This article is based on the Allwork.Space Future of Work Podcast episode Charlene Li On Winning With AI & Leadership | Future of Work Podcast. Watch or listen to the full episode.
Companies are racing to figure out what AI can do, while some are skipping the more important question: What are we actually trying to accomplish? That disconnect can turn AI into a cost-cutting exercise instead of a tool for building something better.
We explored that problem with Charlene Li on The Future of Work® Podcast. Li is a business transformation and disruptive leadership expert, founder of Quantum Networks Group and the founder of Altimeter Group. A New York Times bestselling author of seven books, she has advised 49 Fortune 100 companies.
AI Should Serve the Strategy
Organizations get into trouble when AI becomes the strategy instead of serving one, Li said on our podcast.
The same technology can produce very different outcomes depending on how leaders use it. A company focused on reducing headcount may see AI as a way to do the same amount of work with fewer people. A company focused on growth may use those same capabilities to give employees more capacity, develop new services or pursue work that was previously impossible.
Li described speaking with a professional services firm that grew 87% in one year without increasing headcount, attributing that growth to AI. She also pointed to call centers using AI to eliminate routine administrative work while giving employees more time with customers. One such company expected to increase its headcount by 5% over two years. The difference is the question that leaders ask of the technology.
The Headcount Trap
Li describes using AI primarily to reduce headcount as a scarcity mindset. She recalled a CFO asking whether making one employee 10 times more productive meant a company could eliminate the other nine. Her counterquestion was what could happen if all 10 employees became 10 times more capable.
Making existing employees dramatically more capable allows companies to use the additional capacity to pursue new opportunities. That requires leaders to recognize what people bring that AI does not automatically provide, including judgment, expertise, curiosity, empathy, intuition and organizational knowledge.
It also changes how companies should think about AI training. Li says organizations often focus heavily on the mechanics of using AI, while giving less attention to helping employees apply their own judgment and expertise when working with it.
Leadership Has to Catch Up
For Li, the biggest AI skill is curiosity. That applies to leaders as much as employees. Rather than assuming AI is the answer, leaders need to identify the actual problem first and then determine whether AI can help solve it. That makes asking good questions increasingly important. AI can produce answers quickly, but those answers are only useful when leaders understand what problem they are trying to solve.
Li also rejects the idea that this is primarily a generational issue. Her research on disruptive leadership found little difference between generations in their willingness to think beyond the status quo. People can develop very different leadership styles based on what they have experienced and what they have seen work.
Four Things Companies Need Before They Scale AI
Li’s framework for becoming AI-ready centers on four areas: mindset, skill set, toolset and decision set.
Mindset means creating a culture that is ready to work with AI rather than declaring the company AI-first.
Skill set means helping employees become fluent in using AI responsibly and applying judgment to their work, rather than simply teaching technical prompts.
Toolset means building technology that can be updated as AI capabilities change.
Decision set means establishing enough governance to keep AI use safe without creating so much bureaucracy that employees cannot move.
The goal is to give people enough structure to experiment responsibly while allowing that structure to become lighter as employees gain experience.
AI Could Help People Understand Each Other
Li sees another potential use for AI that receives far less attention: helping people communicate across differences. She described an organization where teams from different departments were struggling to understand each other’s priorities. AI was used to turn the same meetings into different summaries tailored to each group’s responsibilities, concerns and priorities.
The technology helped people recognize that they were often pursuing similar goals while using different language and focusing on different details. That points to a less obvious role for AI in the workplace: beyond automating tasks, it could help people understand intent across departments, generations and communication styles.
Start With the Future, Then Bring in AI
Li’s approach comes down to three questions leaders should be able to answer: Where is the organization going? How will it get there? And what is each person’s role in making that happen?
AI comes after those decisions.
When companies start with their purpose, customers, strategy and people, they can determine where AI actually belongs. When they start with the technology, they risk forcing the organization to serve the tool.
For Li, that distinction will determine whether AI becomes another efficiency initiative or a catalyst for what the organization can do next.
