AI Didn't Replace Me

It Replaced the Gap Between Who I Was—and What I Was Capable of Becoming.

Early in my career, I sold technology I didn't fully understand.

I worked at SAS Institute, talking to customers about advanced analytics platforms while privately realizing an uncomfortable truth: I didn't understand the underlying technology deeply enough to explain why it worked—only that it worked.

Nothing about that situation made me unqualified. But it did make my ceiling very clear.

That tension became the defining moment of my career—not because I was replaced, but because I recognized a gap between my role and my potential.

AI didn't create that gap. It helped me close it.

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Owning the Gap

Like many early-career professionals, I was successful on paper. But I knew intuition wasn't enough. If I wanted to grow, I needed to understand the systems shaping the technology I was selling.

So I took ownership of my learning.

I started with Azure certifications—foundations, cloud, and AI—to build real technical fluency. Not to change my title, but to change how I thought.

That learning led to a more formal commitment: a Master's in Applied Analytics from Columbia University. My goal wasn't academic prestige. It was simple—to move beyond buzzwords and develop the ability to translate data, analytics, and AI into real-world outcomes.

At the time, none of this was automated. There were no copilots summarizing coursework, accelerating research, or turning questions into structured learning paths. Progress required brute effort.

What I didn't realize then was that I was building the mental models AI would later amplify.

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Why Networking Was the Real Force Multiplier

One of the most important investments I made during that period wasn't technical—it was relational.

I stayed in touch with a professor who later became the head of an AI business development and consulting organization. Not through formal programs. Through disciplined follow-up, curiosity, and persistence.

That relationship ultimately became pivotal when I joined Google as a sales rep—still technically adjacent, but increasingly focused on AI-driven solutions.

At Google, opportunity didn't come from résumés. It came from initiative.

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The 20% Project That Changed Everything

Google's 20% program is well-known, but often misunderstood. It's not "permission" to explore—it's expectation that you'll own your growth.

There happened to be a 20% opportunity open in Generative AI—on the team led by the same professor I'd stayed connected with for years.

I volunteered.

What followed wasn't a pivot handed to me. It was work I had to earn—learning fast, synthesizing ideas, and bridging business problems with emerging AI capabilities.

That project didn't replace my role. It expanded it.

And here's the part that matters now: the work required clarity of thought, pattern recognition, and judgment—not just technical execution. Exactly the kind of work AI now accelerates.

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The Truth About AI and Careers

Looking back, the story isn't that AI changed my career. It's that AI would have compressed years of friction.

Research, synthesis, follow-ups, learning paths, first drafts—these were the bottlenecks. Not intelligence. Not effort.

AI didn't replace my expertise. It removed the drag that slowed my growth.

That's the shift most headlines miss.

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Why AI Rewards the Prepared—Not the Curious

AI doesn't magically create high performers. It amplifies existing ones.

Because AI is only as effective as the questions you ask, the judgment you apply, and the context you understand.

The benefit I see today—from AI tools to multi-agent systems—isn't that they think for me. It's that they let me operate closer to my true cognitive ceiling, more often.

Which is why AI creates divergence—not equality.

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From Individual Productivity to Organizational Reality

The same principle applies to organizations.

AI doesn't eliminate people. It eliminates underutilization.

But only if leaders resist the temptation to deploy tools without structure.

Without governance, AI becomes noise:

• Disconnected copilots
• Unowned agents
• Tactical experimentation with no strategic arc

Real impact requires programs. Clear ownership. Shared standards. Execution discipline.

AI scales capability—but only where direction already exists.

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What I Tell Teams Now

When people ask me how to prepare for AI, I don't talk about prompt engineering.

I ask:

• Do you know how to learn?
• Do you know how to synthesize?
• Do you know how to connect ideas across domains?
• Do you know how to follow up, not just explore?

AI will magnify those abilities—and expose where they don't exist yet.

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Final Thought

AI didn't replace my job at SAS. It didn't replace my role at Google. It didn't replace my career.

It replaced the gap between who I was and who I was capable of becoming—once friction was removed.

That same opportunity now exists for every professional and every organization.

The question isn't whether AI will change your work.

It's whether you'll step into the space it just unlocked.