Editorial
As AI takes on a bigger role in our daily work lives as an active collaborator, organizations need to focus beyond job redesign and employee reskilling. If AI is considered a teammate, it needs someone to lead it with clear expectations, feedback loops and shared, cross-functional accountability.
Let's explore what it means to manage AI like part of the team and why it matters to your organization’s success and your employees’ retention.
AI Joined the Team: The Quiet Shift Reshaping Work
It feels like yesterday when ChatGPT opened the floodgates to turn AI into a daily reality for businesses, big and small. Fast-forward to 2025, and AI has gone beyond a background tool to a contributing “co-worker” influencing how we collaborate, make decisions and perform our work.
Just today, I facilitated a leadership development session where the AI-assistants handling meeting summaries and post-session planning outnumbered the human attendees. This moment showcased a bigger truth: AI is now embedded in almost everything we do and is becoming a functional part of the team.
This shift happened quickly, but not in a vacuum. At the World Economic Forum in Davos this year, top C-Suite leaders from PwC and Goldman Sachs encouraged their peers to frame AI as a “digital colleague” to their organizations. Their message was clear: AI should be treated as a colleague we depend on, beyond automation or augmented work.
Most of us have already experienced this change in our daily interactions with AI at work. Companies have focused on job redesign and reskilling efforts to respond to this shift, equipping employees to become better “co-creators” with AI. But this only addresses one part of the equation: our ability and agency to work with AI. The rest of the playbook for AI as an active contributor to our work remains mostly unwritten.
AI as a Teammate: The Need for a Clear Ownership Playbook
If every new teammate has a manager to guide expectations and ensure performance, who is AI’s manager? Who signs off on its work? Who makes sure it’s delivering value?
Who is responsible for setting transparency, guardrails and feedback loops that guide how we work with it every day? In short, who owns the employee experience of working with AI as a collaborator? And when AI works across departments, who owns its performance?
Ownership is currently scattered and siloed. Digital Employee Experience (DEX) teams focus on usability. Employee Experience (EX) leaders care about adoption and trust. HR and compliance leaders want guardrails. People managers look at outcomes. Business leaders want enhanced productivity. Employees co-create with AI in real time.
Without a clearly defined cross-functional ownership playbook, AI’s role as a digital colleague can become ambiguous and inconsistent. The HR tech platform Lattice learned this firsthand when it briefly added AI agents as “employees” to be onboarded, given goals and evaluated on performance similar to its employees. The intent was to treat AI like a co-worker, but the execution created backlash and confusion and the company reversed its decision.
Lattice could have benefited from clearer communication and a defined accountability model that showed where the human vs. AI distinctions resided.
The High Price of an Unmanaged AI Teammate
Even well-intentioned efforts to integrate AI as a teammate can backfire without thoughtful guardrails and clear communication. These misalignments in treating AI as a co-worker show up across five critical organizational areas:
- Decision-Making Bottlenecks: If employees are unclear on when and how to use AI, they’ll leverage it inconsistently and their managers will have little visibility on how work gets done. Unclear expectations create inconsistencies that can slow down decision-making.
- Accountability Blind Spots: When AI agents operate across organizational boundaries or make independent decisions, who owns and approves the outcome? Without clear ownership, mistakes get missed and costly rework becomes routine.
- Missed Improvement Opportunities: When employees identify errors or bias, who do they report it to? Lack of clear feedback loops quickly erodes psychological safety, trust and operational effectiveness.
- Unfair Recognition Practices: Who gets the credit when AI handles more complex work? If organizations do not proactively build guardrails and transparency around human vs. machine contributions, it can damage employee retention and morale as team members feel that rewards are arbitrary.
- Compromised Customer Confidence: What happens when AI-generated outcomes reach customers? Who monitors accuracy, tone and potential mistakes? If customers can’t tell when they interact with a human or when AI introduces errors, they may take their trust and business elsewhere.
The stakes for leaving AI unmanaged are high. Organizations that succeed will design leadership practices with clear AI ownership and continuous feedback loops across the organization. While this approach sounds simple, it requires time and intention.
It Takes Shared Ownership to Manage AI
A cross-functional ownership model to manage AI would look like this to start:
- Employee Experience (EX) and Digital Experience (DEX) Practitioners monitor how AI impacts the daily lived experience of work (e.g., increased grunt work, expanded workloads, poor handoffs, signs of burnout, etc.)
- HR & Compliance Leaders establish norms around how work gets done, guardrails and role boundaries for ethical AI use and transparent guidelines on performance rewards and recognition.
- People Managers integrate AI expectations into team charters, coach employees on workflow integration and act as the final accountability stop for human judgment.
- Employees follow agreed usage guidelines, share feedback and surface mistakes or biases early.
While a cross-functional accountability model sets the foundation, managing AI as a co-worker also takes ongoing practice. Leaders need to stay close to how it’s impacting the daily lived work experience and create regular feedback loops to catch what’s working and identify the friction points. By listening to and following up on employee feedback, leaders can set and iterate on the model to ensure it keeps up with the pace of the work.
Senior leaders and HR need to provide a safety net, giving people managers the training and support to guide AI’s impact on team performance, especially when operating across organizational boundaries.
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If AI is a digital colleague, it’s part of your culture. As the saying goes, “culture eats strategy for breakfast.” It can’t belong to one person if you want it to deliver positive results or avoid becoming a hindrance. Shared responsibility, from the frontline to the C-Suite, ensures AI gets the same clarity, feedback and accountability as any human teammate, so your people and business can thrive alongside it.
Editor's Note: Read more takes on the question of AI managers:
- How Human Employees and AI Agents Can Collaborate Safely and Efficiently — For businesses to realize the benefits of AI agent-human collaboration, they'll need a whole new set of trust and control mechanisms in place.
- IT, the HR of Agentic AI? Not So Fast — NVIDIA CEO Jensen Huang said IT will become the HR of agentic AI. Sounds nice, but it's a huge oversimplification. Here's why.
- Will Your Next Hire Be an AI Agent? — Autonomous AI agents are making their way into every corner of the workplace. A look at where we are and where we're headed.
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