Owning What You Don’t Know Is The Leadership Skill That Defines The AI Era
It's okay to say I don't know. Leaders are so afraid to say that, because they feel they have to have all the answers.
Edie Goldberg
Founder & President
E. L. Goldberg & Associates
AI is reshaping what work requires faster than companies can re-plan around it. The skills a business will need next year may not be represented anywhere on its payroll today, so workforce planning now means tracking which skills a company has, which it’s missing, and where the work is headed. Whether employees embrace AI or resist it depends on how leaders discuss the shift and whether their teams trust them.
That trust problem is where Edie Goldberg, Ph.D., spends most of her time. She is the Founder and President of E. L. Goldberg & Associates, a talent strategy firm that helps companies transform how they operate to better meet the needs of the changing nature of work and workers. Before starting the firm, she was a Global Thought Leader in the Human Capital Practice at Towers Perrin. She is the co-author of The Inside Gig, a book on moving talent across internal boundaries, and Performance Enablement, a new model for driving organizational performance. She also served as the Chair of the Board of Directors for the SHRM Foundation. Her read on what trips up most AI transitions starts with how leaders handle their own uncertainty.
“It’s okay to say I don’t know. Leaders are so afraid to say that, because they feel they have to have all the answers,” Goldberg says. The pace of AI change makes certainty impossible, yet most leaders still feel pressure to project it. Admitting the limits of what anyone knows right now does more to hold a team’s trust than confidence that later falls apart.
Change as opportunity
How leaders talk about change shapes how employees receive it, well before any rollout begins. Goldberg watches companies treat every shift as a heavy lift, narrating each one as another disruption to absorb. The more adaptable organizations describe change as a chance to get ahead, and that language alone lowers the resistance their teams bring to it.
“Companies that are really successful in being more agile as an organization talk about change as an opportunity. It’s a mindset. We’re evolving because that’s what’s going to put us ahead,” Goldberg says. That framing gets tested hardest around AI. Skills matter, but they only go so far without the mindset to use them, and leaders who want their teams ready for AI have to build both the appetite for the shift and the capability behind it.
Faster isn’t better
Goldberg’s bigger concern is what companies optimize for once AI is in the building. Many leaders focus on squeezing out hourly productivity or quick cost savings, and stop short of reworking how the job gets done. Optimizing for speed produces incremental savings, while rebuilding the work itself can open the door to new products and adjacent markets.
“The biggest mistake companies are making right now is trying to chase productivity as opposed to work optimization,” Goldberg says. BambooHR’s State of the Workforce 2026 report finds that 81% of leaders believe productivity rose over the past year, while 85% of employees report significant workplace stress. The report calls that disconnect dignity debt, the price companies pay when they treat people as a means to output and roll out AI without rebuilding the work around it.
Some of that debt traces to how leaders explain their decisions. The report also finds that 39% of companies reduced headcount over the past year as AI took on work people used to do. Goldberg’s view is that the reasoning behind some of those cuts gets blurred, with the technology credited for reductions that owe more to over-hiring or the cost of AI itself. Employees tend to sense the gap between the explanation and the reality, and that erodes trust in leadership. “It’s creating more fear in the employee population, which I would argue is going to long-term hurt their organization,” she says.
Klarna’s learning journey
No company gets AI right on the first try, and Goldberg treats that as the starting assumption. She describes adoption as a learning process, one where the first plan rarely survives contact with reality and leaders have to be willing to back up and rethink it.
“We’re all on this learning journey that nobody’s going to get it right out of the gate, and you’ve got to be willing to back up and rethink what you’ve tried,” Goldberg says. Klarna offers a public version of that lesson. A month after launching its OpenAI-built customer service assistant in early 2024, the Swedish fintech said the tool was handling the work of 700 full-time agents. Its headcount fell from 5,527 employees at the end of 2022 to 3,422 by the end of 2024, a drop of roughly 40% that the chief executive credited to AI and a hiring freeze. By 2025, he acknowledged the all-in approach to customer service had produced lower-quality work, and the company began rehiring agents into a model where AI handles routine queries, and people take the cases that need empathy and judgment.
“It’s a beautiful story of figuring out that their first strategy was wrong, and now they have moved in a different direction. And now the company is seeing a much better outcome for their customers,” she says. For Goldberg, it comes back to how leaders treat the people living through the change. “Employees are an important source of information, and companies really need to make sure that they’re leveraging their intelligence and their experience in this journey.”
