We had a printer for years that could do one thing nothing else could: print directly onto CDs and DVDs. I even bought the special discs, a whole shelf of them, ready for the day I might make another video to share with family or friends. When the printer started to fail, I hesitated to replace it. How would I print on the discs without that tray?
Then I realized I no longer have a drive that burns DVDs. My kids do not own anything that plays them. Everything they do, movies, music, photos, they stream.
What I thought I was protecting was capability. What I was really clinging to was an era. The printer still worked. The world around it had moved on. Once I accepted that, I could see the absurdity clearly: a shelf of blank media, a printer I no longer needed, and a tray attachment for a format no one uses. Letting them go was a small act of progress. The ecosystem that once supported that creativity had quietly expired, and something new had already taken its place without me noticing.
This Pattern Has a Name
In AI in Context, I wrote about how every technology finds its meaning in how we use it. This is the next layer of that idea. Not just context but consequence. What happens when the tools that once defined our work outlive their purpose?
Economists have a name for this. In the 1940s, Joseph Schumpeter described it as creative destruction: new ideas and technologies dismantle existing systems to make space for better ones. Schumpeter understood that innovation does not just reshape markets; it reshapes the workforce. When one kind of work disappears, another takes its place. Roles evolve, new skills develop, and value migrates. The headlines frame this as loss, humans replaced by machines, but what is really happening is a transfer of energy from the repetitive to the creative.
I have lived that pattern many times, not as theory but as practice.
The Parts That Evolved, Not Disappeared
Throughout my career, parts of my work have been automated, replaced, or rewritten by new technology. Every time, it felt unsettling at first. A familiar process disappeared, a system I knew by heart became irrelevant overnight. Yet each time, something new emerged in its place, often something more creative, more analytical, or more strategic. My role did not vanish. It evolved.
Early in my IT work, one principle stuck with me: you have to understand the manual process before you can automate it. Otherwise you are just moving mistakes faster. I still think about that now. I will not automate something I do once every few years; I will document it, because by the time I need it again the technology will have changed anyway. But I will automate what happens every day, because repetition is where efficiency belongs and where human attention is wasted.
A colleague of mine lived this in a different way. Her job did not shrink when her team adopted new data tools. It deepened. She could focus on the valuable work, the analysis, the insight, the storytelling, because she no longer spent hours wrangling data into shape. The time she gained was not idle. It was reinvested in understanding.
When the Pace Gets Punishing
The principle holds. But it carries a human cost when creation cannot keep pace with destruction.
Technology was already accelerating before AI arrived. AI made the speed visible. What once unfolded over a generation now happens within a single product cycle. Futurists like Ray Kurzweil have argued for decades that we are entering an acceleration curve steep enough to feel discontinuous, where the next decade looks nothing like the last. The discomfort we feel right now is not fragility. It is physics.
In some places, AI is removing inefficiencies that should have been retired long ago. In others, it is cutting into work that carried quiet value: the mentorship embedded in routine, the intuition built through repetition, the thinking time hidden inside the doing. When those layers disappear too quickly, the learning that prepared people for the next step can vanish with them. Progress without perspective is not evolution. It is acceleration for its own sake. We cannot slow the technology, but we can choose how deliberately we move alongside it.
From Destruction to Curation
That is the shift I keep coming back to. Creative destruction clears the ground. But curation decides what grows there.
In my own work, AI has made me stop and ask questions I did not used to ask. Which steps in this process genuinely need a human? Where does my judgment make the difference? What do I gain when I delegate a task to a tool, and what do I quietly lose? Those are not rhetorical questions. They have changed how I design my workflows.
I am learning that curation is not a one-time decision. It is a rhythm. In the same way I pause between stages of an AI project to evaluate what the model has produced before moving forward, every workflow needs moments where a human stops, thinks, and steers. The system does not always signal when it needs that. We have to build the pause in ourselves.
Curated creation means progress with stewardship. It is the act of protecting the parts of work that make it meaningful, the thinking, the decision-making, the human connection, even as we embrace tools that make it faster. That is the human counterbalance to automation. Not resistance. Intention.
The Fear Worth Keeping
Fear is healthy until it paralyzes. It is what makes us pause long enough to think before we leap, to question what is at stake and why it matters. The fear I felt about the printer was useful for about five minutes. Then it became a shelf of blank DVDs I was never going to use.
The fear around AI is worth sitting with a little longer, because the stakes are larger. But the same logic applies. Fear was never meant to be a finish line. The moment it keeps us from engaging, it stops protecting us and starts limiting us.
When I look back at every moment I thought a technology might outpace me, the pattern is clear. Each wave demanded something new: new questions, new structure, new perspective. What I lost in routine, I gained in flexibility. What automation took from repetition, it gave back in possibility.
AI is not rewriting what it means to be human. It is rewriting the conditions that reveal it. The work we do next will not be measured only by what we produce, but by how well we protect the parts that make that production thoughtful.
Progress will keep rewriting the tools. Our work is to keep rewriting the meaning. That is what keeps technology human.
And if you are wondering what that looks like in practice, I get into it in Defining Wins in the Age of AI.