As business and operational environments grow increasingly complex with the rise of AI and efforts to reestablish U.S. manufacturing capabilities, executives need to rethink the role of their most vital operational asset: frontline managers (FLMs).
Call to mind an image of an FLM and you may see a nondescript employee, clipboard in hand, monitoring progress and reviewing deliverables. Yet we know this traditional function is becoming rapidly obsolete. With massive manufacturing repatriation in the U.S. on the horizon, four generations in the workplace, and unprecedented business complexity, chief human resources officers and talent executives must rethink how they create value on the front lines. The emerging answer to this challenge is building “super managers” who harness AI to handle routine administrative tasks while focusing on the uniquely human elements of management that create a sustainable competitive advantage.
THE MANAGEMENT CRISIS
Organizations face a paradox: managerial responsibilities have never been more important, yet fewer emerging professionals want these roles. The majority of Gen Z workers are not interested in pursuing leadership positions, creating a leadership vacuum at precisely the moment when skilled guidance through technological transformation is most critical. This reluctance is understandable. Traditional management has become synonymous with bureaucracy, performance monitoring, and administrative overhead. Further, a decade of social and societal reckonings (e.g., #MeToo, COVID-19, BLM, etc.) have brought overdue scrutiny to inclusion, parity, bias and performance management; all topics which now can be addressed with AI tools that support greater objectivity. The question isn’t whether AI will replace managers, but rather how AI will transform the manager architype into something simultaneously more strategic and more human.
FROM TASK MONITOR TO HUMAN DEVELOPER
Research from a global survey administered by SAP SuccessFactors of over 4,000 employees reveals that 63% of employees believe their lack of AI literacy will be a barrier to their future success. This perception creates an urgent mandate for managers to evolve from task monitors to capability developers. Interestingly, managers themselves appear ready for this transformation. When asked about their most desired outcomes from incorporating AI into their work, managers ranked priorities in this order:
- Foster the growth and development of team members
- Demonstrate care and concern for team members
- Build a positive team culture
- Communicate with and influence others
- Specify and evaluate team members’ work
This prioritization reveals a profound truth: managers themselves want to spend less time on performance evaluation and more time on human development. AI offers a path to realize this aspiration.
THE ARCHITECTURE OF THE SUPER MANAGER
Building Super Managers represents a fundamental shift in how we conceptualize the managerial role. Rather than being primarily responsible for oversight and evaluation, Super Managers can create environments where both human and AI capabilities flourish through complementary strengths. This involves partnering with AI agents to handle workflows, create project plans, monitor progress toward objectives, and evaluate quality against consistent standards. Engaging in digital augmentation frees managers from administrative burdens while simultaneously providing more comprehensive and objective performance data. As a result, rather than subjective quarterly reviews based on a manager’s necessarily limited observations, AI systems can provide continuous feedback based on comprehensive data. The Super Manager then applies human judgment to this data, contextualizing it within the team member’s career aspirations and organizational needs.
ORGANIZATIONAL REDESIGN IN THE FACE OF DISRUPTION
AI-augmented management also enables flatter, more agile organizational structures that can repurpose more quickly and respond to changes in the business landscape. With AI handling coordination and monitoring functions, organizations will require fewer middle management layers. Super Managers can oversee larger, more diverse teams while maintaining consistent performance standards. AI systems can track commitments, dependencies, and progress across organizational boundaries, creating transparency that facilitates cooperation without constant managerial intervention.
CREATING SUPER MANAGERS: AN EXECUTIVE AGENDA
To develop super managers, executives need to rethink how they select, equip, and develop managers.
- Align With Strategic Vision: Start by identifying the critical skill-based approaches needed to support your long-term strategic vision. What capabilities will your organization need three to five years from now? How can AI-augmented management accelerate the development of these capabilities? The most effective super-manager implementations will be tailored to specific strategic imperatives, whether that’s a turnaround situation, a period of inorganic growth, or organizational redesign.
- Redefine Managerial Responsibilities: Traditional managerial capabilities must be reconceptualized into broader categories that reflect the AI–human partnership and include: technical abilities, including fluency with AI tools and platforms, judgment for when and how to apply AI versus human decision-making, risk and compliance that ensure ethical and responsible AI use, and human leadership, relationship building, influence, collaboration, and team development. This redefinition must be explicit, as communicated through updated job descriptions, performance metrics, and development programs.
- Rebrand Management: The managerial value proposition needs fundamental rebranding to attract talent, particularly from generations skeptical of traditional hierarchies. It is critical to position management responsibilities as focused on authentic relationships and human development, rather than control and evaluation. Key to this shift is emphasis on organizational citizenship behaviors that transcend formal reporting relationships to provide needed support and camaraderie in challenging business environments. In AI-enabled organizations, influence flows through networks rather than hierarchies, requiring managers who can connect people, ideas, and opportunities across traditional boundaries.
- Position AI as Augmentation, Not Competition: Executives must create clarity around AI adoption that positions technology as augmenting human managers rather than competing with them. Shopify’s approach provides an instructive example: The company explicitly frames AI as a “copilot” that handles routine tasks while elevating human judgment. When selecting AI tools, prioritize those that provide customized support for your specific strategic plans.
THE SUPER MANAGER IMPERATIVE
Organizational success ultimately depends on frontline leadership. By transforming managers from administrative overseers to human developers, the super manager approach doesn’t just improve efficiency, it can respond to broader social dynamics of the moment to attract, develop, and retain talent in an era of unprecedented technological change. Organizations that master this balance will create sustainable competitive advantage through their ability to adapt their workforce, continuously develop human potential, and efficiently leverage advancements in automation. The super manager isn’t just a response to AI—it’s the key to unlocking the full organizational potential of people and AI combined.
Through his portfolio career, Dr. Beau River has been a professional athlete, combat PTSD clinician and professional services executive. The common theme across his experiences is continuous learning to deliver a world-class performance. As the Founder + Managing Partner of Leadership Delta Partners, he works with a range of organizations and leaders to elevate their performance by providing executive development, executive selection, succession planning, strong team development, and board evaluation. Dr. River is also Adjunct Faculty at Northwestern University in their Learning and Organizational Change program.
Dr. Katherine Gibbard is a Research Scientist on the SAP SuccessFactors Growth and Insights team researching the future of work to inform product development, marketing, and strategy. She has deep expertise leading AI research efforts, with a PhD in the trust and adoption of generative AI solutions.
