Daniel Gomez of Omnicon outlines what manufacturers now expect from SIs: repeatable frameworks, scalable architectures, trustworthy data pipelines and teams ready for AI-driven change.
Manufacturers still buy automation projects, but their expectations increasingly extend beyond a single line, cell or plant. They want solutions that can be repeated, supported and expanded — often across multiple facilities and regions — without re-engineering the approach each time. That shift is reshaping how system integrators (SIs) position their value and how engineering teams execute.
Daniel Gomez, CEO of global system integrator Omnicon, describes the market’s direction as a move away from isolated implementations toward architectures that enable ongoing transformation. The job, he argues, is no longer to solve everything in one deployment. It’s to deliver a foundation that makes the next use case faster, cheaper and less risky.
“It’s not just anymore about, we’ll implement a specific solution. Like, this one will be the one that solves everything,” Gomez said. “It’s more about, can it enable you with this architecture to solve those potential problems?”
Gomez shared these perspectives during an interview at the Control System Integrators Association (CSIA) conference in Baltimore, where Omnicon was recognized as a 2026 System Integrator of the Year by Control Engineering and Plant Engineering. For Gomez, a former controls engineer, recognition is meaningful, but the larger focus is what it signals about the future of engineering delivery: scalable practices, data maturity and resilient talent models.
“For us, it means like the Oscars of this industry,” he said.
Why global SI starts with focus and process
Plenty of integrators can execute technically complex work. Fewer can scale execution across multiple geographies while maintaining quality, schedule discipline and a consistent customer experience. Gomez points to focus and repeatability as the critical starting points.
“The first one will be focus, highly focused on where we can really add value to those customers with a specific niche and really have the people and the processes that support that,” he said.
That focus, in his view, must extend beyond a single engagement. The constraint is generally the ability to reproduce outcomes across sites.
“It’s not just the specific project, but also how you can deliver across different sites,” Gomez said.
Omnicon’s own growth reflects the delivery challenge. Gomez described the company as moving from “a single … delivery hub to multiple sites,” adding that it is now delivering projects “from the U.S., Mexico and Europe.” Multi-region delivery forces SIs to formalize what may have been tribal knowledge — standards, methodologies, review gates and commissioning expectations — so outcomes don’t depend on a few individuals.
For engineering leaders, adding engineers often increases variability faster than it increases throughput. Gomez frames process design as a prerequisite to scale, especially when serving large manufacturers with multiple plants.
Architecture is the differentiator
SIs often emphasize consultative selling, but Gomez ties consultative work directly to engineering outcomes. The goal is to define the real pain point, then design the solution and the long-term expansion path together.
“We shaped it from the beginning, from more a consultative approach,” he said of Omnicon’s early work. “It’s more understanding the pain points, what the real challenge is. Based on that, we frame the solution.”
What’s changed, Gomez argues, is the requirement that the solution be designed to scale. The question engineers increasingly have to answer is not only “Does it work?” but “What else will it make possible?”
“With that specific problem, how can we solve that issue but also at the same time that that solution could scale … in this specific site, but also in other sites,” he said.
That means integrators must think in architectures, not just deliverables. It’s about consistent naming and data conventions, reusable templates, repeatable interfaces between operational technology (OT) systems and enterprise applications, and a pattern that can be deployed across facilities without reinventing the design each time.
“They can build whatever is needed versus try to solve all the challenges out of the box,” Gomez said.
Frameworks that empower engineers
Standardization is often framed as a tradeoff: Either you get disciplined execution, or you get flexibility in the field. Gomez rejects that binary. He describes Omnicon’s approach as a structured framework that still leaves room for engineering judgment.
“Flexibility is key, but also it’s a combination between you need a process, but also having the right people to do their thing is very important,” he said. “We have a framework and the people will have … the ability and the innovation to shape it in the way that that really solves an issue for a customer.”
For engineering organizations, this is a management model as much as a technical model. A framework can enforce quality (documentation, reviews, validation methods, cybersecurity baselines), while engineers adapt to plant realities (brownfield constraints, vendor limitations, safety and regulatory requirements, production schedules).
SIs and data management
Gomez sees data as the pivot point for the next phase of SI differentiation. Traditional controls work will remain essential, but integrators who build real capability around data — collection, contextualization and operational decision support — will be positioned to create larger and longer-lasting value.
“In my point of view, data is the right point,” Gomez said. The transition, he added, depends on “how can SIs start building capabilities around the data management and help those companies make better decisions with the information they already have.”
That perspective reframes what digital transformation means on the plant floor. It’s not simply connectivity or dashboards; it’s turning process and production signals into trusted inputs for decisions.
“What we can bring as an SI is we understand what’s going on in the manufacturing world, but also we understand what’s the new technology that is available,” he said. The value, he added, is understanding what is happening in the facility and “transforming that into what is the right set of solutions that will help to solve that pain point.”
He describes system integrators as a community that continuously learns across domains to apply the right combination to specific operational constraints.
“partner for life” is an engineering strategy
In many procurement models, integrators can be treated as interchangeable vendors, selected on price and availability. Gomez argues that SIs who want to be durable partners must orient toward transformation instead of transactions, and prove it through execution.
“Our main focus is about long-term,” he said. “We’re really focused how can we transform that industry and really help solve issues versus a transaction.”
He described the goal as becoming part of the customer’s extended team when needed. That stance, he argues, is how long relationships are built.
“We have customers that have worked with us for the last 30 years,” he said. “They rely that you are the guys that will help them, and we will bring the right solution. … It’s more about how can we build trust in the long term.”
Talent planning and AI
If data architecture is one pillar of SI competitiveness, talent strategy is the other. Gomez believes SIs must look five years ahead and ask whether their workforce model matches the coming wave of AI-enabled engineering work and customer expectations.
“Do you have the right people for the next five years?” he said. “How technology will, AI will transform that — do you have a planning place for those?”
His point is not that AI replaces controls engineering. It’s that the pace of change will pressure integrators to rethink how they produce documentation, validate designs, manage knowledge and develop engineers who can bridge OT fundamentals with data-driven decision support.
What engineers and SIs should take away
Gomez’s perspective can be distilled into a set of engineering-first priorities that align with what many manufacturers are now buying:
- Design architectures that scale across sites, not one-off implementations that can’t be replicated.
- Build delivery frameworks that enforce rigor while leaving room for engineering judgment.
- Invest in data management capabilities so OT signals become trustworthy decision inputs.
- Treat trust as an outcome of engineering execution, not a marketing message.
- Plan talent and AI readiness now, because the next five years will reward SIs who can operationalize new ways of delivering and supporting systems.
As Gomez put it, the objective is to leave customers not just with a solution, but with an architecture that supports the next problem they haven’t defined yet.
“Can it enable you,” he asked, “with this architecture to solve those potential problems?”
The Ctrl+Alt+Mfg Podcast
Make sure to check out other episodes of the Ctrl+Alt+Mfg podcast, where hosts Gary Cohen and Stephanie Neil discuss a range of digital transformation insights. The last five episodes are listed below:
Ep. 11: What plant engineers really want, with Amara Rozgus of Plant Engineering
Ep. 12: Why system integrators matter more than ever in the age of AI, with Adrienne Meyer of CSIA
Ep. 13: Bad data, broken maintenance, with Paul Ross of Limble and Ross Fergerson of RBC Bearings
Ep. 14: From data silos to smart factories, with John Dyck of CESMII and John Harrington of HighByte
Ep. 15: Industrial AI’s reality check, with Josh Peeno of JPeeno Innovation Group
