Navigating the age of AI: rethinking team structure, leadership and change management
Written by Simon Lanngren
AI is fundamentally changing how organizations operate, lead, and adapt. Beyond being a catalyst for increased productivity, it represents a novel form of capital that, when effectively harnessed, can reshape the operational and competitive landscape (Forbes). Successful AI adoption requires more than technical expertise—it calls for rethinking team dynamics, leadership, and how organizations manage ongoing change.
“AI’s capabilities allow organizations to rethink how teams are structured, offering the potential for a strategic edge in leveraging the technology. To fully realize this advantage, leaders must embrace new challenges, adapt their leadership approach, and manage change effectively to ensure AI and human expertise are aligned for success”
- Simon Lanngren, Management consultant at Algorithma
The role of generalists vs. specialists in the age of AI
In Range: Why Generalists Triumph in a Specialized World, David Epstein argues that generalists, who connect knowledge across domains, are often better equipped to solve complex problems. As AI is transforming industries, and while it is highly specialized, the value of being a generalist for a single individual remains clear. Generalists offer a broader perspective, combining insights from different fields to drive innovation in ways that AI alone cannot.
However, at the organizational level, the unique value of generalists may diminish as AI tools allow teams to become more specialized, offering insights across various domains by processing large volumes of information to bridge knowledge gaps. This simplified collaboration suggests that AI may assume some of the integrative roles traditionally held by generalists. This raises an important question: How essential will generalists be when AI can effectively connect the dots between specialists?
Looking ahead, specialist teams supported by AI are likely to achieve even better outcomes than teams of generalists. This shift will reshape team structures, influencing both leadership roles and the approach to change management. To fully harness AI's potential, organizations must not only integrate AI but also manage the transition effectively, fostering seamless collaboration between specialists and AI systems.
Organizing for success in the age of AI
As AI increasingly takes on the integrative role of connecting knowledge across functions, the way teams are organized will need to reflect this shift. Instead of traditional hierarchies or siloed departments, agile, collaborative teams will become the norm. AI-driven, cross-functional teams—bringing together different domain experts and business strategists—will be crucial for efficiently leveraging both human expertise and AI capabilities. These teams must effectively integrate technology with business strategy, ensuring that AI solutions not only function efficiently but also support the organization’s broader goals and objectives. In this new setup, the team itself will take on the role of the generalist, combining the collective expertise of its members with AI’s ability to bridge knowledge gaps across disciplines.
The cross-functional team structure allows the group to stay flexible and responsive, continuously adapting to new AI advancements. This approach also ensures that AI’s potential is fully utilized while keeping human expertise central to decision-making—making these teams more likely to successfully scale AI solutions (Deloitte).
Leadership in the age of AI
As businesses reorganize around AI, the role of leadership is expanding. Leaders must now guide AI-powered teams, where AI plays a central role in decision-making, while human input focuses on strategic oversight and direction. This shift requires leaders to develop new skills—combining an understanding of AI, including its strengths and current limitations, with the ability to lead and support their teams effectively in the evolving landscape.
As businesses restructure to integrate AI—shifting from traditional hierarchies to more agile, cross-functional teams—leadership must evolve accordingly, as this shift requires more than just technical expertise. Strong leadership is crucial for fostering collaboration in the new AI-enhanced team environment. Leaders must treat AI as a new team member, understanding its strengths, limitations, and how to integrate it for maximum business impact. By doing so, they ensure AI becomes a valuable asset, rather than a disruptor, to their business. This concept is further explored in Did we accidentally make computers more human?
In this new business environment, several leadership qualities are becoming increasingly critical:
Facilitating cross-cultural collaboration: leaders must create inclusive environments where specialists from different backgrounds can collaborate successfully. Embracing diverse perspectives and fostering effective communication across domains are essential for driving innovation and ensuring alignment with organizational goals.
Staying informed on AI trends: Leaders need to stay updated on the latest AI advancements. This supports change management efforts and ensures that employees develop the right competencies in a fast-changing environment. By staying informed, leaders can help their teams adapt quickly to new AI tools and innovations, ensuring their team is always up to date with the latest advancements in AI.
Balancing AI’s role with human leadership: Understanding AI’s strengths and limitations is key. Leaders should create environments where AI is seen as a collaborator—much like a new colleague—not a competitor, helping teams achieve strategic goals efficiently. This requires balancing technical knowledge of AI with the ability to manage and support the people who work alongside these systems.
Maintaining the human touch: While AI can handle much of the routine day-to-day tasks and support decision-making, the human element remains critical for success. Leaders must prioritize creativity, emotional intelligence, and ethical judgment—qualities AI lacks—and ensure they are reflected in every aspect of the team's work. These human abilities allow leaders to provide vision, foster collaboration, and ensure that AI-driven decisions align with organizational values. For further information on this topic check out the our article Driving impact through strategic AI and human-centric design
“Leading in the age of AI goes beyond implementing new technologies—it’s about guiding teams through the cultural and operational shifts AI brings. Leaders must ensure that AI and human expertise work together to foster innovation and drive the organization toward its strategic goals”
- Kristofer Kaltea, Business and operations leader at Algorithma
Change management: navigating AI transformations
As AI technology advances, one of the key challenges is that it outpaces people's ability to adapt. Change management is not just an enabler for adopting new technology—it’s a necessity to make sure AI is integrated successfully across the organization. As AI drives cultural and operational shifts, the role of change management will only grow in importance.
In the context of AI, change management is not only about adapting AI itself but also to its ever-changing potential. Without this organizational mindset, even the most well-defined AI strategies will fail. With AI's rapid evolution and accelerating pace of change, guiding the transition becomes a core leadership responsibility, helping employees and leaders integrate AI successfully into everyday workflows.
To drive AI-focused change management, organizations should focus on (Forbes):
Establishing AI literacy: Employees need a solid understanding of how AI functions, its business potential, and the risks it may introduce. Regular training and independent learning should be encouraged to keep pace with AI’s rapid evolution.
Facilitating knowledge transfer: AI experts, such as data scientists, should share their insights with non-technical teams through workshops, presentations, and documentation. This ensures that AI knowledge spreads throughout the organization, fostering continuous upskilling.
Providing hands-on learning opportunities: Establishing internal AI sandboxes gives employees the freedom to experiment, test new AI models, and explore their capabilities and risks in a consequence-free environment. This hands-on approach not only makes learning more practical and engaging but also helps teams gain deeper insights into AI's potential. Organizations that emphasize experimentation are significantly more successful in scaling AI solutions (Deloitte).
For more insights on best practices for scaling AI assistants check out our article on the subject Overcoming barriers to scaling AI assistants.
“Unlike past changes driven by new tools or processes, AI reshapes the very way people and teams work together. Managing this shift isn’t just about rolling out a new system—it requires guiding an ongoing adaptation, where AI becomes a core part of decision-making and team dynamics, not just an add-on.”
- Jens Eriksvik, CEO at Algorithma
Shaping the future: thriving in the age of AI
The real challenge of AI lies not in the technology itself but in transforming how organizations operate. Success depends on rethinking team collaboration, expanding leadership roles, and managing change effectively. Organizations that balance human expertise with AI’s capabilities—from building AI-powered teams to fostering ethical leadership—will lead the way.
Change management is key to this transformation, helping organizations continually adjust their structure, culture, and workflows to keep pace with the ever-changing AI environment. Without it, AI initiatives risk falling short, leaving businesses struggling to adapt.
The future of AI lies in the partnership between human creativity and AI’s capabilities. Those who embrace this shift will not only thrive in the AI era but also help shape it.
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