Eroding the executive talent pipeline by eliminating strategic thinking from middle-management
As organizations increasingly delegate managerial decisions to algorithms, we face a critical question: What kind of managers are we developing for the future? Drawing on evidence from Amazon, McDonald’s, Uber, Walmart, and other major corporations, this article argues that algorithmic management systems are creating “checkers”—supervisors who monitor algorithmic outputs—rather than true managers capable of strategic thinking and judgment. This transformation threatens not only individual career development but also the pipeline for senior executive talent and America’s competitive edge. The article proposes strategies for preserving genuine management development in an age dominated by algorithms.
“It’s very clear that AI is going to change literally every job,” Walmart CEO Doug McMillon recently stated, describing changes affecting the company’s 2.1 million employees. This transformation extends far beyond Walmart. Across Corporate America, algorithms are increasingly making decisions once reserved for human managers, including scheduling workers, assigning tasks, evaluating performance, and even terminating employment. While these systems promise efficiency and objectivity, they raise a fundamental question: If algorithms make the decisions, what exactly are human managers managing?
This article examines how algorithmic management is reshaping the nature of managerial work and argues that we are creating a generation of “checkers”—individuals who monitor algorithmic outputs but lack genuine decision-making authority or opportunity to develop judgment. This shift represents not merely a change in tools but a fundamental transformation in what management means, with profound implications for leadership development and organizational capability.
The Rise of the Algorithmic Supervisor
Automated Decision-Making at Scale
The scope of algorithmic management has grown significantly. Amazon, which employs over three million drivers worldwide, has adopted what researchers call “the most comprehensive” algorithmic management system, where algorithms guide workers through “workstation displays and scanners” in physical workplaces. The system’s Time Off Task (TOT) algorithm automatically monitors every second of inactivity: 30 minutes prompts a warning, one hour triggers disciplinary actions, and two hours lead to automatic termination—all without human intervention.
McDonald’s has deployed its Orquest scheduling system across 70,000 employees globally, reducing schedule preparation time from four hours to 30 minutes—an 87% reduction. The company is now implementing “generative AI virtual managers” to handle administrative tasks traditionally performed by human managers. Similarly, Walmart operates 45 different AI agents, with restaurant general managers historically spending 40% of their time on administrative tasks now being automated.
The Accountability-Authority Gap
A critical pattern emerges across industries: human managers retain responsibility for outcomes while losing decision-making authority. At Amazon, managers are “unable to use empathy or common sense to intervene in decision making” when the algorithm determines disciplinary action. One worker noted that when questioning algorithmic decisions, managers responded that “their hands were tied” by the system.
This creates what we term the “accountability paradox”—managers who face consequences for decisions they didn’t make. Uber drivers report similar frustrations, describing support interactions as “so robotic” that resolving issues, such as missing wages, requires “five or six emails going back and forth” with representatives who can only provide template responses. The human “manager” becomes a messenger for algorithmic decisions, bearing responsibility without authority.
From Managers to Checkers: The Competency Crisis
Judgment Call
Traditional management development occurred through the progressive delegation of decision-making responsibility. Junior managers learned to read situations, make judgment calls, and learn from failures. Middle managers developed pattern recognition through thousands of decisions. Senior executives synthesized these experiences into a strategic vision.
Algorithmic management has disrupted this progression. Those four hours McDonald’s managers once spent on scheduling weren’t just administrative time—they were opportunities to understand team dynamics, recognize patterns, and develop intuition. Now, managers simply verify algorithmic outputs. As one Walmart analysis noted, AI summarization tools have “transformed processes that once took a full day into tasks completed in minutes.” Efficient, certainly, but at what human capital development cost?
Exception Handling
Research on Uber’s algorithmic management reveals drivers developing elaborate workarounds: using multiple phones to run competing apps simultaneously, “periodically turning on and off their driver application while at traffic signals” to avoid distant requests, and creating underground networks to share “algorithm hacks.” These adaptations demonstrate human creativity in responding to algorithmic control, yet the managers overseeing these systems lack the authority to incorporate such innovations into practice.
When California legislators attempted to meet Amazon’s average quota of 420 boxes per hour, none could maintain the pace for even three minutes. Yet warehouse managers cannot adjust these algorithmically set targets based on human limitations or contextual factors. They can only monitor compliance with standards they cannot influence.
