The AI Engineer Isn’t Just a Role — It’s the Next Organizational Capability

Last week I had some incredible conversations trying to unpack what it really means to have an AI Engineer, GTM Engineer, or Forward-Deployed Engineer inside a company. Even had a bunch of great conversations at the ApolloNext event, which is obviously a GTM focused event!

I chatted with a fascinating mix of leaders — the Head of GTM Operations at Anthropic, the Founder of an agentic finance startup, the CFO of an AI database company, Matt Curl - the COO at Apollo, and even ran into Corporate Bro (Ross Pomerantz) and a few others who are all shaping what AI maturity looks like inside their organizations.

And there was one thing they all agreed on — every company today recognizes the need to build AI maturity internally.

Most of these companies have already moved past the first step — buying AI tools or platforms. They’ve invested in foundational technology that gives them secure environments to build and deploy AI safely.

See the Infographic below, where McKinsey clearly identifies that companies are investing in GenAI - 92% of them, but only a cool 1% have achieved maturity.

Getting your people to be AI-ready is HARD.

The gap isn’t the technology anymore. It’s the capability and mindset to use that technology effectively.

Many leaders told me that not only do their internal teams still struggle with adopting AI in a meaningful way, but their customers often sit in the same boat.

Simply procuring technology and checking the “AI” box is no longer enough. What’s effective now is having someone inside your organization who understands your workflows, deeply, and can spot where automation and agentic systems can free people from repetitive, low-leverage work.

That’s the new competitive edge!!

Even for people like me — who live and breathe in AI conversations every day — I can feel how this plays out.

Yes, I’ve replaced a lot of my Google searches with ChatGPT queries. But I’m still not excited about typing out 50 lines of context to get a sophisticated response.

The prompt fatigue is REAL. You reach a point where you’d rather do the manual task than try to coax a perfect answer from the model. And when the system doesn’t get it right the first time — the frustration compounds.

For most business users, that’s the breaking point. They’re not engineers, and they shouldn’t have to be.

This is exactly where the role of an AI Engineer or Forward-Deployed Engineer becomes transformative.

Imagine having someone on your team who understands systems thinking, has a background in computer science or data, and approaches problems with first principles — not just plugging prompts into a tool, but architecting solutions.

Someone who can:

• Shadow your business workflows
• Identify repetitive and manual tasks
• Build, test, and deploy AI agents to automate them
• Integrate data across systems responsibly
• Measure ROI and time saved

That’s not just an efficiency boost — it’s organizational evolution to drive AI Maturity, up from that 1%.

Now imagine that same capability extended across every function — finance, HR, RevOps, support, marketing, and product.

The leaders I spoke with see this as a massive unlock. These AI Engineers and Forward-Deployed Engineers don’t just transform how internal teams work; they’re also being deployed on the customer success side to help clients build their own agents.

It’s an entirely new service layer — where companies aren’t just selling AI tools, they’re helping customers operationalize AI. Think #leverageinfrastructure

That’s exactly why we’ve doubled down at Exordiom Talent.

We’re building an AI Maturity Practice focused on helping companies go beyond buying AI software — by embedding highly skilled, globally sourced AI Engineers who can turn ambition into execution.

For a fraction of the cost of a U.S.-based hire, companies can onboard talent that’s already fluent in LLMs, data integrity, and agentic design — and ready to get their hands dirty automating workflows, building AI copilots, and driving tangible ROI.

Because true AI maturity doesn’t come from purchasing technology — it comes from deploying the people who can operationalize it.

Every company I spoke with — from startups to mature AI-driven organizations — is realizing this same thing:

The future won’t be defined by who buys the best AI tools. It’ll be defined by who builds the best internal capability to use them.

So if you’re leading a function and wondering what it means to get your organization “AI ready,” start here:

• Look at where your team spends the most time on repeatable, manual tasks.
• Identify who could benefit most from intelligent automation.
• Then think about who’s going to build that automation for you.

That’s where the AI Engineer — and the forward-deployed model — comes in.

And that’s where we at Exordiom Talent are helping companies evolve.

👉 If you’re thinking about how to accelerate your AI maturity journey and embed true agentic capabilities within your teams, let’s talk.

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