Do We Need Managers in the Age of AI?


Will companies of the future still have managers?

AI has swiftly made its way beyond support roles and dashboards: AI assistants are entering board rooms and making operational decisions, executing tasks that were once human managers’ prerogative. A recent research by McKinsey points out 7% of companies are using AI for major strategic decision-making. For sales- and marketing-related questions, AI has become a vast source of insight and advice.

Autonomous AI in management is no longer pie in the sky; it’s actually reshaping the workplace. As businesses adapt, new questions arise. What happens to the role of managers as we know it? How to onboard autonomous AI responsibly? Can machines really lead—and do we even want this?

Do Companies Trust AI to Manage Workflows Autonomously?

AI is already taking on critical roles in operations like logistics, budgeting, customer service, and supply chain management—tasks traditionally performed by human managers. The appeal is clear: AI handles these tasks with greater precision and efficiency than humans. For example, a global logistics company implemented AI to manage its supply chain. The AI tracks inventory, flags delays, and reroutes shipments autonomously, achieving a 30% improvement in fulfillment efficiency. Similarly, in finance, AI portfolio managers adjust investments in real-time, analysing market data and assessing risks without human intervention. These AI systems go beyond automating routine tasks—they replicate the decision-making process end-to-end, which challenges traditional management roles at both middle and senior levels.

How Can Companies Introduce Autonomous AI Without Causing Alarm?

Introducing AI into decision-making roles can create uncertainty, particularly around accountability and the loss of the human element in leadership. Employees may worry about job displacement or a reduced personal connection in decision-making. The key to a smooth transition is transparency and inclusion. AI should be positioned as a tool to complement human decision-making, not replace it. This approach allows employees to focus on areas where human skills remain irreplaceable, like strategy, relationship-building, and creative problem-solving.

Workshops are an effective way to explain AI’s role in decision-making, clarifying what the AI will and won’t do, how it makes decisions, and where human oversight is still required. Clear governance structures also ensure accountability by defining who is responsible for what throughout the process.

A culture of continuous feedback ensures employees feel involved and valued. This encourages them to offer insights that can improve AI integration while making them feel more comfortable with the change.

What About the Ethics of AI Making Final Decisions?

Ethics play a crucial role when AI takes on significant decision-making responsibilities. It’s not just about efficiency versus responsibility—it’s about ensuring that AI decisions are fair and transparent. One common approach is to incorporate human oversight at critical decision points. For example, AI systems used in hiring or vendor management should be reviewed by humans to avoid bias and ensure fairness. AI governance boards and ethics committees can help define which decisions AI can handle independently and where human involvement is necessary.

Transparency in AI decision-making, known as explainable AI, helps build trust. When employees understand the reasoning behind an AI’s decisions, it enhances accountability and ensures that decisions are made fairly.

How Does This Shift Affect the Future of Leadership Roles?

Leadership isn’t disappearing—it’s evolving. Autonomous AI agents are taking over traditional managerial tasks like performance monitoring and project planning, allowing leadership to focus on culture, innovation, and ethical oversight. This shift is already happening. For instance, in some manufacturing firms, mid-level managers have been replaced with AI agents. Rather than laying off employees, these companies are retraining them as AI collaboration leads. These employees now focus on monitoring AI system performance, optimising outputs, and maintaining team morale.

In the future, managers will likely move away from overseeing people to managing the systems that support them. Rather than acting as process gatekeepers, they will act more like coaches and facilitators, ensuring AI is working as intended and supporting team success.

What Practical Steps Can Companies Take to Prepare for AI-Managed Operations?

  1. Start with pilot programs: Introduce AI in one workflow at a time, then review results transparently with the team.
  2. Scale thoughtfully: Use insights from smaller AI rollouts to refine processes when scaling to other departments.
  3. Invest in AI training: Ensure all employees, from entry-level to executives, are prepared to work effectively with AI tools.
  4. Collaborate on AI policy: Involve teams from different departments to ensure AI policies are fair, inclusive, and well-rounded.
  5. Monitor AI performance: Regularly assess AI’s impact and stay vigilant for unintended consequences.
  6. Celebrate AI-driven successes: Share stories where AI has empowered employees, rather than replaced them, to promote wider acceptance.

While AI is increasingly responsible for managing workflows, management roles won’t disappear. Instead, leadership will shift from overseeing people to managing the systems that enable them to thrive. Companies that embrace this shift early will be better positioned for success in an automated future.

Written by Atalia Horenshtien, Head of AI Practice at Customertimes

Tags:

We will be happy to hear your thoughts

Leave a reply

Som2ny Network
Logo
Register New Account
Compare items
  • Total (0)
Compare
0
Shopping cart