In the fast-changing world of enterprise software, the conversation has long revolved around innovation, agility, and scale. But a quieter transformation is happening behind the scenes that is redefining how products are conceived, built, and delivered. This shift is driven by a function many companies are only now beginning to recognize: product operations.
Product operations, often called ProdOps, is emerging as the connective tissue between product management, engineering, data, and customer success. Its purpose is simple but transformative: to make the product development process more efficient, data-driven, and aligned with business goals. For years, organizations have focused on improving how they build software, but not necessarily how the system of building software operates. Product operations changes that.
Bridging strategy and execution
At its core, product operations ensures that product teams have the right infrastructure, processes, and insights to make better decisions. It brings together the analytical discipline of operations with the strategic thinking of product management, creating a clearer path from idea to market. In traditional development environments, there are often gaps between product managers defining requirements, project managers tracking timelines, and engineers building the technology. As companies scale, those gaps can widen, leading to duplicated work, missed deadlines, and inconsistent results. Product operations help close those gaps, creating systems that promote visibility, accountability, and speed.
In many large enterprises, product data is spread across different tools—Jira for sprints, Salesforce for customer feedback, Tableau for analytics, and internal systems for operations. Product operations professionals consolidate this information into unified dashboards, giving leaders a single source of truth. That visibility allows teams to anticipate problems before they happen and align priorities based on measurable impact.
When I led an enterprise-wide software rollout in a healthcare system, consolidating fragmented data from multiple legacy systems and reporting tools helped increase reporting efficiency by over 65% which enhanced decision-making in the organization. This meant that cross-functional teams, such as finance, procurement, and IT, could work from a single source of truth, increasing trust and transparency and reducing manual back-and-forth.
The merging of product and operations skills
One of the most significant trends shaping enterprise software is the blending of traditional roles. Product managers, business analysts, and project managers once worked in clearly defined lanes, but today the most effective professionals draw from all three disciplines, combining strategic vision with operational precision.
Companies are increasingly hiring people with hybrid skill sets that merge product strategy with process optimization. These professionals understand both the “why” and the “how” of building great products. It’s no longer enough to write user stories or manage backlogs; modern product leaders are expected to analyze data, design workflows, measure efficiency, and lead cross-functional collaboration.
This convergence is natural. Over the past decade, agile, DevOps, and continuous delivery practices blurred the line between development and operations. Now, product operations is blurring the line between product and operations, ensuring that every decision is backed by evidence and executed with discipline.
I have seen over the years how the traditional disciplines in product and agile teams have evolved in large organizations vs. in startups. Enterprise companies tend to have specific roles and job duties for different departments, whereas in a startup, the same individual is often expected to wear multiple hats. More commonly these days, we see project manager and scrum master roles merging into one, while business analyst, product owner, and product manager roles are converging into a single role. This trend is expected to continue, especially with AI coming into the picture, so individuals should embrace upskilling to continue enabling operational delivery, strategy, and roadmaps alongside AI to stay ahead of the game.
Why enterprises are paying attention
The rise of product operations is also a response to a changing marketplace. Enterprise customers expect faster updates, responsive support, and consistent performance. That pressure puts product teams in a constant balancing act between speed and stability. Product operations provides the structure to maintain both.
It standardizes best practices across teams, introduces repeatable workflows, and ensures that decisions are guided by both customer data and operational metrics. Companies adopting product operations frameworks often see faster release cycles, fewer delays, and stronger alignment between departments.
A well-structured product operations function also serves as the organization’s operational conscience. It ensures that teams don’t just move fast but move intentionally. By creating feedback loops between customers, sales, and engineering, product operations shortens the distance between insight and action.
In one of the EHR scheduling integrations I led previously, the operations team had been receiving constant pushback from the clinicians’ office because of a missing approval documentation needed to see patients. Upon further investigation, I noticed how the system that the scheduling team used vs. what the nurse practitioners were using had significant differences in UX layout. By analyzing workflow gaps and integrating necessary UX fixes for real-time scheduling visibility and automating the process, we were able to resolve the issue that increased physician satisfaction scores, reduced redundant paperwork, and enhanced physician block utilization and rounding times, so they were able to spend more time providing care for the patients. This showed how data-driven prioritization and automation of operational workflow can translate feedback into measurable improvement.
The next wave, AI and accountability
As AI and automation continue to shape enterprise technology, product operations will only become more important. AI can generate insights, optimize workflows, and predict outcomes, but those capabilities mean little without the right operational framework. Product operations ensures that those insights reach decision-makers quickly and are acted on effectively.
It also brings accountability in an era of remote teams and global collaboration. With development spread across continents and time zones, coordination is more complex than ever. Product operations offers a governance model that balances flexibility with control, allowing teams to innovate while staying aligned on goals and outcomes.
If product teams today are not leveraging AI, they are surely missing out on opportunities to build more sophisticated and competitive products. Traditional product lifecycle vs. AI product lifecycle has significant differences, and even if teams are not building AI products specifically, they can still use AI tools in all three phases, discovery, delivery, and distribution, increasing efficiency in building 0 to 1 products. Today’s AI tools can help with market research, competitor analysis, and faster documentation. In healthcare settings, AI-powered workflows or copilots can help save clinician and admin time, and leaders can make more informed decisions from AI-predictive insights rather than relying on manual spreadsheets or manual status collection.
Looking ahead
Many in the industry believe that roles like product manager, business analyst, and project manager will eventually merge into a single, more strategic role. This future leader will combine customer understanding, operational excellence, and data fluency. The next generation of product professionals won’t just manage individual products; they’ll manage the systems that make product creation possible.
Product operations will be at the center of that transformation. As organizations look to scale efficiently and deliver value more quickly, it will become a necessity. The companies that embrace this function early will be the ones best positioned to build not just better products, but better systems for creating them.
Product operations will continue to evolve as a capability that aligns governance, compliance, operations, data, and execution in regulated fields, enabling enterprises to achieve sustainable value in the ROI for their products. With AI shaping the future of regulated tech, ProdOps will serve to balance compliance with AI-driven innovation.
This is an exciting time to be part of that evolution. The conversation is shifting from how we innovate to how we operate, and product operations is leading the way.
