• Reviewing concrete Canadian operator results in pipeline optimization, production surveillance and back-office automation, with real numbers on uptime, throughput and cost.
• Comparing early pilots with steady state operations to show what sustained value looks like on Alberta and BC assets.
• Highlighting patterns that travel well between mid-size producers, pipelines and power utilities to guide 2026 investment priorities.

• Reframing AI strategy away from chatbots and agent trends toward redesigning the work that creates value.

• Redesigning workflows and decision paths to embed AI where it changes speed, quality, and cost to serve.

• Reshaping roles, accountability, and human to AI teaming to unlock operating leverage without breaking governance.

• Upskilling teams with the practical capabilities needed to adopt AI at scale and sustain measurable performance gains.

• Explaining the technical drivers behind the shift to agentic AI: compute, algorithms, data scale and cost, in language business stakeholders can understand.
• Showing what “agents” actually do on real Canadian use cases, from automating multi-step workflows to coordinating with humans.
• Equipping technologists to explain this shift credibly to CIOs, COOs and regulators.

• Sharing quantified results from predictive maintenance, leak detection and commercial optimization on Canadian assets.
• Discussing how Calgary based operators are deciding where to double down, where to pause, and how to stop “pilot sprawl.”
• Comparing governance and investment models in large integrated companies versus mid-size independents.

Three rapid 15-minute talks. One messy data problem, one approach, one result.

• Ensuring the First Mile of Data - Jesus Borobia, PowerTrunk
• AI governance and guardrails in safety-critical, highly regulated environments - Alain Siewe - Arc Resources
• SLB’s Tela: Agentic AI enabling domain expertise for the subsurface and automated workflows - Steve Dahl, SLB

• Discover how a Canadian industrial services company launched its AI transformation using an internally developed roadmap - without overspending or relying on a large IT team.
• This session highlights two real-world use cases that delivered measurable results for Accounts Payable and other business areas.
• Walk away with actionable insights, lessons learned, and practical strategies to help your organization unlock AI’s potential on a realistic budget.

• Identifying the specific new risks introduced by GenAI and agentic AI for Canadian operators: hallucinations, IP leakage, bias and safety-critical decision support.
• Comparing approaches to guardrails: internal policies, vendor controls, prompt retention, auditability and “kill switches.”
• How legal, cyber, data and operations teams in Calgary are sharing accountability for AI governance instead of passing the buck.

• Defining high consequence events in OT and critical infrastructure, for prioritizing what truly matters, to protect safety, uptime, and public trust.
• Mapping threat vectors and attack paths back to those high consequence outcomes, for focusing controls on real operational risk, to reduce blind spots and wasted effort.
• Applying the CCE methodology to identify critical functions and weakest links, for strengthening resilience, to prevent disruption of essential services.
• Aligning engineering, operations, and cyber teams around consequence based risk decisions, for clearer accountability, to accelerate action without compromising safety.

• Defining when an AI agent can act, when it must ask, and when it must stop in pipeline, plant and field contexts.
• Designing user interfaces and notifications that engineers, controllers and field staff will actually trust and respond to.
• Building auditability and reversibility into every agent workflow so operations keeps ultimate control.

The Enbridge Innovation Team will deliver two 15-minute presentations. Across the session, the team will also reflect on the challenges the Lab had to overcome, the new types of issues that emerged during implementation, and what they are working on today.

Presentation 1: Responsible AI and AI Literacy

Allan Cheung, Enbridge

Presentation 2: Machine Learning to Cut Pipeline Power Costs Without Compromising Safety A product-specific presentation exploring how machine learning is being used to reduce pipeline power costs while maintaining safety standards.

Fed Briceno and Kevin Wuerstl, Enbridge

Explore real-world lessons and case studies on how energy leaders design intuitive human-AI interactions, scale impactful use cases, and orchestrate technology across the AI landscape to unlock business value. In this session, we'll dive into the following topics:

· Designing human-AI interactions that drive adoption

· Where Energy organizations typically start, and how they scale to maximize impact

· How to set up an AI technology ecosystem that serves end-to-end business processes

Rapid 15-minute talks to spark discovery.

• Explainability and the operational value created for our automated mining haul system at Kearl - Bryan Kan, ExxonMobil and Hannah Zhao, ExxonMobil
• Own Your Data, Own Your AI: Sovereign Compute at the Industrial Edge - Glen Crockford, Telus
• Session by Accelerated Focus - Travis Cavanagh, Accelerated Focus

Get a rapid-fire preview of the future in this high-energy session. Six startups will pitch their groundbreaking AI solutions for oil and gas in just six minutes each.

• Seeing how local startups are tackling emissions monitoring, field data capture, workflow agents and industrial AI.
• Understanding pricing, integration effort and typical timelines from pilot to production.
• Voting for the solution you would most realistically trial in your own organization.
• The winner receives a free exhibition space to another ECN conference

For more information, please contact Filipa de Almeida Ribeiro, Partnership Manager, Energy Conference Network

filipa.ribeiro@energyconferencenetwork.com

• Identify one idea you can test in your own team within 30 days.
• Pair up to pressure-test it and commit to a next step.
• Share the best actions via live poll to shape tomorrow’s discussions.

• Moving from scattered initiatives to a clear portfolio tied to Canadian regulatory, emissions and reliability pressures.
• Structuring a simple “funnel” from ideas to pilots to scaled programs that mid-size and large operators can both use.
• How boards, CIOs and business leaders in Canada are aligning on one AI narrative and investment plan.

