I’ve been in this industry long enough to see a few technology waves come through. But I can’t remember a time when the gap between what’s possible and what’s actually happening in AI production has been this wide.
I was reading through the recap from Cisco’s AI Summit, where Matt Garman, Jensen Huang, Sam Altman, Marc Andreessen, and about a dozen other leaders who are literally building the AI economy, all came together.
And one thing really stood out at me.
Despite representing very different companies and perspectives, they kept circling back to the same point: the AI adoption challenge for businesses isn’t models or infrastructure anymore. It’s clarity. Trust. And all that legacy friction we’ve been dragging around
The technology isn’t the issue anymore. The models work. The infrastructure is there. But most businesses are still stuck in proof-of-concept mode, unable to get AI running reliably in production. That’s not a technology problem. That’s an execution problem.
Why Business AI Adoption Stalls: Too Many Options, Not Enough Direction
The thing about the AI market right now, is that it’s massive. There are a hundred different areas where you could move the needle, which is great, but also the problem. Companies are drowning in options while simultaneously starving for direction.
What really struck me from the summit wasn’t any single announcement, but how consistent the themes were:
- Customers don’t lack AI tools. They lack clarity on what they’re actually trying to accomplish.
- Data governance and trust are prerequisites, not nice-to-haves. And most organizations aren’t there yet.
- Legacy systems aren’t just inconvenient — they’re actively blocking AI adoption.
- Pilots that never make it to production? That’s the norm, not the exception.
If you’re a partner in this space, the message is clear: stop selling more AI tools. Start helping your customers actually use them.
Related Read: ENTERPRISE AI GOVERNANCE: HOW TO PLAY DEFENSE WHEN YOU CAN’T STOP EVERY YARD
5 Ways to Move from Pilot Mode to AI Production
Based on what came out of this year’s AI Summit, I see five specific areas where execution-focused partners can genuinely differentiate and actually move from pilot mode to AI production.
1. Outcome-Driven AI Strategy: Start with the Outcome, Not the Platform
Why do so many AI projects never make it past the pilot phase? Because the organization started with a platform, built a POC, and only then tried to figure out what business problem they were solving.
It’s backwards. You can’t retrofit purpose into technology.
Ask the hard questions up front:
- What process needs to improve?
- Why does it need to improve?
- How will you measure success?
- What does production actually look like for this specific use case?
Get clear on these answers first, and then talk technology.
AI Data Readiness and Governance: Make Data Usable, Not Just Accessible
Almost every speaker at the summit came back to the same theme: data access, governance, security, and guardrails. You can have the most powerful model in the world, but if your data is siloed, ungoverned, or untrusted, you’re not going to move forward.
This is where partners who can work across cloud, data, security, and networking really stand out. Transforming data to be AI-ready requires collaboration across multiple disciplines, and most organizations struggle to coordinate all those moving parts on their own.
Without trusted, accessible data, every AI investment is dead on arrival.
3. Reframe Legacy Modernization as AI Enablement
Tech debt and outdated workflows also came up again and again as blockers of AI enablement. The organizations that want to move fast are being held back by infrastructure decisions made a decade ago.
They need to flip the script and remember that modernization isn’t as simple as IT cleanup. Modernization is what makes AI possible.
Every legacy system you address and every workflow you streamline removes friction from your AI roadmap. When you position it that way, it stops being a cost center conversation and becomes a strategic investment.
4. Hybrid AI Infrastructure Management: Curate the Ecosystem, Don’t Try to Replace It
Customers don’t need another platform vendor. They’ve got plenty of those. What they need is help integrating and operating hybrid AI environments across all the platforms they’re already using or are in the process of evaluating.
Strong partnerships with Cisco, AWS, Microsoft, NVIDIA, and others let you help customers navigate choices instead of adding to the confusion. You become the guide, not just another option to evaluate.
That’s a fundamentally stronger value proposition, and one your customers are actually looking for.
5. AI Production Operations and Lifecycle Management: Start Now and Keep it Running
This one hits close to home.
Trust deficits, operational gaps, and a lack of lifecycle management are all reasons why AI pilots never graduate into full AI adoption. The demo works great. The POC impresses everyone.
And then? Nothing.
Because nobody can figure out how to run it in production with the governance, security, and reliability the business actually requires.
If you’ve got managed services capabilities, this is your moment. The partner who can take AI from pilot to production (with real security, monitoring, and ongoing support) is solving the single biggest blocker to AI adoption.
Without this capability, you’re not in the AI business. You’re just selling demos.
Execution Will Define the Next Phase of AI in Business
This year’s AI Summit delivered absolute clarity on where the market is headed. Differentiation can’t come from building better models or infrastructure, it needs to come from helping customers actually operationalize what they already have.
The winners in this space will be the partners who can move customers from ambition to production. Not the ones selling more tools to evaluate. Not the ones delivering another impressive demo. They’ll be the ones who will actually get AI working in the business, at scale, and on the outcomes that matter, with the governance and trust organizations require.
That’s where I see the opportunity. And that’s exactly what we’re building toward at Presidio.
If you’re ready to move beyond pilots and into AI production, that’s a conversation worth having. Connect with our team to talk through where you’re stuck and what it will take to get your organization’s AI into production securely, reliably, and at scale.
Michael Kelly
Michael Kelly is the Senior Vice President, Digital at Presidio. He is passionate about the growth and development of his team and the success of Presidio's customers. Prior to joining Presidio in 2015, Michael spent 11 years at EMC within its Commercial Sales Division building and leading one of the highest revenue producing commercial sales teams in the country. Michael holds a bachelors of science in business from Northeastern University.
