(Good) Product Ops is Still the Backbone
Yes, because we've had enough time to know what bad looks like.
We’re all in this weird moment where everything feels so damn loud and fast. AI is everywhere, every tool is suddenly “transformational,” and product management is evolving so quickly that even the most seasoned PMs are struggling to keep up. I open LinkedIn and feel my brain buzzing…and not in a good way. It’s the Instagram way, where everything feels too perfect or too horrible, and the in-between norms are lost.
Underneath all of this noise in our space, one question keeps coming up in conversations with PMs, leaders, and teams I work with. With everything changing this quickly, what actually holds a product org together? What makes it work in the real world, and not just on a board slide?
The answer is not flashy and it’s not going to win any hype. But it keeps showing up in the data, in the stories, and in the companies that are quietly thriving.
Product operations is still the cornerstone. Not despite AI and the tool explosion, but because of it. And when I say product operations, I mean ‘good product operations’.
The data keeps pointing in the same direction
McKinsey looked at more than 400 companies and found that those with mature product operating models - the ones with the systems, practices, and foundations product ops usually owns - see 60% higher shareholder returns and 16% higher operating margins than those in the bottom half. They also report 38% higher customer engagement and 37% higher brand awareness.
So clearly, when the operating model is strong, everything else tends to perform better. This is evident in companies where the strategy lands well, everyone is aligned, teams know what they need to execute on and how long it will take to do it, and customers ultimately feel the difference.
The funny thing is almost every post and report I read still shows the same tension. Most organizations now have “something” called product ops, but role clarity is consistently the number one challenge. When it’s not done well, we’re just creating a presence without definition and that is not going to serve any of us well.
We’ve changed because of AI, but we really haven’t changed.
In my conversations with customers, especially PMs and product leaders, one pattern is obvious. AI is no longer just a feature or a bullet point. It’s shaping how we build, how we ship, and how we make decisions. Like every decision from business outcomes to tooling to staff. Expectations on PMs keep stacking at the same time: be AI‑literate and AI-forward, be more data‑driven, move faster, stay lean, and still be accountable for outcomes, not output (but also be accountable for output because people don’t get product management).
The fundamentals haven’t magically disappeared from our discipline. Products still need to ship. Teams still need to collaborate. Someone still has to make sure data gets to the right people at the right time, that we’re not reinventing the wheel every sprint, and that product, engineering, sales, and success stay connected instead of drifting into their own worlds.
That “someone” is product ops.
As complexity increases, AI adds new layers, and tools multiply, the need for strong operational foundations doesn’t go away. For the smart ones it’s non‑negotiable. Product ops as a thing we need to do isn’t getting automated out of existence. It’s getting pulled closer to the center so teams can navigate all of this change without burning out or losing sight of what matters. That is the success of the PM, designer, and engineer, and the outcomes their pods are accountable for.
The work you feel more than you see
I’ve built product ops from scratch in a few flavors now. I’ve had fully staffed teams, shared ownership, and messy hybrids, done it myself (pain. pain. pain.), and the thing I’ve learned is this: the best product ops work is often invisible. When it’s working, no one calls it “product ops.” PMs and engineers just have what they need to plan and move efficiently. The data is there for execs and leaders. The process feels natural. Communication flows seamlessly across teams. The thing ships and delivers value.
That invisibility is a blessing and a curse. I’ve called it “the curse of competence” for years. It’s when you’re really good and people stop noticing the effort behind the ease.
Productboard’s data reflects what many of us already know: 93% of product ops teams drive cross-functional alignment, 90% manage processes and workflows, and 81% own tools and platforms. None of that is glamorous. All of it is essential.
On the ground, product ops is the team making sure customer feedback doesn’t die. Often it does in Slack threads, buried emails, and random JIRA tickets. They’re working with Sales and CS to design the systems that help teams stop arguing and start deciding, and maintain a single source of truth so product, engineering, sales, marketing, and success are actually looking at the same picture and the same customer pain.
What’s good lately is I see more and more they’re the ones helping teams adopt AI in a way that’s useful and ethical. They’re helping to put guardrails around experimentation so we don’t give up our credibility for the sake of speed.
Product‑led growth runs on (really) good ops
Product‑led growth sounds exciting on paper to everyone. Your product drives acquisition, retention, and expansion. Wooh! Sales, marketing, and success get to lean into higher‑value work because the product is doing more heavy lifting.
Yet, here’s the part we gloss over: that is an enormous operational challenge. If users can discover, sign up, onboard, and get to value without talking to a human, every part of that journey has to be designed, instrumented, and maintained. There is no “we’ll fix it live on the next call” safety net.
Product ops is what makes that possible in modern product teams. They centralize and standardize feedback loops so you know what’s working and what’s breaking as you scale. They make sure product data actually flows to the teams using it for planning and reporting. They create the consistency that lets you grow without everything fraying at the edges. This is not project management in disguise. This is building an operating system the whole company runs on, and as a former colleague of mine once said, “they are the peripheral vision for the PM.”
