At Automate 2025, Aamir Paul, president of North America operations at Schneider Electric, offered a challenge for those in manufacturing.
Labor shortages are deepening. Energy demands are rising. The pace of change is accelerating. Manufacturing is at a pivotal point where innovation is moving faster than traditional industrial systems were designed to handle.
What’s needed now to thrive is more than incremental improvements. It’s a step-function change in how productivity works in manufacturing, A change that Aamir Paul frames up as the 10x productivity unlock. And achieving it requires a fundamental shift in how automation is architected, deployed, and scaled.
That shift centers on software-defined automation.
SOFTWARE-DEFINED AUTOMATION, EXPLAINED
Software-defined automation (SDA) is an approach to industrial automation that separates (or decouples) the software from the physical hardware used to run machines and processes. Essentially, the intelligence lives at the software layer of the system versus the hardware. So, core automation functions such as logic, sequencing, coordination, and analytics can be reused across different machines or hardware platforms.
This differs from traditional automation systems, where intelligence is tied to specific controllers.
The shift to software-defined automation offers more flexibility in how automation systems are designed, updated, and scaled.
THE PRODUCTIVITY IMPERATIVE: WHY CHANGE IS NON-NEGOTIABLE
As we build factories of the future, it’s clear that we are on the brink of an industrial transformation. Software-defined automation is integral to this next chapter.
Next Industrial Revolution
Aamir Paul opened his keynote by framing the moment plainly: manufacturing is standing at the edge of another industrial revolution.
The implication isn’t subtle either. Systems built for stability and longer lifecycles are now being asked to respond to constant change. And that tension is showing up everywhere, from workforce constraints and energy planning to global competitiveness.
Paul emphasized that no single company can solve this alone. Productivity at this scale is a collective responsibility across manufacturers, technology providers, system integrators, and policymakers.
Labor and Wage Crisis
Manufacturing today faces a projected workforce shortfall of more than 2 million jobs by 2030. Even with heavy recruitment and training, the math doesn’t work. Raising wages without increasing output only shifts the problem elsewhere, like driving up costs or reducing competitiveness.
“There are not enough people in the United States to make this work,” Paul says. “It’s not going to happen with wage increases. The only way out of this is a productivity boom like we haven’t seen before.”
Reshoring, nearshoring, and supply-chain resilience all depend on one thing. Manufacturers need to produce more with fewer people — and without sacrificing quality, safety, or sustainability. This reality requires automation. Not to replace people but to support and enable them.
Sustainability as a Productivity Lever
There is a lingering assumption that sustainability and economic performance are parallel priorities. At Schneider Electric, that’s not the case. Paul shares how sustainability is treated as a form of waste elimination.
Excess energy consumption, unplanned downtime, inefficient changeovers, and material losses all represent waste in the system. Reducing them improves both environmental performance and operational efficiency.
“Sustainability is simply a different vector of efficiency,” Paul notes. When addressed at the system level, it becomes a productivity accelerator versus a constraint.
HISTORICAL CONTEXT TO ACCELERATE THE SPEED OF CHANGE
Advancement can bring uncertainty or discomfort. It can also bring excitement and opportunity. Whichever side you’re on, remember that history has taught us a thing or two about navigating the next era of manufacturing.
Navigating Technological Transitions isn’t New
To put today’s disruption in perspective, Paul drew a parallel to the 1893 Chicago World’s Fair when electricity was first demonstrated at scale.
At the time, the questions were strikingly familiar. Is this technology safe? How will it change the way we live and work? What does it mean for society? What will humans do in a world reshaped by it?
The technology was new, and the uncertainty was real. But the transition happened because people learned how to work with it. Sound familiar? The constant across every industrial shift isn’t the technology itself, but how humans adopt and interface with it.
Software is the Only Vector that Scales Fast Enough
What once took decades now takes years, if not months, to reach mass adoption. This is largely due to software rather than physical infrastructure.
Since the smartphone era, nearly every major technology category has become software-defined. Software architectures make it possible to add functionality and upgrade performance without completely rebuilding or buying new.
While physical systems remain essential, they can’t scale at the same pace as software. By focusing on the software side, you gain the ability to respond faster, iterate safely, and expand efficiently across operations.
Following a Wait-and-See Approach is a Risky Move
Paul described change as moving through three phases. First, the idea seems crazy. Then, it seems dangerous. Until finally, it seems obvious.
