Hello, fellow humans! I hope you’ve enjoyed the holiday. Coming back from the break, it’s time to think about how we want to be in our work lives for the coming year. Today, I have some data, intelligence, and insight for you to consider as you try to navigate an increasingly agentic AI world in 2026.

Retail and ecommerce teams using AI for customer service are resolving 40-60% more tickets without more staff, cutting cost-per-ticket by 30%+, and handling seasonal spikes 3x faster.

But here's what separates winners from everyone else: they started with the data, not the hype.

Gladly handles the predictable volume, FAQs, routing, returns, order status, while your team focuses on customers who need a human touch. The result? Better experiences. Lower costs. Real competitive advantage. Ready to see what's possible for your business?

See it in action

The more we see leadership in organizations driving the evergreen themes of efficiency, innovation, and growth, the more the rest of the organization is paddling furiously to make AI fit those objectives. Everyone is feeling the pressure to adopt AI in some form, but the reality is that most organizations and industries are still mostly using chatbots, and struggling to use agentic AI in any meaningful way. These are some of the findings from a McKinsey report last fall.

A major roadblock is that managers and team members are unprepared for leading human-AI hybrid teams. Executive leaders are expressing a vision of AI agents being able to perform work autonomously with minimal human intervention. But the reality in the office is that managers and team members are finding that they need to actively manage the AI agent just like a team member. The shift requires new management skills, performance metrics, and organizational structures as AI agents take on more employee-like roles.

Organizations are rapidly adopting some AI systems:

According to a report from Inc., managers and workers are unprepared for leading hybrid human-AI teams. The shift requires new management skills, performance metrics, and organizational structures as AI agents take on more employee-like roles. In other words, the challenge is at least as much about human interactions as it is about technology.

AI agents can be inconsistent, requiring a human-in-the-loop to ensure consistent, high-quality results. That is leading teams to ask questions like how much agent management time is too much? How do we plan for building, testing, and deploying agents? How do humans need to think and work differently when we’re interacting with agents and not humans? How should we think about the agents that are becoming part of our workforce?

As a lot of workplaces are making the AI transition from the shiny new toy stage with chatbots to the era of finding ways to make AI automate and scale for us, the challenge is becoming how to adapt our behavior, thinking, and practices in ways that work for our identities, our colleagues, and our organization’s mission. Christyl Lucille Murray tries to address this complex space with her SHINE framework at Chief Learning Officer.

For readers familiar with change management principles, this framework shares some key concepts. But she build on each piece with the added complexities of AI. While having a sponsor for any change initiative is important, we also need conversations to help us make sense of our new relationships to work, technology, and our teammates. Changing habits is also a part of any change process, but using AI changes the nature of the habits dramatically because it requires AI fluency and managerial skills that may be new.

Her framework covers five areas:

Even professionals skilled in change management are challenged by the fundamental transformations that AI is bringing to the workplace, and this could be a powerful starting point for organizations trying to clearly define roles and workflows as AI develops and disrupts our work lives.

Business leaders from the executive suite to the garage startup are facing difficult questions about how to learn as AI gradually becomes more capable and more integrated into our work and school lives. One senior executive described the problem as “None of us knows how people will learn in this new era.”

Lynda Gratton from the London Business School writes for the Harvard Business Review that she is having these difficult conversations with executives in what she calls “sense-making conversations” to navigate the new learning paths. They’re tackling difficult topics like:

AI is fundamentally altering how humans develop expertise and professional identity. There's growing concern about AI shortcuts disrupting natural pathways to mastery, while simultaneously creating new requirements for AI delegation skills and full-stack capabilities. Organizations are grappling with preserving human experiences that foster empathy and agency while adapting to AI-enhanced workflows.