AI isn't a tool, it's a teammate: A guide to team adaptation

We are all focused on the technical roadmap for AI. But you don’t just need a tech plan, you need a team development plan. Because AI doesn’t just change the tools we use; it changes how teams think, work, and lead.

Let's start with a thought-provoking question: What if AI is your new team member?

In most technology shifts, we adopt a new tool and embed it into our existing ways of working. But AI isn’t a simple plug-and-play solution. It’s a catalyst for people-powered change that fundamentally alters the rules of the game. We all agree on keeping a "human in the loop," but have we stopped to consider what that means for the structure, mindset, and health of our teams?

In this article, we'll explore frameworks to help you navigate this transformation, ensuring your team doesn’t just adopt AI, but thrives with it.

Hitting reset: How AI can send your team back to ‘Storming’

Bruce Tuckman's model of team development, Forming, Storming, Norming, and Performing, is a brilliant lens for this challenge. Most leaders strive to get their teams to the ‘Performing’ stage. But what happens when you introduce a disruptive force like AI?

You risk hitting the reset button. The introduction of a powerful AI tool can unintentionally send a high-performing team right back into the ‘Storming’ phase. Consider two angles:

1. Team dynamics: How has the tool disrupted the fabric of the team? For some, it might expose how their role can be done faster, making them feel less valuable. For others, it may amplify the value of their work, bringing their strategic thinking to the forefront. Are team members now expected to play different roles? Is there less dependency on certain individuals?
   
   
2. Tool effectiveness: How well is your team actually using the tool? The expected ROI for AI is often tied to immediate performance gains. But is your team truly ‘Performing’ with the tool, or are they stuck ‘Storming’ - wrestling with how to use it, where it adds value, and how to take advantage of it effectively?

Don’t let these unsaid challenges impact team dynamics and morale. The critical first step is to bring these questions out into the open and solve for them as a team. This shared challenge will build trust and help you move back toward ‘Performing’ with minimal disruption.

A practical example: The evolution of a customer service team using AI

Let's make this tangible. Imagine a customer service team with a manager, agents, and an engineer. They are a ‘Performing’ team. Now, they introduce an AI tool that filters complaints, automatically manages simple queries, and prioritizes complex cases. Their goal is the same - excellent customer service - but their roles must adapt to achieve it.

• The Agents, now free from repetitive tasks, can handle complex cases with more personal, one-to-one interaction. Their roles shift, requiring them to build skills in conflict resolution and advanced problem-solving.
• The Manager’s role flexes in response. They move from managing workload and escalations to acting as a coach, identifying skill gaps, mentoring the team through difficult cases, and stepping in only when truly necessary.
• The Engineer’s role becomes more front-office. They are now an interpreter of data, sharing trends with the team, and ensuring the AI is monitored for biases, highlighting when a human needs to step in to make adjustments.

The team can achieve better outcomes, but only if they consciously adapt. Without acknowledging these new roles, this once high-performing team risks failure.

Case study examples of customer service teams using AI

• KLM leveraged DigitalGenius AI to automate over 50% of customer inquiries, enabling agents to focus on complex cases that required more of a human approach. As a result, KLM saw a 40% increase in Messenger interactions (improved customer experience) and a 5-point boost in NPS
• BT Group transformed its customer support by integrating Sprinklr’s AI platform, enabling virtual assistant Aimee to handle 60,000 weekly conversations and automate nearly 50% of common journeys. This shift has doubled usage, cut chat demand in half for key services, and freed up agents to focus on complex needs, while maintaining strong ethical and data safeguards. 
• Verizon redefined the role of its 60,000 contact center agents by using predictive AI to match each customer to the best-suited agent and equip them with real-time insights, cutting call times and boosting confidence. Instead of cutting headcount, Verizon reskilled agents into high-performing sales roles, driving a 40% increase in sales and turning its contact center into a powerful revenue engine.

Beyond Jobs to be Done: Defining the ‘Roles to be Played’

This brings us to a deeper point. Job descriptions explain the tasks that need to be done, but they don’t explain how they get done. In any successful team, people play unwritten roles that contribute to the outcome.

I'm a fan of the nine Belbin Team Roles, but for simplicity, let’s consider four essential ones:

1. The Leader: Sets the vision and provides direction.
2. The Facilitator: Guides discussions and ensures everyone participates.
3. The Coach: Provides support and feedback to help others develop.
4. The Member: Contributes expertise and supports the team's goals.

A team member can play any of these roles at any time. Instead of just thinking, "I need to bring a prompt engineer to this meeting," consider, "What roles do we need to solve this problem?" This framing allows every member to shine and ensures no one gets left behind.

Navigating the human adoption curve with COM-B

We can talk about team structures all day, but we haven't addressed the elephant in the room: an individual's readiness to adopt AI. The COM-B model for behavior change is an excellent framework here. For someone to adopt a new behavior, they need the capability, opportunity, and motivation.

The COM-B model for behavior change

Let's look at two common scenarios:

• The Laggard Leader: Imagine a team leader who has won awards for outstanding delivery. A new AI tool is introduced to extend their impact, but team performance declines. Upon investigation using COM-B, it becomes clear the leader, while motivated, lacks the capability. They don't understand the tool and fear it will make their role redundant. The solution isn't to replace them, but to provide targeted training and support to build their confidence and break down the barrier to adoption.
  
  
• The Early-Adopter Member: Now consider a team member who is a wizard with the new tool. They are an early adopter, and their work is helping everyone see the tool's potential. They are brought into leadership meetings to help make decisions. But this team member, while having the capability, may not be ready for the opportunity. They are being asked to play a role they aren't skilled for. The key is to leverage their strengths - let them be a change champion, a motivator, and a coach - while supporting them with the right guidance, rather than catapulting them into a role they aren’t ready for.

The five categories of adopters

Treat your new AI tool like a new person joining the team. You would naturally explain your ways of working and give them time to learn. Do the same with AI and have an open conversation about how the team needs to adapt in response.

Practical takeaways to start incorporating AI into your team

To move beyond questions and into action, here are four things you can do with your team this week:

1. Co-create principles: Don't let AI usage be a free-for-all. Work together to establish guidelines for "how we want to use AI here."
2. Foster experimentation: Create psychological safety for the team to experiment, learn, and even fail with the new tools. This is how you discover how to work together in new and better ways.
3. Map your "day in the life": Take time for each member to walk through their daily tasks. This builds a shared understanding of the entire system and sparks a collective conversation about where AI can genuinely help and improve the day to day.
4. Establish feedback loops: Success requires radical candor. Effective teams give each other quick, honest, and situational feedback that builds trust. Create open, reflective cycles to learn what’s working and what isn’t, ensuring fear doesn't drive AI usage underground. Don’t forget, the AI “team member” should also receive the feedback. What is working, what is not and what needs to change in response. 

The next step in your AI transformation journey is a conscious one. AI isn’t just a tool - it's your newest teammate, ready to help your organization reimagine roles, spark innovation, and enhance team performance. Embracing GenAI requires more than technology adoption; it’s about evolving how your people work together, adapt, and lead.

Ready to move beyond the hype and unlock AI’s full potential for your team? We can help you co-create principles, foster experimentation, and develop a future-ready approach that maximizes both human and AI strengths. Discover how embracing AI can propel your organization into a new era of growth and opportunity. Talk to us about making GenAI your team’s catalyst for lasting transformation.