Will Gen AI Eliminate Engineering Services?

The rapid rise of Generative AI (Gen AI) is transforming industries worldwide, but nowhere is this shift more pronounced than in the field of engineering. As #AI continues to evolve, a provocative question has emerged: Will Gen AI eliminate the need for traditional engineering services? Specifically, can Owner-Operators (OOs) auto-generate Front-End Engineering Design (FEED) using AI and historical project data, bypassing the need for large engineering firms?

This article explores how Gen AI is revolutionizing FEED, the potential for Owner-Operators to generate project designs autonomously, and what this means for the future of engineering services.

The Role of FEED in Project Success

Before delving into AI's impact, it's important to understand the role of FEED. FEED is critical to defining a project's scope, design, costs, and potential risks before significant investments are made. Traditionally, engineering firms provide these services, using extensive expertise to tailor project plans to specific needs, ensuring smooth transitions to execution EPC.

In the Gen AI era, the process is undergoing a transformation. For example, AI-powered systems can automatically generate P&IDs based on historical data and project requirements, minimizing the risk of human error while increasing efficiency. By feeding AI with specifications from previous projects, it can also create MDRs that are optimized for specific project timelines, reducing administrative overhead.

Auto-Generated FEED?

Gen AI is making it possible for Owner Operators OOs to generate detailed FEED documents by analyzing vast amounts of historical project data. This transformation opens the door to a future where projects can be designed, evaluated, and optimized without relying on external engineering services.

How does it work?

• Historical Data Analysis: Gen AI can review and learn from thousands of past projects, identifying patterns and successful designs based on location, materials, costs, and environmental conditions.
• Automated Design Generation: AI can propose optimized design solutions in minutes, compared to the weeks or months it traditionally takes for human teams to complete FEED. Designs are automatically adjusted to meet regulatory requirements, safety standards, and cost-efficiency goals.
• Risk Prediction: AI tools can simulate potential risks during the design phase, helping to identify problems like supply chain disruptions, equipment failures, or weather-related delays. This allows decision-makers to mitigate risks before they occur.

Use Case: A Middle Eastern energy company piloted an AI-driven FEED process for a refinery expansion. By leveraging data from 50 similar projects, the AI system delivered a complete FEED design 40% faster than traditional methods, optimizing for cost and material efficiency.

The Power of AI in Engineering, Beyond FEED

While the idea of AI-generated FEED is compelling, Gen AI is not the only technology reshaping engineering services. Other emerging technologies are playing crucial roles in how Owner-Operators approach design, construction, and operations:

Digital Twins are virtual representations of physical assets that enable real-time monitoring and simulation. When integrated with AI, Digital Twins provide engineers and Owner-Operators the ability to predict performance and optimize designs during the FEED phase and beyond. Use Case: A petrochemical plant used a Digital Twin to simulate various operational conditions during the FEED phase. This allowed the engineering team to optimize the layout for maximum efficiency while reducing potential safety risks.

The Industrial Metaverse introduces immersive environments where engineers can interact with 3D models in real time, walking through project designs using Augmented Reality (AR) and Virtual Reality (VR). This level of collaboration and visualization enhances the quality of design reviews, helping to spot potential issues early. Use Case: An offshore platform design team used AR technology to virtually walk through a digital model of the platform. By identifying potential maintenance issues in real time, they reduced the risk of costly rework during construction.

AI-powered simulations allow engineers to test multiple scenarios and predict potential risks during the design and construction phases. These simulations can consider variables such as fluctuating material costs, labor availability, and extreme weather conditions, providing valuable insights for project planning. Use Case: A renewable energy company used advanced simulations to test the resilience of its FEED design under extreme weather scenarios. This led to a redesign that improved the safety and longevity of the wind farm, saving millions in potential damages.

Will Engineering Services Disappear?

Despite the immense potential of Gen AI and related technologies, it’s unlikely that traditional engineering services will become obsolete. Here’s why:

Complex Problem-Solving: While AI can replicate and optimize designs based on historical data, it lacks the creativity and innovative problem-solving abilities of human engineers. Projects that require novel solutions or cutting-edge designs will still rely heavily on the expertise of engineering firms.

Oversight and Validation: AI-generated designs still need human oversight to ensure they meet all safety, regulatory, and operational standards. Engineers will play a crucial role in reviewing AI outputs, validating designs, and offering insights that AI systems cannot provide.

Unprecedented Challenges: For projects involving entirely new technologies or complex environmental conditions, engineering firms will remain indispensable. AI relies on historical data to make predictions, but when faced with novel challenges, it may not provide adequate solutions.

Collaboration Between AI and Human Expertise

Rather than eliminating the need for engineering services, Gen AI will likely shift the role of engineering firms from manual design tasks to more strategic and high-value activities. In this new paradigm, engineering firms will:

• Oversee AI Outputs: Engineers will review AI-generated designs, ensuring they meet the specific needs and standards of each project.
• Focus on Innovation: Firms will tackle complex engineering challenges that require creative solutions, while AI handles routine tasks.
• Optimize AI Integration: Engineering firms will also evolve to integrate AI into their own processes, using these tools to enhance efficiency and deliver faster, more cost-effective services.