• Connecting historians, SCADA, ERP and cloud platforms in ways that respect bandwidth, latency and security constraints.
• Using integration platforms and data pipelines to deliver trusted data products to AI teams.
• Lessons learned from projects on Canadian pipelines, gas plants and power facilities.

• What is working in enterprise AI today, and where organisations are seeing measurable outcomes
• Why deployments stall after the pilot stage, including data, operating model, risk, and adoption blockers
• Where agentic AI and automation are taking hold first, and what “safe to scale” looks like in practice
• The emerging blueprint for AI ready organisations, from governance to delivery and change management
• What leaders should prioritise over the next 12 to 18 months to move from pilots to portfolio value

• Identifying the few AI competencies operators actually need (by role) for avoiding generic training, to improve day-to-day usage.
• Embedding governance into workflows for reducing mistakes, to make adoption safe in control rooms and the field.
• Creating feedback loops between users and model owners for preventing drift, to keep performance reliable over time.
• Standardizing what “good” looks like for scaling faster, to replicate success across assets.

• Using AI on LDAR, satellite and sensor data to cut false positives and focus field crews on real leaks.
• Shortening the time from detection to fix for methane and other emissions under Canadian and provincial regimes.
• Integrating AI workflows with existing environmental management systems and reporting processes.

• Exploring where agentic AI can automate end to end supply chain workflows
• Identifying the highest value “starter use cases” in procurement, logistics, and maintenance supply
• Assessing the data, governance, and operating model guardrails needed to deploy agents safely
• Applying practical lessons on integration, human in the loop design, and change management

• Using chatbots and self-service tools to resolve simple invoice and PO queries without tying up supply chain staff. - Brian Emmerson, EY
• Applying advanced analytics and AI to identify and address risks in procurement and your supply chain. Carl Hammersburg, SAS
• Optimize operations securely with AI on the Edge - Javier Lopez, HP

Move from presentation to problem-solving in these highly interactive, peer-driven roundtables. Each roundtable covers a different topic, allowing attendees to choose the discussion most relevant to them.

Roundtable leaders will open with a brief 10-minute introduction and a short overview of the topic, which can include a case study, lessons learned, or an industry update. This is followed by a 40-minute peer discussion, with the leader facilitating questions, feedback, and practical exchange. The final 10 minutes are dedicated to aligning on five clear industry recommendations to share back with the wider audience.

Choose one topic that aligns with your most urgent priority.

1. Starting Your First Agentic AI Pilot Without Over-Promising - Travis Cavanagh, Accelerated Focus

2. OT Cyber and AI – Joint Playbooks for IT, OT and Security.

3. Proving AI's Bottom-Line Impact: From Unit Economics to Portfolio ROI - Nizar Mohamed, IBM Consulting Canada

4. Fueling GenAI with OSDU: Taxonomies, Security, and Speed

5. Governing GenAI and Agentic AI in Canadian Energy, Risk, Liability, and Guardrails

6. The challenges with AI: Going from POC to Enterprise Solution- Sia Partners

7. Winning Hearts and Minds: Change Management for AI on the Frontlines - Mitch Perreault, Celonis

8. The Data Defects That Derail AI: Prioritizing Quality for Trusted Answers - Stephen Petch, Wrench Solutions

9. Your AI Vendor Blueprint: Build, Buy, or Bolt-On for 2026-2028 – Glen Crockford, Telus

10. LLMs vs. Small Models: Matching the Tool to the Operational Task

11. AI at the Edge: Solving Power, Connectivity, and Harsh Environment Challenges - Jesus Borobia, PowerTrunk

12. What Makes AI Stick: Trust, Adoption, and Accountability - Christian Keon, Nanoprecise Sci Corp

13. Replacing High Friction Manual Processes with Agentic AI - Session by Xerox

14. Supply Chain and Contractor Management - Using AI Without Breaking Relationships – Carl Hammersburg, SAS

15. Canadian Operator Challenges, Canadian Operator Solutions? 

16. AI at the Edge: Secure, private and customized to your needs - Kevin Campbell, HP

17. Cybersecurity & AI- Amir Ashuri, EY

18. GenAI Disrupting Oil & Gas: Rapidly Deploying the Use Cases That Drive Margin, Safety, and Speed- Rodrigo Coronado, Avanade

• Sharing operator results for maintenance, production tuning, and leak detection to show real outcomes
• Quantifying value using fewer incidents, higher output, and lower energy cost to build the business case
• Shortening time to value by targeting data that already exists to move fast
• Sustaining results by tracking model quality and user adoption to avoid drop off

• Deploying AI models that can run reliably at remote well sites, compressor stations and power facilities.
• Managing model drift, updates and synchronization when connectivity is intermittent.
• Defining the right balance between edge processing and cloud intelligence for Canadian geographies.

• Running visual and sensor-based anomaly detection on edge devices along pipelines and facilities.
• Reducing bandwidth, latency and storage by sending only alerts and essential metadata upstream.
• Equipping integrity and field teams with timely, trustworthy alerts that fit existing workflows.

• Closing the gap between analytics, recommendations, and real decisions. - Aashnee Kamboj, Nanoprecise Sci Corp
• Data Quality, Retrieval and Trusted Metrics Across the Asset Lifecycle - Bob Jessey, SIA Partners
• AI Is Only as Smart as Your Data: Modernizing Land & Asset Intelligence to Scale Digital Transformation - Samantha Bush, Pandell. An ESG Company