AI is increasingly integrated into day-to-day operations, but few organizations have figured out how to make the most of it. It’s often piloted in silos or treated like just another piece of software. When results don’t match the hype, teams blame the technology or move on to the next tool.
The issue, however, usually isn’t technical; it’s conceptual. AI performs differently from traditional platforms. It adapts and improves through use. Its behavior is closer to that of a junior colleague than a finished product, and that’s exactly how organizations need to think about it.
Teams that treat AI as a teammate, not a technology, are seeing greater impact. They’re getting the most out of AI by teaching and guiding it, not merely deploying it. And they’re thinking about it differently: Rather than changing technology, they’re changing how people work with it. Here’s how to shift how your teams use AI.
# Assign Two Seats For AI
One way to reframe AI’s role in the organization is to assume that every team has two open seats—both of which are reserved for AI. The first seat is for automation. This seat can handle repeatable, rules-based tasks that no longer require human effort, such as categorizing support tickets, pulling KPI snapshots, or summarizing notes from a call.
AI is already capable of performing these tasks well, and this frees its teammates for more strategic work. The second seat is for augmentation. In this role, AI supports each team member as a high-functioning assistant would. It helps them move faster, think more clearly, and test assumptions. A strategist might use AI to pressure-test an idea or look for precedent, while a sales lead might ask AI to synthesize a complex client history. Both roles are important.
When AI operates only as automation, your team misses out on its creative potential. When it functions only as a thought partner, your team still carries too much administrative burden. By putting both seats in play, you open up capacity, creating room for better thinking across the board.
Read the full article written for Enterprise AI World to learn how to:
- Define clear roles for AI by assigning it both automation and augmentation responsibilities
- Write a practical “job description” for AI to align expectations and measure impact
- Establish team norms that guide how and when people work with AI
- Rethink success metrics to focus on team outcomes, not just efficiency gains
