A flagship opening discussion on what has genuinely moved from pilot to production, where ROI appeared fastest, and what still stalls in execution.

A strategic view of how digitalization changes workflows, management systems, and the way the business runs.

A practical look at where agentic AI is useful now, what data and context it requires, and where human-in-the-loop oversight remains essential.

Operators and practitioners discuss what helped scale high-value use cases, what killed momentum, and how ROI was measured and defended internally.

Three rapid talks on semantic layers, contextualized industrial data, RAG and metadata, and governance, lineage, and auditability for production AI.

10:30 - 10:40 5a. Semantic layers and ontologies

10:40 - 10:50 5b. RAG, metadata, embeddings, and context

10:50 - 11:00 5c. Governance, lineage, and auditability for enterprise AI Framework-- Omar Omar, Senior Advisor in AI Engineering, Phillips 66

Industrial AI is at a crossroads. Many organizations are rich in pilots but poor in scale. We’ve seen it before; every leap forward starts with the foundation beneath it. The Roman roads connected an empire, the U.S. highways connected an economy, and Google Maps created a common lens for how the world navigates. Now, manufacturing is building its next great network: the AI Highway. Discover how Albemarle delivered over $150 Million in annual improvements by building an AI Highway.

A practical session on secure internal AI platforms, controlled enterprise assistants, model flexibility, and what users actually adopt.

AI value is rarely determined by technology alone. This session connects compute cost, vendor spend, and model economics with the harder questions of workflow redesign, decision rights, user adoption, and process ownership. It examines what it takes to embed AI into measurable payback.

A case study demonstrating how process automation - often treated as an unavoidable operating expense, can be deliberately transformed into a high-yield investment, particularly as advanced algorithms cannot compensate for weak automation & data foundations.

● Why automation maturity is the primary limiter of AI value in manufacturing

● How standardized, lifecycle‑managed automation creates reusable data, trust, and scalability

● A pragmatic pathway to automation‑driven AI implementation, including operator‑facing AI use cases

A forward-looking discussion on quantum and high-performance computing, framed realistically for the next few years rather than the distant horizon.

A premium operator fireside on what makes a digital leader different: leadership behavior, supplier ecosystem, scaling logic, and operational discipline.

A practical panel on choosing between model types, deployment patterns, hybrid/on-prem/cloud architectures, and how to avoid overbuilding.

A fast-moving lightning round on responsible AI in operations, semantic data products, fast model upgrades, and safe automation in OT environments:

Topic subject to change

• 2:55 - 3:10 From Vision to Value: Unlocking Data and AI ROI in Oil and Gas
• 3:10 - 3:20 Semantic data products versus dangerous data lakes
• 3:20 - 3:30 Fast model-backend upgrades
• 3:30 - 3:40 Safe automation in OT environments

A case study on where digital twins still create value through standardization, simulation, Turnaround P&S, LOTO preparation. Maintenance & Operational training, and emergency preplanning.

A curated showcase of deployable technologies across drone analytics, robotics, semantic layers, IoT, AI governance, and workflow automation. In this showcase, each innovator pitches practical solutions built for oil and gas.

You will:

• See a curated showcase of applications designed for real operational environments.
• Compare commercial models, integration requirements, and typical timelines from pilot to production.
• Hear real-world examples and measurable outcomes aligned with operator priorities.
• Vote live for the solution you would most realistically trial in your own organization.

A Day 2 opener on portfolio strategy, centers of excellence, standardization, and scaling digitalization across assets and regions.

A presentation on avoiding lock-in, building adaptable data foundations, and maintaining flexibility across tools, models, and vendors.

A panel on governance boards, auditability, lineage, SAP/SOX realities, risk review and what production-grade AI requires in large industrial companies.

An overview of deploying Spot to automate data collection, improve asset integrity, and scale digitalized reliability workflows in refining operations

A broad panel on inspection robots, drone-in-a-box systems, ground robots, subsea robotics, and where economics work in real operations.

A practical presentation on LoRaWAN, low-cost telemetry, battery-powered sensing, and the physical data layer needed for future AI use cases

An interactive discussion on standards, data models, facility templates, hardware upgrade paths, and decisions that unlock future competitiveness.

Roundtable leaders will open these highly interactive, peer-driven roundtables with a brief 5-minute introduction and a short overview of the topic, which can include a case study, lessons learned, or an industry update.

Each roundtable covers a different topic, allowing attendees to choose the discussion most relevant to them.

This is followed by a 30-minute peer discussion, with the leader facilitating questions, feedback, and practical exchange. The final 5 minutes are dedicated to aligning on five clear industry recommendations which will be included in the post-conference report.

Choose one topic that aligns with your most urgent priority.

Topic subject to change

1. From Pilot to Production: What Actually Helps a Use Case Scale? 
2. Building an AI-Ready Data Foundation: Governance, Lineage, and Business Ownership - Ram Seetepalli, Director, AI & Digital Solutions, Motiva Enterprise LLC
3. OT, IT, Cloud, and Edge: Where Integration Still Breaks Down 
4. Agentic AI in Operations: Where Human-in-the-Loop Still Matters Most 
5. Choosing the Right Model, Tool, and Architecture for the Job 
6. How to Measure ROI for AI, Automation, and Digitalization in Real Operations 
7. Digital Twins After the Hype: Where They Still Deliver Operational Value 
8. Drone, Sensor, and Visual Analytics: What Actually Works in the Field 
9. Field IoT and Edge Telemetry: Building the Data Capture Layer for Future AI 
10. Operationalizing AI in a Regulated, Asset-Heavy Business: Governance That Enables Rather Than Blocks 
11. Safety, Cybersecurity, and Reliability in More Autonomous Operations 
12. Workforce 2030: Reskilling, Role Redesign, and Protecting Critical Expertise – Julie Thyne, Dow
13. Standardizing Asset Data Across Sites Without Locking Yourself Into One Vendor 
14. Physical AI in Industry: Connecting Robotics, Sensors, and Decision Systems – Ashley Raimondi, Enterprise Sales Engineering Manager, Boston Dynamics
15. Future-Proofing the Operating Model: What to Standardize Now for the Next Wave of AI 

A session on OT cybersecurity, edge protection, segmented architectures, drones and robotics oversight, and safe deployment in high-consequence environments.

A lightning round covering drone-in-a-box deployment lessons, low-code robot training, reality capture and GPR, and ROI tracking from day one.

• Drone-in-a-box deployment lessons
• Low-code robot training and modular automation
• Reality capture and GPR with drones

A practical workforce session on retiring expertise, digital twin–based training, end-user programmability, and new role design in a more automated sector.

A cross-industry panel on simulation, robotics, AI-first workflows, manufacturing automation, and what is realistically transferable to oil and gas.