Industry
Manufacturing
Future-Ready Manufacturing: Partnering in your journey to a sustainable manufacturing enterprise
Highlights
- Engineering in the energy and process industries faces significant challenges due to siloed collaboration, fragmented design reviews, and inefficient change management resulting in costly delays and rework.
- Agentic AI deploys intelligent, autonomous agents that collaborate seamlessly across processes, instrumentation, controls, electrical, mechanical and configuration management disciplines; driving real-time synchronization and strategic coherence throughout the engineering lifecycle.
- By integrating adaptive AI orchestration with human-in-the-loop governance, organizations can reinvent their engineering business operating model; accelerating innovation, reducing risk, and unlocking sustainable competitive advantage.
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SETTING THE STAGE
Reimagining engineering design in energy and process industries by breaking silos and building collaborative ecosystems
In the energy and power industries, product engineering design is becoming exponentially more complex. From fossil-fueled power plants to clean hydrogen energy solutions, the product development lifecycle spanning Process Flow Diagrams (PFDs), Piping and Instrumentation Diagrams (P&IDs), instrumentation datasheets, loop diagrams, electrical schematics, wiring diagrams, 3D Piping design and routing, through to parts and Bill of Materials (BOM) management in PLM and ERP handoff remain fragmented. Disparate systems and disconnected workflows hinder traceability and cross-functional alignment, highlighting the urgent need for an orchestrated and intelligent engineering design ecosystem.
According to Gartner, 45% of product launches are delayed by at least one month largely due to fragmented collaboration across engineering functions, repetitive design validation cycles, and disconnected change management processes. Engineering teams often operate in silos, using different tools, datasets, and schedules with communication that is manual, asynchronous and prone to misalignment. These inefficiencies not only lead to cost overruns and rework but also slow down innovation and time to market; at a time when competitive advantage increasingly depends on engineering agility and digital continuity.
In a capital project worth USD 500M-700M, even a 1% delay in engineering can lead to millions in downstream cost overruns and months in delayed commissioning.
THE REAL CHALLENGE
The design relay - engineering without orchestration: A system of alerts, not intelligence
Consider a real-world example from an Electrolyzer OEM - the process engineering team updates a pipeline specification, but the change isn't reflected in the instrumentation tag sheet. As a result, the wrong control valve is specified and this issue is discovered late during the electrical load review triggering last-minute rework, vendor renegotiations and costly delays in downstream procurement and manufacturing.
Even in organizations with advanced, digitally connected tools, a critical gap remains; that is the lack of true engineering orchestration. Despite systems integrations, design and change reviews still depend on individual expertise with engineers/subject matter experts manually catching errors, analyzing the impacts and resolving them based on individual judgment. This reliance on tribal knowledge introduces inconsistency and risk.
Most modern product development engineering tools and applications flag alerts and notifications, but they stop at surface level insights. They do not uncover in-depth root causes or analyze historical patterns and do not support cross-disciplinary reasoning which is the key here. More importantly, they do not act autonomously to fix errors across systems, adapt workflows and make decisions with contextual intelligence. As a result, engineering problem solving stays reactive while collaboration and change management remain largely manual.
THE AGENTIC AI SHIFT
Rise of agentic AI: From reactive engineering to adaptive and orchestrated agents
The next evolution is not just AI-powered engineering, drafting, or simulation. It is agentic AI, an intelligent orchestration fabric where autonomous engineering agents represent each engineering function and work in tandem.
Imagine a future-ready business model powered by specialized engineering agents working in harmony across the design lifecycle. A Simulation Agent interprets process simulations to extract key parameters, auto-generates flow diagrams, and sets foundational specifications. The Process Design Agent transforms these into compliant P&IDs, aligns schematic and physical designs, and validates logics against safety standards.
Next, the Instrumentation Design Agent auto-fills tag sheets, validates control loops, and recommends compatible instruments. The Controls Design Agent builds control logic diagrams, simulates behavior, and ensures consistency across automation layers.
