AI is already changing management — companies must decide how
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Ethan Mollick is associate professor of management at The Wharton School of the University of Pennsylvania and author of “Co-Intelligence: Living and Working with AI” (WH Allen)
Most companies do not have an artificial intelligence strategy, yet they are already riddled with the technology. A survey published this month by LinkedIn and Microsoft suggested that three-quarters of white-collar workers have used AI for work, and four-fifths of them have done so from their own accounts and devices. They are not seeking the permission of their employers; in fact, they are hiding it from them, because they are afraid of the consequences.
What that means is managers need to stop asking if AI will matter in their organisations and start shaping how it will matter. That is going to introduce a wide range of new challenges that will alter what management means. Our organisational structures are built around the idea that human workers are the only form of intelligence at work. That is no longer true.
For many people in many organisations, their measurable output is words — in emails, reports and presentations. We use words as a proxy for effort, intelligence and care. When a middle manager writes a weekly status report, the report itself may not be the point. Rather, it serves as a signal that the manager has done their job of monitoring the project and making corrections, as needed.
Historically, this has worked well enough. A senior manager could tell at a glance if a report was substantive (showing effort) and well-written (showing quality). But, now, every employee with access to AI tools can produce work that checks all the formal boxes without necessarily representing underlying effort or thought.
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This poses a significant challenge to traditional management practices. If AI can generate reports, emails and presentations that are indistinguishable from human-created content, how can managers assess the true contributions and value of their employees?
In organisations that have become bogged down by bureaucracy, AI can help by automating endless paperwork. However, it will also create underlying questions of why the paperwork exists at all. In addition, once meaningful processes, such as performance reviews, may suffer as managers succumb to the temptation of the “write-it-for-me” button. When faced with AI-written content that replicates their work, some employees may even face a crisis of meaning about the nature and value of their contributions.
The quality of AI writing is already quite good, especially when given source data, so the urge to use it will be ubiquitous. Our research shows that people “fall asleep at the wheel” when faced with “good-enough” AI content. They become less critical, and less likely to fact-check or thoroughly edit the AI’s output.
This can lead to the propagation of errors, misinformation or superficial analysis. As AI-generated content becomes more prevalent, organisations therefore risk a gradual erosion of the depth and quality of their collective work product. Very soon, AI-generated content will be everywhere, in every organisation.
To productively use AI at work, leaders and employees need to reflect on what their work means to others, and to themselves. Thoughtful organisations can find answers, but few seem to be grappling with these issues as AI adoption expands, often under the radar.
On the other side of the crisis, though, lies the possibility of freedom. Surveys repeatedly find that workers like using AI, even while recognising risks to their jobs, because the AI does the work they do not want to do.
Tools such as Microsoft’s Copilot make it easy for anyone to delegate drudge work and to focus on what they enjoy — and what others value — about their contributions. Organisations that embrace this and are willing to cut processes that no longer make sense in an AI-enabled world may find themselves benefiting.
AI may also help managers directly. Its capabilities in empathy, summarisation, and customisation make it a powerful tool for coaching and mentoring. AI can provide personalised feedback, help employees navigate complex situations, and offer guidance tailored to individual needs and learning styles. It can also watch everything an employee does and offer comments.
By leveraging AI in this way, as a coach and mentor, organisations can scale employee development and support it to a degree that was previously impossible — creating freedom from boring tasks along the way. Done wrong, however, it risks creating a panopticon, where employees feel constantly monitored and judged by an all-seeing AI.
So, the new form of management must strike a balance: using AI to empower and support employees while respecting their autonomy and privacy.
A strategic response from managers is imperative. The option to wait is no longer realistic. Nor is deploying the standard approaches of consultants and committees. The challenges and opportunities are much deeper.
By reflecting on the meaning of work and embracing the opportunities while mitigating the risks, organisations can chart a course to a future in which human and machine intelligence combine in powerful new ways.
Organisations that fail to do this will still be AI-powered, but without the human guidance that will help them thrive.
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