But for many, waiting until it’s obvious (or waiting until everyone else adapts first) could be too late. While taking risks may not always be the right choice for your business, falling back on a "we've always done it this way" strategy will only limit progress.
Leadership requires strategically committing to progress and growth, even when it’s uncomfortable.
SYSTEM ARCHITECTURE SHIFT TO SOFTWARE-DEFINED AUTOMATION
If you’re considering the shift to software-defined automation, you may be asking or hearing a lot of “why” and “how” questions. Aligning on answers and understanding the context behind the shift is integral to ensuring its success.
How Legacy Automation Architectures Limit Productivity
For decades, automation discussions have been segmented. Controls are separated from energy, software from hardware, and operations from data. Paul calls that separation a “bankrupt idea.”
Closed, siloed automation architectures put the integration burden on operators and manufacturers. It fragments data and slows down decision-making. And all of this makes it harder to adapt, harder to scale, and harder to extract value from emerging technologies.
But software-defined automation addresses these challenges by unifying layers under an open, system-level architecture. Instead of silos, there is connectivity and cohesion.
Why Connected Infrastructure is No Longer Optional
When infrastructures are connected, data becomes visible and actionable. Diagnostics happen faster. Energy is optimized. Downtime is reduced. Systems adapt to changing conditions. The list goes on, but the core point is that connectivity is a prerequisite today.
How Digital Twins Change the Economics of Automation
One of the most practical outcomes of software-defined automation is the ability to use a digital twin earlier and more effectively in workflows.
Rather than designing systems on paper and discovering inefficiencies after deployment, digital twins allow you to simulate, optimize, and validate operations digitally before anything is actually built or physically changed.
This capability opens the door to more confident design decisions, smoother handoffs, and continuous improvement across the full lifecycle.
Why the Mandate for Open vs. Closed Software
At its core, software-defined automation helps manufacturers move faster and adapt more easily. In practice, that means:
- Faster changes to the automation system without hardware lock-in
- Greater reuse and portability of automation logic
- Improved visibility across the asset lifecycle
- Lower long-term integration and upgrade costs
- Stronger alignment between IT and OT systems
These are real and valuable benefits that directly address the pressures manufacturers are facing today.
WHAT’S LEADING THE CHANGE: ENERGY, WORKFORCE, AND PROOF
While Paul’s keynote was focused on manufacturing, some of the key factors driving the need for software-defined automation apply to many other industries.
Intersection of Energy and Industrial Production
Energy costs in the U.S. have risen sharply in recent years. At the same time, demand from data centers and digital infrastructure is placing additional pressure on the power grid. Even automation itself is increasing electricity and power use inside factories.
This means energy can no longer be treated as a separate planning decision. Automation choices directly impact energy demand, and energy availability shapes how systems can operate. Keeping both in mind at the system level helps better manage costs, reliability, and productivity.
Investing in the Next-Generation Workforce
In our 2026 automation tips and trends article, we discussed how technology alone won’t solve workforce challenges. The human side of automation is just as critical to prioritize.
While most Americans support bringing manufacturing jobs back, only a small percentage want to work in the industry. At the same time, many of the most experienced engineers are nearing retirement.
In order to close the gap, we need to capture institutional knowledge before it leaves and evolve manufacturing roles to reflect a more digital, software-driven reality. A reality that the next generation of workers crave.
Success Story: Step-Function Change at Work
Paul pointed to Schneider Electric’s Lexington, Kentucky case study to demonstrate what software-defined automation looks like in practice.
The 66-year-old manufacturing plant needed an upgrade. But instead of attempting a massive, one-time overhaul, the team focused on creating a connected infrastructure and software-defined systems.
The plant saw a 26% reduction in energy costs, a 20% reduction in mean time to repair, and a 5% reduction in downtime. It even achieved a World Economic Forum Lighthouse Smart Factory status. And it did this with the same workforce while increasing productivity.
COMMIT TO THE FUTURE OF MANUFACTURING
The tools required to modernize manufacturing already exist. We’re seeing them used in factories and facilities around the world. The architectures are in place, and the results are measurable. What remains up in the air is whether leaders are willing to move away from existing systems that may be limiting their operations.
Think about how you’re using software today to drive productivity and flexibility. Evaluate current workflows and platforms with a long-term perspective. Can your current systems scale? Do they deliver as much value as possible? Or, is it time to embrace software-defined automation that’s shaping the future of manufacturing?
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