Why this matters now
As explored in his recent article in Control Engineering, Emerson’s Dave Denison—leveraging his decades of experience in the automation industry—explains that OT teams face a unique challenge as AI adoption accelerates. While AI is gaining traction across industries, process manufacturers must ensure any solution they deploy fits securely, reliably, and sustainably into complex operational technology environments. These requirements differ significantly from consumer or enterprise AI trends, and they place a premium on lifecycle‑ready, deeply integrated industrial AI solutions.
- OT teams need AI that integrates seamlessly with existing systems—without disruption or added data silos.
- Industrial AI strengthens decision‑making across planning, modernization, engineering, and operations.
- Lifecycle‑ready AI helps teams adopt advanced tools without requiring deep in‑house AI expertise.
How do integrated industrial AI solutions improve planning?
Integrated industrial AI helps project and operations teams make more informed decisions from the earliest stages of an asset’s lifecycle. Using techniques such as Monte Carlo simulation and scenario analysis, AI can evaluate probable outcomes across design, capacity, operations, maintenance, logistics, and market conditions. These insights allow teams to identify risks, improve lifecycle cost planning, and align decisions with long‑term operational needs. As tools evolve, natural‑language interfaces will help teams generate tailored analyses based on their own plant data—making advanced modeling more intuitive and accessible.
“As automation solutions continue to evolve, they are increasingly including critical technologies to support every stage of the lifecycle, making it easy for companies to deploy AI as part of a trusted, intuitive system.”
Takeaway: Integrated industrial AI strengthens early‑stage planning and helps teams lock in better lifecycle outcomes.
What are AI’s capabilities for modernization and engineering?
Modern industrial organizations rarely have the depth of engineering resources they once relied on. Industrial AI tools help close that gap by reducing engineering effort and accelerating modernization workflows. Technologies such as Emerson’s DeltaV™ Revamp provide an integrated digital workflow that uses AI to evaluate legacy control configurations, extract controller and I/O information, and present it in a clear, human‑readable format. This eliminates the need for specialized expertise in proprietary legacy systems and gives engineering teams a streamlined starting point for modernization.
“AI assistance accelerates development by starting with proven standard solutions and established first principles models. These approaches are then intelligently customized using a manufacturer’s specific operational data and unique requirements, empowering critical engineering personnel to spend more time evaluating and refining those solutions to deliver optimal control strategies.”
Takeaway: AI simplifies modernization by converting complex legacy configurations into actionable engineering insights.
How can AI help today’s digital workers be more effective?
Industrial AI is not a future concept—it is already embedded in the tools operators use every day. Machine learning models help teams diagnose issues, deliver actionable insights, and intervene before failures occur. Intelligent edge devices, such as the AMS Asset Monitor with built‑in analytics, expand visibility into equipment health and support more proactive decision‑making. At the same time, emerging virtual advisors with natural‑language capabilities will increasingly act as operator copilots, helping teams make informed decisions and ensuring consistent, efficient operations across shifts.
Takeaway: Embedded AI and emerging virtual advisors strengthen operator awareness, consistency, and confidence.
How can I take advantage of AI if I don’t have AI expertise?
For many OT organizations, the biggest barrier to AI adoption is not willingness—it is uncertainty about which solutions will work in their environments. With many startups offering niche tools, teams risk adopting technologies that introduce data silos, require extensive training, or become unsupported shortly after deployment. Emerson addresses this challenge by delivering lifecycle‑ready industrial AI as incremental upgrades to the automation platforms teams already trust. This reduces training requirements, minimizes integration complexity, and ensures new AI capabilities align with the long lifecycles and reliability demands of OT systems.