Meanwhile, the Electrical Design Agent generates single-line diagrams, cable schedules, and validates power systems while coordinating with other disciplines. The Mechanical Design Agent creates 3D piping models, isometrics, and pushes accurate BOMs into PLM systems.
A Configuration Management Agent governs design revisions, enforces baselines, and integrates structured BOMs with ERP systems. Finally, the Engineering Change Management Agent detects real-time deviations, assesses cross-functional impacts, and suggests design alternatives with updated documentation.
When applied across the product development engineering lifecycle, these agents take ownership of outcomes and agentic AI holds the potential to shift from isolated engineering operations to operate in orchestral harmony and intelligent design evolution.
Moreover, all these activities are continuously overseen by engineers/subject matter experts, who intervene not for routine tasks, but to provide strategic oversight, apply expert judgment, and make customer experience-driven decisions where human discernment is essential.
HUMAN + AI SYNERGY
Human-in-the-loop: Engineering wisdom meets agentic AI agility
Even the best agents need guardrails. Engineering judgment, especially in the energy and power sector, where safety, quality and compliance are non-negotiable, cannot be left entirely to engineering AI agents.
Here is where human-in-the-loop oversight becomes pivotal. Engineers/subject matter experts do not just validate what these agents generate but they guide, correct, and refine them continuously.
As organizations reimagine their engineering workflows, an orchestrated system of agentic AI offers a compelling promise for measurable improvements in speed, quality, and efficiency. Acting as intelligent design companions, these AI agents work alongside engineers/subject matter experts to enhance cross-discipline coordination and ensure seamless data continuity across the lifecycle. While the below outcomes represent a forward-looking vision, they are grounded in proven pilots and evolving use cases building strong confidence in the transformative potential ahead.
- 20 - 30% reduction in engineering cycle time: Coordinated design agents automate design diagrams, 3D models and specification transfer across domains, accelerating end-to-end design workflows.
- Up to 40% effort savings in routine engineering tasks: Design agents automate validation and documentation, freeing engineers to focus on customer experience and problem solving.
- 15 - 25% reduction in rework and cross-discipline errors: Change and Configuration agents track deviations, assess impacts, and align designs to reduce late-stage rework.
- 10 - 20% faster procurement and manufacturing readiness: Configuration agents generate structured design records, enabling smooth handoff to business enterprise systems and speeding up planning and vendor coordination.
- Full design traceability and improved compliance readiness: Every step from design to release is tracked and validated by agents, ensuring traceability, accountability and design audit readiness.
THE PATH FORWARD
Connected AI-enabled engineering
Engineering leaders should focus on accelerating collaboration, integrating engineering data into a unified context, and deploying AI agents trained in industry-specific standards. By enabling real-time design reviews and tracking engineering velocity through metrics like design accuracy and change closure rates, they can drive smarter, faster, and more resilient engineering outcomes.
CONCLUSION
A future where product engineering moves as one - autonomous, aligned, accelerated
With stringent compliance and regulatory requirements, energy and power industries cannot afford product engineering functions that work in separate parts. The next generation of performance, sustainability, and agility will come not from faster tools but from smarter collaboration.
Agentic AI offers the way forward; a seamless, intelligent layer that binds engineering teams, tools, and data into a cohesive, change-ready ecosystem. It is time to stop reacting to change and start collaborating with it.
Organizations have already started shifting from fragmented tool chains to orchestrated ecosystems, where AI agents enable real-time collaboration, predictive design optimization, and traceable change propagation.
This future is not notional. It is already underway quietly piloted in AI initiatives, generative design workflows, and AI-assisted Engineering, Procurement & Construction (EPC) environments. The imperative now is for engineering leaders to embrace AI as a co-engineer and to invest in systems that bring together knowledge, agents, and human decision-making into a unified, orchestrated, and real-time collaborative and responsive business operating model.
