Is your team using AI to work better or just faster? Are AI tools stifling your creativity? Are you using AI for the right processes?

There’s a bottomless pit of questions with which managers are contending while overseeing and implementing AI in a rapidly shifting environment. This week, Kellogg’s Hatim Rahman talks about how slowing down can be a benefit for your AI rollout.

Plus, we try to understand how big companies stay so … big.

Adjusting AI’s speed

As new tools and technology flood firms and upend workflows, leaders must learn to balance competing directives while making AI manageable.

Harvard Business Review interviewed 100 researchers and leaders to provide a framework for navigating common AI-related tensions, such as centralization vs. decentralization and top-down vs. bottom-up change.

One such tension is the fast vs. slow dilemma. Leaders want to be seen as “doing AI,” and doing it fast has become a sign they’re doing it right. But faster isn’t always better. When leaders move quickly but don’t slow down enough to fix systems or understand new tech, a perilous gap can form between decision and implementation.

For an example, Rahman points to findings from his PhD student Jodie Koh on how AI is being introduced to improve access to medical diagnostics.

Training AI requires thousands upon thousands of ultrasound images. But clinicians are taught to minimize the number of images taken of each patient to save time and money. Imaging departments may lack incentives to implement AI tools, Rahman says, and their technicians may be concerned about performance monitoring, increased workloads, or job cuts. So forcing an abrupt AI transition without addressing these hurdles can doom a new project from the very beginning.

The AI framework suggests protecting “slow mode” instead of taking this fast approach. Build speed bumps like checkpoints, incubation periods, and reflection rituals into creative and strategic work. The key is knowing which parts of the process benefit from fast execution and which require the slow thinking and struggle that enable original ideas to reach their potential.

Read more in Harvard Business Review.

How big businesses get bigger

Economic theory predicts that as firms get bigger, it will be difficult for them to grow even larger.

So how have the Golden Arches of McDonald’s and other industry giants like Starbucks, Procter & Gamble, and Coca-Cola grown so much more quickly than competitors and stayed on top for so long?

Kellogg’s Sara Moreira investigated how these companies came to be so huge compared with other firms in the same product category. Through mathematical modeling and an analysis of the consumer-packaged-goods industry, Moreira found that a key factor propelling firms’ growth is standardization: the degree to which a company reuses components, knowledge, and relationships across different product lines and locations.

Take IKEA, which became famous for using similar parts and materials for various types of furniture. Similarly, Starbucks has relied on tried-and-true formulas for floor plans, menus, and barista training to efficiently open more locations.

As a result, standardization practices like these have become a kind of superpower, allowing fast growth and higher responsiveness to increased demand.

“When knowledge, investments, and inputs are potentially scalable, that can allow the firms to become bigger.” By reusing components and previously successful strategies, “it’s less costly to you,” Moreira says.

Read more about mega-firms and growing smaller ones at Kellogg Insight.