The AI paradox
AI will absolutely help us and it already does. Clearly, it can process massive volumes of feedback, generate drafts, and highlight patterns we might miss. But it also raises the stakes for those of us who are transforming to AI forward. Data quality issues become critical when you’re feeding multiple models. Integrations get messier as you add AI onto an existing stack. And of course, governance and compliance get harder when algorithms are doing work humans used to own.
The real challenge isn’t “Can we use this tool?” It’s “Does this make our system better, or are we just adding more noise?”
This is where strong product ops shines. They’re the ones who zoom out and ask:
Is this solving a real problem, or are we chasing this month’s hype?
How will we measure whether it’s actually helping?
What processes and responsibilities need to change to support it?
Who is accountable when something goes sideways?
My own experience keeps confirming something: adoption is almost never blocked by technology. It’s blocked by trust, skills, habits, and change fatigue. Those are people and process problems. Product ops is often the function that builds the systems and support that make new ways of working stick instead of becoming “that thing we tried for a quarter.”
Measuring what actually matters
There’s one question I hear all the time: “What does success look like for product ops?”
I’ve led and seen teams who anchor on hard numbers like time saved for PMs and GTM teams, reduced support tickets, increased adoption (shared with PM), or faster time‑to‑market. There are also those who lean into softer indicators like PM satisfaction, stakeholder alignment, and overall team health. The truth is, both matter for lots of reasons, and they all lead to a better experience for the customer.
The strongest product ops teams blend the two types of measurements. They track whether PMs are spending more time with customers and on strategy instead of constantly firefighting. They also look at whether customer feedback is showing up in roadmaps at the right time and influencing sentiment and renewal. They definitely pay attention to whether cross‑functional partners feel more aligned and less frustrated, or as I like to say more ‘ready’.
When product ops is working, you feel it ripple out. Sales and SEs get sharper on the product. Success teams get better, earlier, meaningful enablement. Engineering sees clearer priorities and a stronger line of sight from their work to business outcomes. And when the system is strong enough, leadership gets a cleaner window into what’s actually happening on the ground and stops bothering several people with the same questions.
I will say that none of this works without measurement. The PLA data shows that only seven percent of practitioners report high levels of automation, 19% of centralized teams have dedicated cross‑department liaisons, and 21% of product ops teams aren’t formally measuring their effectiveness at all. That last number stings, and it’s fixable.
Why this matters right now
I wish I could say every company fully understands the value of product ops. We know that isn’t true as some of that noise on LinkedIn shows me that all the time. Also, budgets get cut, teams get re-orged, and leaders change.
But I would point you to those who are actually thriving at this moment. It’s not the companies shouting the loudest about AI features or adding the most tools. It’s the ones with strong foundations and the operating models that let them move quickly, take smart risks, and adapt without spinning their people into the ground.
Product operations is that foundation when it’s got buy in from the top. It’s the steady heartbeat behind the product‑led story and the connective tissue that turns partners of the product team into one unit. When it’s done well, it drives the operational excellence that lets that unit scale.
I want to be clear that this isn’t about glorifying process, and I think most of us know those words have been negatively associated with product ops too many times. It’s about acknowledging that in a world of constant change, the ability to operate well is the difference between growing and slowly, painfully grinding to a halt.
What this means for you
If you lead product, treat product ops as a strategic multiplier, not a nice‑to‑have or a dumping ground for “stuff no one else wants.” Done well, it accelerates the entire org.
If you’re a PM, lean into the partnership. Product ops isn’t there to make your life more annoying and create bureaucracy. They’re there to give you back time and headspace so you can stay closer to customers and the problems that actually matter. That’s your job, so use what you can to do it well.
If you’re in product ops, keep fighting for clarity and keep talking about your impact. One of the best pieces of advice I got from a manager was this: sharing progress backed by outcomes is not bragging. A lot of us in the product world prefer to be the quiet doers. The work you’re doing is too important to stay quiet about.
And if you’re building a product‑led organization, please don’t convince yourself you can “add ops later.” The product might be the engine of growth, but operations is what keeps that engine running as you scale. The cost of fixing foundations later is almost always higher than investing in them early.
At the end of the day, product management has always been about connecting dots between customer needs, business goals and technical realities. Across those three, there are many friction points and sensitivities. We rarely own the people, but we’re responsible for bringing them together to build something meaningful.
Product operations does the same thing, just at a different altitude. It connects the systems, processes, and people that make great product management possible at scale.
In a world full of AI tools, frameworks, and constant change, that connective work is more valuable than ever. It’s too easy to get disconnected today with all the noise. While it’s not the hype role, the data highlights its value.
Now that it’s been here long enough, we can spot the difference in the outcomes or lack of them.