The Pipeline Problem: Where Will Tomorrow’s Executives Come From?
Leadership Development
The transformation from checker to executive requires developmental experiences that algorithmic management eliminates. A Carnegie Mellon study found that while drivers were initially “happy with algorithmic management,” they soon discovered they were “pushed to do things that seemed unreasonable” with no ability to negotiate or appeal. This learned helplessness extends to managers who oversee these systems.
Labor unions report that Walmart’s AI-driven scheduling has “slashed employee hours by 20%” with workers arguing the system “ignores human needs.” The managers implementing these cuts cannot explain the logic or modify the outcomes—they merely communicate algorithmic decisions. How can such “managers” develop the judgment needed for senior leadership?
Strategies for Developing True Managers
Organizations seeking to develop true managers rather than algorithmic hall monitors should consider:
1. Preserved Decision Spaces: Deliberately maintain areas where human judgment is required. Some decisions should remain outside algorithmic control to provide opportunities for development.
2. Rotation Through Non-Algorithmic Roles: Ensure emerging managers experience positions requiring genuine decision-making, even if less efficient than algorithmic alternatives.
3. Rewarded Override Authority: Create mechanisms for managers to override algorithms with appropriate justification, celebrating successful human intervention rather than punishing deviation.
4. Algorithm Design Participation: Train managers to understand and influence algorithm design rather than merely monitor outputs. Managers should shape the tools, not just serve them.
5. Failure-Tolerant Sandboxes: Establish low-stakes environments where managers can experiment, fail, and learn—experiences that algorithms cannot provide.
The Choice Ahead
The evidence is clear: we are creating checkers, not managers. The efficiency gains are real—McDonald’s saves 3.5 hours per schedule, Amazon processes millions of packages with minimal human intervention, and Walmart’s AI agents handle routine tasks at scale. But efficiency in the present may come at the cost of capability in the future.
The question isn’t whether to use algorithms in management—that ship has sailed. The question is whether humans will manage with algorithmic assistance or whether algorithms will manage with human checkers. Currently, we’re choosing the latter while referring to the checkers as “managers.”
In 10 to 15 years, when organizations need senior executives capable of navigating unprecedented challenges, making judgment calls with incomplete information, and leading through crisis, we may discover we’ve optimized away the very experiences that develop such leaders. The algorithmic middle manager isn’t just changing how work gets done, it’s changing what management itself means. If we continue on this path, we risk creating a generation of leaders who can monitor efficiently but cannot manage effectively.
The choice is ours: develop genuine managers who use algorithms as tools or build a workforce of checkers subservient to the algorithm. The long-term competitiveness of American business talent may depend on which path we choose.
References
- “Walmart’s Wake-Up Call: AI Will Change Every Job,” Lawyer Monthly, November 7, 2025.
- Teke Wiggin, “Weaponizing the Workplace: How Algorithmic Management Shaped Amazon’s Antiunion Campaign in Bessemer, Alabama,” Socius 11 (2025).
- Devansh, “Crushing Dissent by Code: Amazon’s Algorithmic War on Labor,” Medium, May 26, 2025.
- “Transforming McDonald’s Restaurant Operations Globally,” Orquest, September 3, 2024.
- “How McDonald’s Is Integrating AI Across Restaurants Globally,” Technology Magazine, March 18, 2025.
- “[8 Ways McDonald’s Is Using AI [Case Study]](https://digitaldefynd.com/IQ/mcdonalds-using-ai-case-study/),” DigitalDefynd, July 3, 2025.
- “When the Algorithm Is Your Boss,” Tribune Magazine, January 2022.
- Rosenblat, Alex. Uberland: How algorithms are rewriting the rules of work. Univ of California Press, 2018.
- “How AI Is Changing Grocery Retail Jobs at Walmart,” SymphonyAI, January 23, 2025.
- Min Kyung Lee et al. “Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers.” in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (2015), 1603-1612.
- “Regulating Amazon’s Warehouse Algorithms Is About More Than Injuries,” New Republic, November 28, 2023.
- “When Your Boss Is an Uber Algorithm,” MIT Technology Review, August 22, 2024.
- “Walmart’s AI Scheduling Sparks Worker Revolt, Nationwide Strike Looms,” Silicon Review, March 25, 2025.
