What does AI in the workplace actually change – and what stays the same? The honest answer is that the disruption most people are watching for isn’t where the real pressure is building. It isn’t entry-level jobs disappearing overnight. The middle layer of most organizations is quietly eroding, and the teams that remain will need to be built very differently than anything most leaders have managed before.
That’s the thread running through a recent episode of The Marketing Blender Show. Our CEO Dacia Coffey sat down with fractional CMO Stacey Force, who spent eight years at ManpowerGroup leading disruptive innovation in talent solutions. She then moved to Korn Ferry, where she used behavioral data to understand what actually separates high performers from everyone else. Her take on where AI is creating real organizational pressure – and what to do about it – is worth sitting with.
How Is AI in the Workplace Changing the Role of Middle Managers?
Most conversations about AI and jobs focus on automation at the entry level, but Stacey thinks that’s where people are looking at the wrong place. “We thought that AI was gonna come in and it was gonna take a lot of entry-level jobs. And we’ll see some of that, but where we’re really seeing the most impact is in that sort of middle manager tier. Because you can’t replace the strategy and the vision of sort of your C-level leadership, but AI is getting really good at parsing out the tasks and creating sort of the marching orders for the doers.”
Middle managers have traditionally held organizations together in ways that rarely get acknowledged. Strategy got translated into daily action. Culture got deployed in the moments no policy document could anticipate, and someone was always reading the room when things were off. When AI absorbs the workflow management and task delegation they spent most of their time on, the question isn’t just who does that work – it’s what holds the organization together without them.
The path forward isn’t rebuilding the same model with fewer people. It’s designing teams that don’t need that layer to function – teams with enough autonomy to make decisions without waiting for permission, and enough cohesion to stay aligned without a manager in the middle.
What Does a High-Performing Team Look Like in the Age of AI?
Stacey uses a vivid analogy to get at this: the octopus. An octopus has a central brain and smaller autonomous brains in each tentacle. Each limb can investigate, solve problems, and act on its own – then pass what it learns back to the center. She sees that as a useful model for where team structure is heading.
Teams that work across disciplines, make decisions without constant escalation, and still move in a shared direction. Cross-functional teams in the past were often assembled under pressure, when no single department could solve a problem alone. Going forward, that kind of structure needs to be designed on purpose – before the pressure hits.
Stacey and her colleagues at Someta have built a framework around this, organized around what they call the ABCs of teams:
- Awareness: Psychological safety comes first. If people don’t feel safe to speak up, flag problems, or admit what isn’t working, nothing else in the framework functions the way it should.
- Balance: Role clarity, shared mental models, and process alignment. When people understand what they own – and what the people around them are working on – collaboration gets less complicated and handoffs stop falling apart.
- Cohesion: The trust that lets a team move quickly without second-guessing each other. It takes longer to build than most leaders budget for – but without it, speed creates fragility instead of strength.
These aren’t soft skills in the colloquial sense. They’re the conditions that determine whether a team can function when the work gets complicated and the pressure is real.
Why Behavioral Leadership Matters More as AI Takes Hold
One of the more thought-provoking threads in this conversation is the push to move leadership assessment away from personality and toward behavior. Traditional assessments – rooted in the five-factor personality model – give you a snapshot of who someone is. That snapshot is relatively stable, which is useful in stable environments. The problem is that stability is exactly what AI is disrupting.
Stacey makes a sharp distinction between uncertainty and unpredictability. In uncertainty, your past experience and mental models still apply – you’re navigating fog, but you know the terrain. Unpredictability is different. The terrain itself keeps shifting. The frameworks you built your career on may not give you reliable answers anymore. What matters is how a leader behaves in the moment, under pressure, when there’s no clear precedent.
There’s also something genuinely hopeful about this shift. “You can change behaviors. There are ways to coach behaviors, and I find the view of approaching this in a behavioral lens as being absolutely empowering for individuals because it is the science of making people stronger humans,” Stacey says.
