Coinbase just cut 700 people and called it an AI transformation.
Read the financial results before accepting that framing. Q1 revenue down 26% year-on-year. Consumer trading volumes at an 18-month low. Bitcoin had its worst quarter since 2018. Mizuho’s own analyst described the crypto winter as the primary driver, with AI serving as “a convenient framing.”
I do not doubt that Coinbase is genuinely restructuring around AI. But when you dress up market-driven cuts in an AI narrative, you are not just spinning investors. You are feeding a story that millions of people are already afraid of: that AI is coming for their jobs, indiscriminately and inevitably. And the people best positioned to correct that story are largely silent.
That silence is the real problem.
The Narrative Vacuum That Displacement Fills
There is a reason the displacement story wins the headline every time. It is emotionally compelling, it confirms pre-existing fears, and it is easy to dramatise. “Company cuts 700 jobs, blames AI” is a story. “Company restructures around AI and creates new roles in engineering and product” is not a story, even when it is true.
The augmentation story is harder to tell because it is slower, more diffuse, and requires the audience to hold complexity. It does not have a single dramatic event to anchor it. It lives in the accumulation of small changes to how work actually gets done, and those changes are hard to communicate without either sounding defensive or slipping into corporate uplift.
But the absence of that story is not neutral. It is being filled by the default narrative, and the default narrative is fear.
What Augmentation Actually Looks Like
The evidence for AI as a genuine augmentation force exists. It is documented, measurable, and happens in industries people care about. The challenge is that it almost never makes the news.
Cisco saved 1,500 engineering hours a month using OpenAI Codex. Engineers were not replaced. They shifted to reviewing, directing, and doing the architectural work that machines cannot do. Acentra Health deployed AI scribing tools for nurses and cut documentation time by 50%, saving 11,000 hours across six months. Not one nurse was replaced. Stadler, a 230-year-old Swiss manufacturer, gave 650 employees AI tools and watched output on knowledge tasks double. The workers are still there, less buried in admin, faster at the work that required human judgment.
These are not edge cases or cherry-picked examples. They represent a pattern that is playing out across industries, at scale, in organisations that are doing the implementation work properly.
The problem is the communication work is not being done at the same scale.
Who Is Responsible for Telling This Story
This is where I want to name something that does not get said clearly enough in the AI policy conversation: the AI Labs have a communication responsibility they are largely not meeting.
OpenAI, Anthropic, Google DeepMind. These organisations have reach, credibility, and access to the data that would support a sustained public narrative about what AI actually does to work. Not a press release when a product launches. A roadmap. Ongoing, specific, industry-grounded communication about where AI is creating capacity, which roles are gaining value as a result, and what the realistic trajectory of change looks like for someone working in a given field.
The displacement story is winning by default because the augmentation story requires sustained effort. It requires naming real organisations, real roles, and real numbers. It requires being willing to share context that is commercially sensitive. It requires treating the public conversation about work and AI as a strategic responsibility, not a communications problem to be managed reactively.
None of that is easy. But the alternative is allowing every poorly framed restructuring announcement to accumulate into a public consensus that AI is primarily a job elimination tool, and watching that consensus become self-reinforcing as it shapes policy, talent decisions, and institutional behaviour.
The Leadership Dimension
For executives leading organisations through AI transformation, the communication question is not optional. It is a core part of the leadership job.
The leaders who will build durable trust with their teams, their boards, and their external stakeholders during this period are not the ones who communicate least about AI to avoid controversy. They are the ones who commit to a consistent narrative: here is what we are doing, here is why, here is what it means for roles and careers, and here is what we are doing to support the people whose work is changing.
That narrative does not have to be perfect. It has to be honest and sustained. A single town hall followed by silence is not a communication strategy. A quarterly update without specifics is not a communication strategy. A communication strategy is a deliberate, ongoing effort to help the people inside and around your organisation make sense of change that is real, significant, and moving faster than most of them expected.
The disruption is real. The anxiety is real. But the story being told right now is the wrong one, and it is being told by default because the right story requires more effort than a quarterly earnings call.
If your AI strategy does not include a communication strategy, you only have half a strategy.