In 1838, a French painter saw one of the first photographs ever made and declared that “from today, painting is dead.” Nearly two centuries later, Microsoft’s vice chair and president Brad Smith is using that same story to make a point about artificial intelligence, work, and why this generation of graduates is right to be skeptical — but not fatalistic — about where AI is heading.
In a new blog post, Smith argues that AI sits in a long line of “general purpose” technologies that initially spark fear, disrupt jobs, and then eventually expand what people can do instead of replacing them outright. He points to the camera’s impact on art as an early example: portrait painting collapsed for a while, but the tech shock helped drive Impressionism, Cubism, Surrealism, and an explosion of new styles that made painting more, not less, relevant. In his telling, AI is on track to play a similar role for both creativity and the job market — if we handle it correctly.
Smith’s piece arrives at a moment when the next generation is pushing back on the AI boom in very public ways. At recent US college graduations, mentions of AI sometimes drew boos, not applause. On one level, that’s surprising: young adults and college towns are actually among the fastest adopters of AI tools, according to Microsoft’s own research. On another level, it’s a warning sign from the group that usually embraces new tech first.
Microsoft’s Brad Smith: A message from students: “not so fast”
Smith spends a big chunk of the post on what he sees as a wake‑up call from this year’s graduates. Even as they use AI, many don’t like how it’s showing up in their lives, and they want a say in what happens next. On campus, that pushback has been visible in small but symbolic ways. At Princeton, for example, seniors recently rejected a class “beer jacket” design because it had been created with the help of AI, opting instead for jackets marked “100 percent cotton” and “100 percent human.”
For Smith, that kind of decision says a lot about how culture and taste shape the real economy. Efficiency alone doesn’t decide what wins; people do. Students aren’t rejecting AI across the board — they know it can be useful and powerful — but they want to keep it in what they see as its proper place. They want humans deciding what machines do, not the other way around, and they want those decisions made with input from a broad community, not just a handful of tech executives.
He ties this to a bigger point about the “American Dream.” It has always been about economic opportunity, he says, but also about the dignity of work and the sense of purpose it provides. That’s why talk of a future where computers replace most jobs feels so threatening. To tech leaders who seem comfortable chasing that vision, Smith says graduates are sending a clear reply: “not so fast.”
Tech changes fast. People adapt slower — and better.
Microsoft president and vice-chair Brad Smith has spent nearly four decades in and around the tech sector, from law firm associate to Microsoft’s top lawyer to one of the company’s most public-facing executives. Over that time, he says he has watched technologists make the same two mistakes over and over: overestimating how quickly new technologies will reshape everything, and underestimating how well people adapt and find new ways to use them.
To put AI in context, he leans on economic history. AI is what economists call a “general purpose technology” — something like electricity, ironworking, or digital computing that spreads across industries and rewires the economy over decades, not months. Yes, AI will automate some jobs, create new ones, and change the way many roles work. But diffusion takes time, and the limiting factor is rarely the tech itself. It’s people: how fast individuals, organizations, and institutions can change.
Smith points to early usage data to make that clear. Even amid the hype, Microsoft’s internal research estimates that less than a third of the US working-age population is currently using generative AI, and the global figure is significantly lower. Initial adoption curves don’t instantly translate into deep transformation across every job or sector. Borrowing a line from legendary UCLA coach John Wooden, Smith’s advice is to “be quick, but don’t hurry” — move decisively on AI, but resist panic and shortcuts that create new problems.
What individuals can actually do with AI
Zooming in from the big picture, Smith lays out a pretty practical framework for how workers can think about AI without being overwhelmed by it. His core view: AI is at its best when it amplifies human capability, not when it tries to replace it. He highlights examples from Microsoft’s AI for Good Lab — firefighters spotting wildfires faster, legal advocates extending help to women without access to lawyers, teams in Ukraine locating landmines, and conservation groups helping farmers improve yields — as early proof that AI can make specialized human expertise go further.
He then draws on ideas from the book “Open to Work: How to Get Ahead in the Age of AI,” written by LinkedIn executives Ryan Roslansky and Aneesh Raman. Their first suggestion is to stop thinking of your job as a single title and start seeing it as a bundle of tasks. Once you do that, you can sort those tasks into three buckets:
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Tasks AI can do on its own
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Tasks you can do better with AI
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Tasks only humans can (or should) do
If almost everything you do lands in the first bucket, that’s a warning sign — time to shift toward different work. For most people, though, the second and third buckets should dominate. The goal becomes clear: offload what you can to AI, then double down on the uniquely human parts and the areas where AI makes you more effective.
That leads to their second key point: soft skills matter more, not less, in an AI‑heavy world. Smith highlights five “C” skills — curiosity, creativity, compassion, communication, and courage — as areas where humans still have a decisive edge. Even when AI handles more tasks, humans still need to oversee, interpret, and ultimately own the decisions. Human judgment doesn’t go away; it becomes more important.
When people ask what they should study, Smith’s answer is stubbornly traditional: pursue a field you’re passionate about, work to master it, and layer in AI fluency on top so you can apply that expertise in new ways. The future will not be easy, he admits, but that combination — deep domain knowledge plus AI skills — is one of the most resilient bets you can make.
Why companies need “hill‑climbing” AI, not just big models
The same logic, Brad Smith argues, applies to companies and institutions. AI should reinforce their unique strengths — the hard‑won expertise about products, processes, and customers — rather than hollowing them out. He sketches a model where organizations move beyond generic, chat‑based assistants and start building AI systems that combine multiple models with their own internal data and knowledge.
In that setup, AI becomes a “hill‑climbing machine”: a system that organizations constantly evaluate, tune, and improve using tools that measure how well it performs on specific tasks. Instead of just consuming whatever the latest frontier model provides, companies keep their own AI on a steady upward slope, aligned with their goals and powered by their proprietary data.
That’s not just a performance story; it’s also about control. If companies simply pour their unique knowledge into someone else’s model without guardrails, they risk giving away the very expertise that makes them competitive. In Smith’s view, that’s why every firm — and, at a larger scale, every country — needs to build its own internal AI capabilities, guard its data, and protect both sovereignty and privacy.
AI, work, and a broader social bargain
Brad Smith closes by widening the frame again. If AI really is as transformative as he and many others expect, then it demands a bigger, more inclusive public conversation about work, education, and who benefits from the next wave of change. Previous tech shifts have left too many people behind, and he argues that the stakes are too high to repeat that pattern.
Brad Smith calls for a “big tent” approach that includes not just tech companies and governments but also labor unions, nonprofits, faith communities, students, and workers themselves — the people who actually experience how workplaces run day to day. The quote he chooses to emphasize, from AFL‑CIO president Liz Shuler, is blunt: “Who knows best how workplaces function and how work gets done than people who work for a living?”
For Microsoft’s part, Brad Smith frames the company’s business model as tightly bound to workers’ fortunes. If people don’t have meaningful work, he says, Microsoft doesn’t have a business. He points to earlier waves of worry around word processors, spreadsheets, and email — and the way each ultimately led to more complex work, more communication, and new industries, rather than the collapse of white‑collar jobs.
The difference now is the intensity of the concern, especially from younger people who have already lived through a pandemic, a chaotic social media era, and an uncertain economy. When they boo AI at graduation, Smith argues, they’re not rejecting technology itself; they’re demanding that the people building it raise the bar. His message back is both cautionary and encouraging: this generation has every reason to be wary, but they’re also unusually well equipped to shape what happens next — if they lean into their agency, ambition, and sense of dignity in work.
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