creative through AI: new or enhanced products or services enabled by AI, transformed processes that redefine the role of humans alongside AI, and new partnerships or alliances that expand the organization’s reach into adjacent ecosystems. These aren’t soft metrics – they’re observable business outcomes that leaders can track and act on.

“Use AI or else” is not a strategy.

Hosanagar is direct about what doesn’t work: top-down mandates that pressure employees to adopt AI without a clear vision of what human-AI collaboration should look like. He describes seeing CEO memos that essentially say “use AI or you’ll be fired” and argues that they put all the responsibility on employees while offering no leadership on what good AI use actually means. The better model: celebrate employees who use AI well, share a clear organizational vision for human-AI collaboration, and rethink talent as individuals empowered by AI, not replaced by it.