When AI Becomes the Boss’s Best Friend and Worst Enemy
How AI May Amplify the Dark Side of Management
Imagine a workplace where your daily performance is driven not just by your team leader’s mood—but by invisible algorithms quietly measuring your every move, your next task selected by a machine, your mistakes logged, and your future trajectory defined by a spreadsheet. That future is nearer than you might think. In his recent piece for Bloomberg Opinion, business columnist Adrian Wooldridge argues exactly that: artificial intelligence (AI) isn’t just changing management—it may well be magnifying the worst of it. (bloomberg.com)
Here’s a deep dive into what’s at stake, why it matters, and what leaders and workers should watch for.
The core argument: AI, management and the worst instincts
Wooldridge asserts that AI in management doesn’t automatically lead to more enlightened decisions or more empowered employees. On the contrary, if deployed poorly, it can reinforce three troubling trends:
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Centralised control and micromanagement AI systems make it easier than ever for top management to track and measure everything. As Wooldridge writes: “The more the smart machines take over, the more skills atrophy and self‑direction withers.” (bloomberg.com) So rather than freeing humans to be creative, AI can tighten the screws.
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Deskilling and loss of human agency When machines make decisions—or support decisions—with little human input, staff may get trained to react rather than act. Wooldridge highlights that reliance on automation “trades brainpower for convenience”. (facebook.com) In effect: the worker becomes the machine’s puppet.
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Reinforcing short‑term metrics and gaming the system Because AI thrives on easily measurable data, management might focus more on what can be tracked (output, speed, compliance) than what matters (learning, adaptability, meaningful work). The result is optimisation of the wrong things.
In short, instead of AI ushering in a new era of enlightened leadership, it risks exacerbating traditional managerial failures: control over trust, measurement over meaning, automation over autonomy.
Why this matters now
- As companies rush to adopt AI, management frameworks lag behind. The promise of transformational change is often replaced by incremental automation of old habits.
- For workers, this means the risk isn’t just job loss—it’s losing what makes work human: discretion, purpose, meaningful collaboration.
- For leaders, the allure of efficiency can mask deeper costs: talent attrition, stifled innovation, lower morale.
- For society, this opens a bigger question: if AI enables deeper control, what happens to agency, training and fairness in work?
Key takeaways for stakeholders
- For executives: Don’t treat AI as a plug‑and‑play fix. Ask: What skills will our people lose? What human judgement do we want to preserve?
- For managers: Resist using AI only to measure headlines (productivity, speed). Use it to amplify human decision‑making, not replace it.
- For employees: Be aware of how your role may shift—from decision‑maker to compliance‑actor. Expand your skill‑set into areas machines struggle with: judgement, ethics, innovation.
- For HR/organisational designers: Design AI‑management systems with guardrails: transparency, appeal mechanisms, meaningful feedback loops—not just dashboards.
Outlook: Risks & opportunities
There is a silver lining. If organisations are intentional, AI could liberate people from repetitive tasks and enable higher‑level work. But Wooldridge’s caution is timely: without conscious change, AI may instead deepen the very pathologies of management that we’ve been trying to escape for decades.
The window for shaping this is now. If companies just replicate yesterday’s structures with new tech, the outcome is not progress—it’s reinforced mediocrity.
Glossary
- Artificial Intelligence (AI): A set of computational methods (machine learning, deep learning, etc.) enabling machines to perform tasks that traditionally required human intelligence.
- Deskilling: The process by which jobs require fewer skills as machines or systems take over more complex tasks.
- Metric‑driven management: A leadership style heavily reliant on quantifiable performance indicators (e.g., output numbers, response times) at the expense of qualitative aspects (e.g., creativity, judgement).
- Human agency: The capacity of individuals to make choices and act independently—not simply follow instructions or protocols.
- Automation creep: The progressive takeover of tasks by automated systems, often starting with the simple ones and gradually moving into higher cognitive territory.
