Artificial intelligence is changing how companies operate, but Airbnb CEO Brian Chesky believes the biggest workplace risk may not be the technology itself. He has singled out two types of workers he believes could struggle to adapt: managers who only supervise people and employees who resist change.
His warning raises a question for American workers across industries: does staying employable in the AI era mean learning new tools, rethinking traditional management or both? The answer is more nuanced than the headline suggests.
What Brian Chesky actually said about AI and jobs
Chesky shared his views on the Invest Like The Best podcast, arguing that two groups may struggle to make the transition to an AI-driven workplace: “pure people managers” and people who are rigid and unwilling to evolve.
His criticism of traditional management is specific. He is not arguing that companies no longer need leaders. Instead, he questions the value of managers whose work consists largely of meetings, one-to-one conversations and supervising employees without contributing directly to the work itself.
In Chesky’s view, effective leaders should combine people management with practical knowledge of their team’s work. A design leader, for example, should understand design itself rather than simply coordinate designers.
His second concern is resistance to change. As businesses adopt AI tools, workers who refuse to learn how those systems affect their responsibilities could find themselves at a disadvantage.
These are Chesky’s predictions about the future of work, however, not proof that either group is destined to lose its job.
Why middle managers and resistant workers are in the spotlight
AI can increasingly assist with tasks such as summarising documents, preparing reports, analysing information and handling routine administrative work. When those activities account for a substantial part of a role, employers may reconsider how the work is organised.
That could put pressure on some management structures, particularly where several layers of supervision add limited practical value. A manager who understands the product, makes sound decisions and helps a team solve difficult problems offers something different from someone whose role is primarily administrative.
For US employees, the implications extend beyond Silicon Valley. Professionals in finance, marketing, customer service, consulting and operations may all encounter AI-assisted workflows, although the extent of change will vary by employer and occupation.
The second group Chesky identifies — workers unwilling to adapt — faces a different challenge. Even when AI does not replace a job, colleagues who use it effectively may complete certain tasks faster or take on more complex work.
That does not mean every employee must become a programmer or AI specialist. Understanding how to use relevant tools, check their output and recognise their limitations may be more immediately useful for many roles.
What the wider jobs research says
Chesky’s warning comes amid broader evidence that AI is changing employers’ skills requirements, although forecasts do not suggest that all traditional jobs will disappear.
The World Economic Forum’s Future of Jobs Report 2025 found that employers expect technological literacy, AI skills, analytical thinking and adaptability to become increasingly important. The report also highlights the continuing value of leadership, creative thinking and other human skills.
US employment projections offer another important perspective. The Bureau of Labor Statistics expects AI-related technological change to support growth in several occupations, including data science and information security, over its 2024–34 projection period. The effects are expected to differ by occupation, rather than moving every job in the same direction.
The distinction matters: AI may change the tasks people perform without eliminating the entire occupation. Some businesses may reduce hiring or reorganise teams, while others may use the technology to expand their operations.
Common misconceptions about AI and employment
Myth: All managers are at risk.
Chesky’s criticism targets managers who only supervise, not every person responsible for leading a team. Coaching, resolving conflict, setting priorities and making difficult decisions can remain valuable when combined with a strong understanding of the work.
Myth: Workers need advanced technical skills to stay relevant.
Many employees can start by learning a small number of AI tools relevant to their roles. Knowing how to ask useful questions, verify results and protect confidential information can be more practical than trying to master every new platform.
Myth: Adopting AI guarantees job security.
It does not. Employers may still restructure teams, change budgets or reduce roles for reasons unrelated to an individual’s willingness to learn. Adaptability can improve someone’s options, but it cannot guarantee continued employment.
What can American workers do now?
Workers do not need to overhaul their careers overnight. A few practical steps can help them prepare for changes in their industries.
- Identify repetitive tasks. Look for routine research, reporting, scheduling or drafting that AI might help streamline.
- Learn one relevant tool. Start with a task you already understand, then check the output carefully for errors and unsupported claims.
- Build skills AI cannot easily replicate. Develop judgement, communication, problem-solving, relationship-building and subject expertise.
- Managers should stay close to the work. Understand the products, services and decisions their teams handle, rather than relying entirely on status meetings.
- Ask about training. Check whether your employer offers AI guidance, professional development or opportunities to take on new responsibilities.
For further context, workers can consult the US Bureau of Labor Statistics, explore occupational trends and training resources, and review their employer’s policies on approved AI tools and sensitive data.
The bottom line
Brian Chesky’s message is that workers may need to rethink how they contribute as AI becomes more widely used. He believes managers who only supervise and employees who refuse to adapt will struggle most.
That is a warning, not a guarantee of job losses. For American workers, the practical lesson is to combine relevant AI skills with experience, judgement and the ability to work effectively with other people.
