Bausch & Lomb CEO: AI hype echoes past tech cycles — what matters is people

The Bausch & Lomb CEO opens with a claim that current AI discussions treat technological change as unprecedented, when in fact every generation has experienced similar cycles. Companies rush to acquire new systems, hire specialists, and announce transformation plans — but they often confuse adopting technology with having a strategy. The CEO draws a parallel: when new technologies have arrived in the past, companies invest heavily, reorganize around them, and assume early adoption will create lasting advantage. Over time, however, competitors acquire the same capabilities, and revolutionary features become standard. The underlying lesson, he argues, is that technology alone does not create lasting competitive advantage; people and organizations that learn faster do. AI may be more powerful and faster-moving than previous technologies, but the business logic remains unchanged.

The CEO acknowledges the scale of AI's potential impact but emphasizes that the real competitive battle will not be decided by which models companies choose or how quickly they deploy them. Instead, it will hinge on whether an organization's people are prepared to keep learning as the technology changes. He contrasts this with the current corporate focus on evaluating models, comparing vendors, and deploying tools — activities that matter but are unlikely to determine ultimate success. Bausch & Lomb's response has been to invest in building a culture of continuous learning rather than simply purchasing the latest technology. Last year, the company partnered with Coursera to launch an enterprise-wide AI learning program and made the courses mandatory for knowledge workers, despite understanding that mandatory training is not always welcomed and that completing a course does not make someone an AI expert. The CEO justified this decision by noting that if AI is going to affect nearly every business function, giving people a foundation for understanding and using it should not be optional.

Beyond training, the company launched a VisionAI Challenge that invited colleagues across the company — not just AI experts — to identify practical ways AI could improve operations. The CEO notes that ideas came from manufacturing, R&D, commercial operations, finance, HR, and other parts of the business, ranging from ambitious initiatives to small, persistent problems that consume time. While the smaller ideas may not make headlines, the CEO observes that collectively they can make a company faster and more effective. This experience reinforced a broader principle: people closest to the work often have the clearest view of how it can be improved, and the challenge for leaders is to give them the knowledge, permission, and opportunity to act. The company also created AI in Action, a platform where colleagues share practical examples of how they are using AI to solve problems, eliminate repetitive work, and improve customer service. Some examples save dozens of hours each month; others save one or two hours. The CEO emphasizes that all have value, especially when one person's solution gives someone elsewhere in the company a better way to approach a similar problem.

The CEO concludes by reframing the role of leadership in the AI era. For years, leaders were expected to have the answers; increasingly, the responsibility is to create an environment where people ask better questions, set clear expectations and guardrails, and remain comfortable acknowledging uncertainty about where the technology will lead. Companies that treat transformation as something directed from the center — with a small group selecting technology and telling the rest of the organization how to use it — often find that lasting change does not happen. Instead, the companies that benefit most from AI will equip people throughout the organization to experiment responsibly, share what they learn, and help others improve. The CEO predicts that the current AI frenzy will subside, as it has with other technology waves, and AI will become more embedded, familiar, and widely available. When that happens, advantage will not belong to the company that was first to buy the latest technology, but to the company whose people kept learning how to use it.