Anna’s Story – When Leadership Meets Automation

Anna, a project manager, saw AI take over her workflows and move faster than she could ask for input.  Like everyone, she knew she couldn’t compete and didn’t want to spend her career auditing with AI output. This is where she saw her role heading. Until she realized her most powerful capabilities couldn’t be coded: her own communication and system thinking.

Stories from the Frontline of Capability Transformation

Anna used to describe her job as “herding cats while juggling calendars.” As a project manager in a mid-sized marketing firm, she lived in spreadsheets, color-coded timelines, and caffeine. She was good, great even. Her boss once joked that if Anna left, the company would need two people and a therapy dog to replace her.

Then came the rollout.

It started innocently enough: an AI platform that promised to “streamline project workflows and boost efficiency by 37 percent.” Anna liked efficiency. Who doesn’t like finishing a meeting before the coffee gets cold?

But by week three, the AI wasn’t just supporting her, it was anticipating her. Before she could assign a task, the system already had. Before she could update the timeline, it had optimized it. Before she could say, “Can someone check this copy?” it was already flagged, rewritten, and sent for approval.

Anna stared at her screen one Tuesday morning and realized she had become the person watching the project happen rather than running it.

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The five-minute meeting that broke her brain

During the first AI progress stand up, the team stared blankly while the system summarized their updates in real time. It even cracked a joke about “human latency.” The joke landed, just not in the way the developers hoped.

Afterward, Anna whispered to her colleague Armita,

“I think I just got outperformed by a chatbot with better timing.”

Armita shrugged. “At least it can’t steal your coffee.”

For now, Anna thought.

Existential dread, but make it productive

That night, she did what every professional in quiet panic does: opened a new spreadsheet titled "Contingency Plan If I Become Redundant".

But as she stared at the blank cells, something shifted. What exactly was she worried about losing? Her job? Sure. Her salary? Obviously. But beneath that was something else: the sense of being the hub, the translator, the glue that held chaos together.

AI could predict timelines, but it couldn’t sense when a designer was burning out or when a client was pretending everything was fine right before a meltdown. Anna could. That was her real work, the invisible kind that made teams functional.

So she started listing capabilities instead of tasks:

• Reading the room before the meeting starts

• Knowing when to escalate and when to let silence do the work

• Explaining technical chaos

• Making people laugh when deadlines looked like doomsday

By midnight, the spreadsheet didn’t look like a contingency plan. It looked like a capability map.

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The accidental experiment

The next week, Anna decided to test a theory: if AI was going to automate her "tasks", she’d automate it back.

She asked the system to draft a communication plan for a tricky client. It produced a perfectly structured, soulless masterpiece. Anna replied, yes, to the bot, with, “Now make it sound like someone who actually likes their job.”

The AI apologized (“I’ll do better next time, Anna”) and rewrote the plan with emojis and forced enthusiasm. She laughed so hard she startled her cat.

But when she compared the two drafts, something clicked. The first version was efficient. The second was empathetic. Neither was quite right, but together, they were something new: a workflow that paired machine speed with human nuance.

That became her new capability: designing the handoff between human and AI judgment.

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The Slack confession

At Friday’s team meeting, Anna told her boss she was running “a little experiment.” “I let the AI write the communication plan,” she said, “but I kept the parts where people might cry.”

The team laughed. Her boss raised an eyebrow but admitted the client loved it. “Whatever you’re doing,” he said, “keep doing it.”

That afternoon, she renamed her spreadsheet "Project Phoenix" because apparently, she was rising from the ashes of automation with better timing and a better joke.

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The realization

By October, Anna had stopped worrying about being replaced. She started teaching her team how to use the AI more like a partner than a threat, running small capability sprints to see what parts of their work were purely mechanical and which were deeply human.

The surprising part? The AI got better, but so did they. People spoke up more. They redesigned processes that hadn’t been questioned in years. And Anna discovered her unofficial new role: AI Capability Manager.

She still jokes that she works for a robot now, but she’s the one training it in office politics.

Coming 27 December: Anna’s Story Part II Redeploying Leadership

Anna’s company announces a second automation wave. This time, entire departments are being restructured. Instead of waiting for the fallout, Anna leads a Capability Reset Lab inside her firm and discovers what it means to design redeployment instead of fear it.