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Edie Goldberg
E. L. Goldberg & Associates
Founder & President
Founder & President
AI is reshaping what work requires faster than companies can re-plan around it. The skills a business will need next year may not be represented anywhere on its payroll today, so workforce planning now means tracking which skills a company has, which it’s missing, and where the work is headed. Whether employees embrace AI or resist it depends on how leaders discuss the shift and whether their teams trust them.
That trust problem is where Edie Goldberg, Ph.D., spends most of her time. She is the Founder and President of E. L. Goldberg & Associates, a talent strategy firm that helps companies transform how they operate to better meet the needs of the changing nature of work and workers. Before starting the firm, she was a Global Thought Leader in the Human Capital Practice at Towers Perrin. She is the co-author of The Inside Gig, a book on moving talent across internal boundaries, and Performance Enablement, a new model for driving organizational performance. She also served as the Chair of the Board of Directors for the SHRM Foundation. Her read on what trips up most AI transitions starts with how leaders handle their own uncertainty.
“It’s okay to say I don’t know. Leaders are so afraid to say that, because they feel they have to have all the answers,” Goldberg says. The pace of AI change makes certainty impossible, yet most leaders still feel pressure to project it. Admitting the limits of what anyone knows right now does more to hold a team’s trust than confidence that later falls apart.
Change as opportunity
How leaders talk about change shapes how employees receive it, well before any rollout begins. Goldberg watches companies treat every shift as a heavy lift, narrating each one as another disruption to absorb. The more adaptable organizations describe change as a chance to get ahead, and that language alone lowers the resistance their teams bring to it.
“Companies that are really successful in being more agile as an organization talk about change as an opportunity. It’s a mindset. We’re evolving because that’s what’s going to put us ahead,” Goldberg says. That framing gets tested hardest around AI. Skills matter, but they only go so far without the mindset to use them, and leaders who want their teams ready for AI have to build both the appetite for the shift and the capability behind it.
Faster isn’t better
Goldberg’s bigger concern is what companies optimize for once AI is in the building. Many leaders focus on squeezing out hourly productivity or quick cost savings, and stop short of reworking how the job gets done. Optimizing for speed produces incremental savings, while rebuilding the work itself can open the door to new products and adjacent markets.
“The biggest mistake companies are making right now is trying to chase productivity as opposed to work optimization,” Goldberg says. BambooHR’s State of the Workforce 2026 report finds that 81% of leaders believe productivity rose over the past year, while 85% of employees report significant workplace stress. The report calls that disconnect dignity debt, the price companies pay when they treat people as a means to output and roll out AI without rebuilding the work around it.
Some of that debt traces to how leaders explain their decisions. The report also finds that 39% of companies reduced headcount over the past year as AI took on work people used to do. Goldberg’s view is that the reasoning behind some of those cuts gets blurred, with the technology credited for reductions that owe more to over-hiring or the cost of AI itself. Employees tend to sense the gap between the explanation and the reality, and that erodes trust in leadership. “It’s creating more fear in the employee population, which I would argue is going to long-term hurt their organization,” she says.
Klarna’s learning journey
No company gets AI right on the first try, and Goldberg treats that as the starting assumption. She describes adoption as a learning process, one where the first plan rarely survives contact with reality and leaders have to be willing to back up and rethink it.
“We’re all on this learning journey that nobody’s going to get it right out of the gate, and you’ve got to be willing to back up and rethink what you’ve tried,” Goldberg says. Klarna offers a public version of that lesson. A month after launching its OpenAI-built customer service assistant in early 2024, the Swedish fintech said the tool was handling the work of 700 full-time agents. Its headcount fell from 5,527 employees at the end of 2022 to 3,422 by the end of 2024, a drop of roughly 40% that the chief executive credited to AI and a hiring freeze. By 2025, he acknowledged the all-in approach to customer service had produced lower-quality work, and the company began rehiring agents into a model where AI handles routine queries, and people take the cases that need empathy and judgment.
“It’s a beautiful story of figuring out that their first strategy was wrong, and now they have moved in a different direction. And now the company is seeing a much better outcome for their customers,” she says. For Goldberg, it comes back to how leaders treat the people living through the change. “Employees are an important source of information, and companies really need to make sure that they’re leveraging their intelligence and their experience in this journey.”