- New wave of managers transforming business
A few years back, a Harvard Business Review’s (HBR) article argued that humans’ edge in “reframing” ensures their indispensability, and while AI has advanced since then, it’s not yet at a point where it can autonomously handle the nuanced, adaptive thinking managers often require. The concept that ‘AI won’t replace managers, but managers who utilise AI will outperform those who don’t’ reflects a growing consensus on the evolving role of artificial intelligence in the workplace.
Indeed, AI won’t replace managers but will elevate those who use it—history and logic support this. However, the paradigm’s arrival isn’t a distant promise; it’s a present, if incomplete, reality. The divide isn’t between AI and managers but between managers who see AI as a partner and those who don’t—a divide that’s widening, even if it hasn’t yet engulfed every corner of the workforce.
AI enhances, not replaces, managers
The core idea is that AI won’t replace managers but will favor those who exercise and using it. So rests on the unique strengths humans bring to management that AI cannot fully replicate. Management isn’t just about data analysis or task automation; it involves emotional intelligence, creativity, and the ability to navigate complex interpersonal dynamics. For instance, AI can analyze employee performance metrics or optimize schedules, but it struggles to inspire a team, mediate conflicts, or adapt to unexpected cultural shifts within an organization. These human-centric skills ensure managers remain essential, even as AI takes over routine or analytical tasks. Moreover, AI is a force multiplier. Managers who use AI can leverage it to make faster, more informed decisions by predicting project risks or identifying market trends; outpacing those who rely solely on traditional methods. This mirrors historical technological shifts: the advent of spreadsheets for example LOTUS 1-2-3 in 1982, MS Excel in 1985 and Google sheets in 2006 or “Sheetgo” in 2024 didn’t eliminate accountants but made those adept these become more competitive. Similarly, AI tools like predictive analytics or natural language processing can give managers an edge, turning raw data into actionable insights while freeing them to focus on strategy and leadership. The competitive replacement dynamic is logical so in a results-driven world, organizations will naturally favor managers who harness AI to boost efficiency and innovation over those who don’t.
Paradigm’s arrival
The assertion that “this new paradigm hasn’t arrived yet” underestimates how much AI has already infiltrated management practices. By today, AI tools are no longer futuristic novelties but practical realities in many workplaces. Managers in industries like tech, finance, and retail are already using AI-powered platforms—think tools like Salesforce with AI-driven insights or workforce management systems like Workday—to streamline operations and enhance decision-making. A 2023 statement from an IBM executive highlighted that roughly a fifth of businesses were starting to integrate AI, and that trend has likely accelerated.
In 2017, Erik Brynjolfsson, MIT Sloan School professor, explains how rapid advances in machine learning are presenting new opportunities for businesses. He breaks down how the technology works and what it can and can’t do (yet). He also discusses the potential impact of AI on the economy, how workforces will interact with it in the future, and suggests managers start experimenting now. This foreshadowed the shift, and today, we see it materializing.
Consider customer service management: AI chatbots handle routine inquiries, allowing managers to focus on escalations and strategy, as seen with companies like NatWest, which scaled its chatbot usage during the pandemic. In project management, tools like Forecast or Zeda.io automate scheduling and resource allocation, yet still require human oversight for strategic direction. These examples suggest the paradigm isn’t waiting to arrive—it’s here, just not universally adopted. The gap isn’t in the technology’s presence but in its uneven uptake, with only 15% of managers consistently using generative AI, according to a 2024 Capgemini survey, compared to 40% of business students who do. This disparity hints at a generational and adoption lag, not an absence of the paradigm itself.
But why it feels incomplete
On the flip side, the “hasn’t arrived yet” claim resonates because the transformation is patchy and nascent. Many managers, particularly in smaller firms or traditional sectors, still operate without AI, either due to lack of awareness, resources, or trust in the technology. A 2023 survey by “Pega” found 78% of executives believed AI would reduce middle management ranks, yet a 2024 article noted that only a minority of managers actively use it daily. This suggests a disconnect between potential and practice. If the paradigm were fully here, we’d expect broader adoption, not a landscape where AI-savvy managers are the exception rather than the rule. Additionally, AI’s limitations temper the shift. Current systems excel at pattern recognition and optimization but falter at reframing problems or exercising judgment in ambiguous situations—skills critical to management. A 2021 Harvard Business Review piece argued that humans’ unique ability to “reframe” problems guarantees their essential role, and although AI has made significant strides since post-pandemic era, it still falls short of independently managing the subtle, flexible thinking that managers frequently need. This gap in AI’s development could explain why the anticipated shift feels like it’s still approaching. Arguably no, the technology exists, but it hasn’t fully evolved into a flawless collaborator for all managerial responsibilities.
Why the paradigm hasn’t fully arrived
1- Technological Barriers:
- AI adoption requires substantial investment in technology infrastructure, which might be a barrier for some organizations.
- There are still technical limitations and challenges in integrating AI with existing systems, hindering widespread adoption.
2- Skill Gaps:
- Managers need a certain level of digital literacy and familiarity with AI tools. The current workforce may lack the necessary skills to fully leverage AI.
- Bridging the skill gap through training and education is essential but takes time and resources.
3- Cultural Resistance:
- There can be resistance to change within organizations. Some managers may fear that AI threatens their jobs, leading to reluctance in adopting new technologies.
- Creating a culture that embraces innovation and continuous learning is crucial to overcoming this resistance.
4- Ethical and Regulatory Concerns:
- The ethical implications of AI, such as privacy, bias, and accountability, need to be addressed. Organizations are cautious about adopting AI without clear guidelines and regulations.
- Navigating these concerns requires a thoughtful and responsible approach, which can slow down the pace of adoption.
An Evolving Shift
The reality probably rests in a blend of perspectives. The new era has begun conceptually but isn’t fully realized. In innovative companies, like tech powerhouses or data-centric startups, managers leveraging AI are outpacing their non-AI counterparts, reaping clear efficiency benefits that are recognized and valued. Still, across wider industries, the transition lags, slowed by obstacles to adoption and AI’s still-developing capabilities. The sentiment holds because it’s directionally correct: over time, market forces will 淘汰 (淘汰,淘汰 which means “eliminate” in Chinese (used here metaphorically) managers who don’t adapt, just as typewriter users faded when word processors emerged.
A book published by Harvard Business Review (HBR), on February 11, 2025 The HBR Guide to Generative AI for Managers, written by Elisa Farri and Gabriele Rosaniis is packed with practical tips, prompts, and case studies. This 288 pages’ guide explains how one can run smart experiments and boost productivity, determine the right collaboration mode: a Co-Pilot or a Co-Thinker. However, it also warns and give awareness of the risks and avoid traps along with capitalizing gen AI–enabled mindset
Epilogue
AI won’t replace managers but will elevate those who use it—history and logic support this. However, the paradigm’s arrival isn’t a distant promise; it’s a present, if incomplete, reality. The divide isn’t between AI and managers but between managers who see AI as a partner and those who don’t—a divide that’s widening, even if it hasn’t yet engulfed every corner of the workforce.
The author, Nazir Ahmed Shaikh, is a freelance writer, columnist, blogger, and motivational speaker. He writes articles on diversified topics. He can be reached at nazir_shaikh86@hotmail.com
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