Sugarcoating the AI Future Is a Trust Problem

On October 4, 2026, 60 Minutes aired a report on AI and the future of work that carries a lesson about trust for every leader.

There are two reliable ways to lose people's trust during a period of change. One is to tell them nothing. The other is to tell them a story that keeps changing.

Both came up in the report. The segment noted that for a time, AI companies spoke openly about technology that could make much of today's work obsolete. More recently the tone has softened. In June, OpenAI's Sam Altman said the industry had underestimated how much people would remain at the center of an economy built around people.

Clara Shih, who led AI divisions at Salesforce and Meta before founding a nonprofit for young workers, was skeptical of the shift. AI labs, she said, have every incentive to sell what they are doing to the public, and she doubts they truly believe AI will not hurt jobs. Her advice was simple: be honest with people about the risks, and do not sugarcoat a utopia that may arrive only after a great deal of hurt.

I am in no position to judge what any executive privately believes. But Shih's point applies to every leader, not only to AI companies. Nearly three-fourths of Americans now fear AI is coming for their jobs, according to Pew Research Center findings cited in the report. When people are that anxious, how leaders talk about the future becomes part of the future.

People Can Handle Hard News

In my years advising organizations through change, I have watched leaders underestimate their people again and again. They worry that honesty will cause panic, so they soften the message. The effect is usually the opposite.

People can handle hard news. What they struggle with is a story that shifts every quarter, or a message that does not match what they see around them. When the official language says nothing will change and the work is clearly changing, people stop listening to the language and start reading the signals. They update their résumés. They stop volunteering ideas. They protect themselves.

That is the real cost of sugarcoating. Fear doesn't go away. It goes underground, where leaders can no longer see it or address it.

Honesty Is a Practice, Not a Speech

Being honest about AI is less about predicting doom than about telling people three things: what you know, what you don't know yet and what you are committed to.

In practice, it sounds something like this.

• What we know: AI will change how much of our work gets done, starting with routine research, drafting and analysis.
• What we don't know yet: exactly which roles will change most, and how quickly.
• What we are committed to: telling you as soon as we know more, investing in your development and involving you in redesigning the work.

That message is harder to deliver than a reassuring slogan. It is also far more likely to keep your best people engaged, because it treats them as adults who deserve the truth and as partners who can help shape what comes next.

Where Trust Is Actually Built

Shih knows this cycle personally. Her family came to the United States from Hong Kong in the 1980s and settled in Ohio as globalization hollowed out factories and neighborhoods. She told 60 Minutes that the first lesson from that era is to be honest with people about what the risks are.

When change comes without honesty, the damage is not only economic. Shih named it in the segment: job loss reaches people's sense of self-worth and the fabric of their communities. Leaders cannot prevent every disruption. They can decide whether people face it with information or with rumors.

Trust gets built in small moments. A team meeting where a manager admits a role is likely to change. A conversation where a leader asks people what worries them and actually listens. The follow-through, when a promise to reskill people turns into a real budget and a real schedule. As I wrote in Why People Wait Until They Leave to Tell the Truth, cultures that make honesty expensive end up hearing the truth only at the exit. And as I argued in my commentary on the segment, AI Can Learn Your Expertise. It Can't Learn Who You Are., being straight with people is the first thing leaders owe them.

Read Your Message Back Before You Send It

Before your next all-hands or team meeting about AI, read your message back and ask whether you would believe it if you were sitting in the audience. If the answer is no, rewrite it.

Name the risk. Share the plan. Admit what you are still figuring out. Then invite people into the work of redesigning their own jobs, because they understand that work better than anyone.

The future of AI at work is uncertain. Your credibility doesn't have to be.

Want to explore these ideas further? Learn more about my work on leadership, identity and conviction at www.theglennllopis.com.