SuperOps Plug
The price of waiting on agentic AI
SuperOps Plug
The price of waiting on agentic AI
You've probably used agentic AI this week.
Summarized a ticket, drafted a response, automated a triage.
But somewhere between using it occasionally and running it in production -- in live service desk environments, handling real customer workflows -- most MSPs and IT teams are stuck.
Every month that gap stays open, the teams on the other side are getting better.
Their systems are learning, their data is accumulating, their technicians are building muscle.
And the distance between them and everyone else isn't staying the same size.
It's growing.
A recent survey by Omdia, conducted in partnership with SuperOps, put a number on that gap.
Around 70% of organizations say they're using agentic AI in some form.
Actual production deployment sits at roughly 10%.
And roughly 30% of MSPs aren't using agentic AI at all.
"Hesitation doesn't keep you neutral here," says Jessica, principal analyst at Omdia and author of the report.
"It compounds the disadvantages over time."
At the launch of the report, Jessica sat down with Damo Vasudevan, VP of Product at SuperOps and an AI practitioner who builds agentic systems for MSPs and IT teams, to dig into what the data means on the ground.
The gap is coming from both sides
And the pressure isn't only coming from competitors pulling ahead.
It's coming from clients too.
More than 40% of MSPs report that over a third of their customers have already deployed some form of agentic AI in 2025.
A majority expect that number to exceed 40% by 2028.
Your customers are moving.
And they're going to expect you to keep up.
"Customer expectations are clearly moving faster than MSP operational readiness," Jessica says, "and historically, when these gaps form, they tend to widen before they narrow."
For internal IT teams, the pressure shows up differently -- it comes from leadership.
When your CEO is looking for AI initiatives that show value, being the team that hasn't moved yet is a hard position to defend.
It's a growth story, not just an efficiency one
The hesitation conversation tends to get stuck on risk.
But Damo frames it differently -- as a capacity story.
A technician today manages roughly 150 to 200 endpoints.
With agentic AI embedded in the workflow, that number goes to around 500.
That's not a marginal improvement.
That's an entirely different business.
"Imagine the capacity you now have to go acquire new customers," Damo says.
"And just have a better quality of life as a technician or as an MSP."
For internal IT teams, the benefit lands differently -- it's the productivity gains and the strategic seat at the table that opens up when your team isn't buried in repetitive work.
PE is paying attention
For MSP owners thinking about exits or growth capital, the stakes go further than day-to-day operations.
PE firms are now evaluating MSPs on how deeply AI is embedded in their operations.
"We're also seeing private equity firms evaluate MSPs based on the efficiencies they've built through AI," Jessica notes.
"If you delay the journey, it gets harder to compete every year."
Damo echoes this from his own recent conversations with PE firms.
"The ones with AI embedded are the ones they're betting on for growth."
AI maturity is no longer a nice-to-have.
It is becoming a variable in how your business is valued.
The side dish trap
For many MSPs, the response to all of this isn't inaction -- it's the appearance of action.
Experimenting with AI, adding it as an occasional tool, moving on when it doesn't immediately transform operations.
It's easy to mistake this for progress.
"The MSPs that really adopt and restructure their whole business workflow and technician workflow, they are the ones getting the best value," Damo says.
"That discomfort is where the value is."
Around 40% of organizations try agentic AI and fall off.
Only 10 to 20% genuinely operationalize it by year's end.
The cost of half-adoption isn't just wasted effort.
It's the opportunity cost of time spent experimenting without building anything durable.
This pattern has played out before.
In the previous automation cycle, the MSPs that committed grew significantly and positioned themselves for strong exits.
The ones that waited fell behind in ways that became progressively harder to recover from.
Agentic AI is the same pattern -- with a bigger lever and a faster clock.
The gap between the 70% and the 10% won't stay that wide for long.
The question is which side of it you're on when it closes.
The Autonomy Advantage, the full Omdia report commissioned in partnership with SuperOps, goes deeper into the data behind this story -- including a staged roadmap from assistive to autonomous IT operations, practical action plans for MSPs and IT teams, and what it actually takes to move from experimenting to operationalizing.
Scan the QR code to download your copy.