"AI hype is following a well-worn path. During the dot-com boom, we were promised the internet would bring an overnight revolution. While it was revolutionary, some changes arrived quickly, but most unfolded over years, marked as much by failures and false starts as by lasting breakthroughs. I was at Inbound in San Francisco last week, and the AI hype was overwhelming. Conversations were either focused solely on the tactical use of AI or, interestingly, on reframing AI in our minds."
"AI as the new OS AI is quickly becoming the infrastructure layer of modern business. In his keynote, Dario Amodei, CEO of Anthropic, called it an operating system, much like cloud computing. Adoption isn't theoretical anymore. Usage is widespread across roles and industries. In pharma, legal and manufacturing, AI reduces friction at a scale humans can't match. For example, innovative manufacturers now use AI to detect user context to serve different experiences automatically and are accelerating their use of AI to mine for insights."
"AI is powerful, but curiosity makes it valuable. AI provides scale, but curiosity provides depth. Aravind Srinivas, CEO of Perplexity, reminded us that progress often begins with the questions nobody dares to ask. Eric Bailey, president of Bailey Strategic Innovation Group, pushed further, showing how our brains trick us with certainty when what we need instead is professional not-knowing, a disciplined willingness to lead through"
AI adoption follows a pattern of intense hype followed by gradual, uneven transformation and many failures alongside breakthroughs. AI is evolving into the infrastructure layer of modern business and is now widely used across roles and industries. Sectors such as pharma, legal, and manufacturing use AI to reduce friction, detect user context, and accelerate insight mining. Generative assistants accelerate code and content creation through automated drafting and suggestions, but impressive demos do not always translate to reliable real-world features. Reliable foundations are required for AI to be transformative, and disciplined curiosity and professional not-knowing add depth to AI's scale.
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