Moving from traits to behaviors changes what development looks like. Traits are things you assess. Behaviors are things you practice, observe, and improve – and that shift has real implications for how organizations build leaders and measure growth.
How Do You Build Team Culture When AI Is Reshaping How Work Gets Done?
Culture is easy to post on a wall and hard to actually live. As AI in the workplace accelerates and middle management thins, the informal channels that culture used to travel through are disappearing. It spread through managers, through hallway conversations, through the accumulated experience of people working alongside each other every day. A lot of that infrastructure is gone or going.
Stacey doesn’t mince words about what that requires: “Culture has to be something that you’re practicing actively. It can’t just be on a poster in the lunchroom anymore. It’s gotta be something that you’re infusing in all of the different ways that you’re creating, forming, and maintaining teams.”
That starts with values – not the polished version on your about page, but the behavioral version that tells people what you actually expect of them. If curiosity is a value, what does that look like on a Thursday? Who’s expected to push back in a meeting, and how? As AI agents join team workflows, those same questions extend to them. Who is responsible for onboarding an AI agent into your culture?
We think marketing has a role here that most organizations haven’t considered. Marketers study human influence for a living – how to shift behavior at scale, build shared language, and connect people to an idea in ways that stick. Those skills aren’t just for external audiences. They’re exactly what’s needed to make culture something people practice, not just something they can recite.
Three Levels of AI Maturity – and Why Most Organizations Are Stuck
Stacey references a framework from NAMDA and MIT that maps organizations across three stages of AI adoption:
- Level 1 – Productivity: Using AI to do known tasks faster. This is where most people start.
- Level 2 – Agentic Automation: Understanding processes well enough to delegate entire workflows to AI agents.
- Level 3 – Net New Value: Using AI to generate entirely new revenue streams through recombinant ideas and novel business models.
Most organizations are hovering between levels one and two. Getting to level three requires leadership speed that most large organizations simply don’t have right now. The current average is nine months from idea to pilot – and by then, the window has often closed.
There’s also a warning embedded in level two that doesn’t get enough attention. Agentic automation doesn’t just change what work gets done – it forces people to behave differently. Most organizations haven’t thought through what that means for team dynamics, trust, or culture.
The Human Work Doesn’t Go Away – It Gets More Important
There’s a version of the AI story that treats human skills as the thing that gets left behind. This conversation points the opposite direction. When AI takes over task management and workflow routing, what remains is the work that has always been hardest to systematize: building trust, reading people, making judgment calls in ambiguous situations, and maintaining a culture that holds up when no one is watching.
The organizations best positioned for what’s coming aren’t necessarily the ones that have adopted the most tools. They’re the ones investing in team cohesion, behavioral leadership, and a culture that’s practiced rather than posted. That’s the foundation that makes AI adoption genuinely generative, rather than just faster.
If you’d like to think through what this means for your team structure, leadership development, or culture strategy, reach out to The Marketing Blender. It’s one of our favorite conversations to have.
FAQs
What part of an organization is most affected by AI in the workplace right now? Middle management is where the pressure is hitting hardest. AI is increasingly capable of handling the task-parsing and workflow direction that mid-level managers traditionally owned. The challenge is figuring out what fills the connective role that layer provided – and how to build teams with enough autonomy to function without it.
How does behavioral leadership differ from traditional leadership development? Traditional leadership development tends to focus on stable personality traits. Behavioral leadership focuses on what someone actually does under pressure, in the moment. Behaviors can be observed, coached, and tracked over time. That makes them a more useful lens when the environment is shifting faster than any single framework can keep up with.
Why is team culture harder to maintain as AI adoption increases? Culture has always traveled through informal channels – shared spaces, daily interactions, the accumulated context of working alongside the same people. As middle management shrinks and remote work reduces those touchpoints, those channels narrow. Culture doesn’t disappear, but it stops spreading on its own. It has to be deliberately built into how teams are formed, how they communicate, and what they’re rewarded for doing.
