• 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.

• 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.

• Moving beyond generic chatbots to industry-trained models that understand Canadian geology, acronyms and asset taxonomies.
• Connecting domain-specific agents to existing subsurface, drilling and production workflows without disrupting safety or regulatory obligations.
• Lessons from early deployments with Canadian operators on data prep, change management and user trust.

• 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 10-minute talks. One messy data problem, one approach, one result.

• Cleaning up decades of asset and equipment hierarchies to support AI in maintenance and integrity.
• Using medallion style (bronze to silver to gold) architectures during S4HANA and ERP upgrades so AI is not built on sand.
• Tackling M and A data chaos in Calgary portfolios so production, finance and land data finally line up.

• Mapping where a 200-to-500-person company actually started: what was in scope year one and what was not.
• Showing the first three use cases that delivered value – and which “cool ideas” were parked.
• How IT, operations and accounting cooperated to fund and sustain the work without a huge central program.

• Criteria Canadian operators are using to pick “safe to learn” AI use cases under strict safety, environmental and regulatory scrutiny.
• Designing governance, testing and human oversight so experiments do not undermine trust with frontline staff.
• How to communicate guardrails clearly to executives, engineers and unions.

• 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.

• Integrating AI into SCADA, DCS and field systems without weakening existing defense in depth.
• Using AI for anomaly detection in control environments while managing false positives and alarm fatigue.
• Aligning with Canadian critical infrastructure requirements and expectations from regulators and insurers.

• How CIOs and technology leaders from Calgary operators are prioritizing AI and digital investments for the next two years.
• Where they see value in working with global vendors versus local specialists and startups.
• What they wish vendors and consultants would do differently when pitching AI to Canadian operators.

• 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.

Rapid 10-minute talks to spark discovery.

• Letting agents handle low-value ticket triage and documentation so Canadian engineers focus on complex work.
• Using agents to orchestrate well surveillance and exception management across gas fields.
• Agents as copilots for project managers and planners: from risk registers to look-ahead schedules.

• Automating document search, extraction and reconciliation across land files, agreements and regulatory submissions.
• Reducing cycle time and error rates in land and regulatory workflows while preserving defensible records.
• Working with legal and land teams so AI supports professional judgment rather than replacing it.

Get a rapid-fire preview of the future in this high-energy session. Ten hand-picked start-ups 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.

• Defining thresholds and rules for autonomous versus human-approved actions in Canadian control environments.
• Setting up audit trails, rollback and “kill switch” mechanisms that operations and regulators both accept.
• Stories from control rooms and field supervisors on when they overrode AI and why that built or eroded trust.

• Applying non-deterministic models to process data to reduce power and fuel use on existing facilities.
• Working with control engineers to integrate AI suggestions safely into existing DCS and procedures.
• Quantifying the combined value in energy cost, emissions and reliability.

• 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.

• Deploying AI in procurement to classify spend, flag savings and support sourcing decisions.
• Using chatbots and self-service tools to resolve simple invoice and PO queries without tying up supply chain staff.
• Applying advanced analytics in finance to improve forecasting, capital planning and variance analysis in volatile markets.

Part talk, part live walkthrough.

• Walking through a simple pattern for turning one repetitive task into a small agent or copilot.
• Showing how an individual engineer, planner, analyst or land professional can start, even without a big program.
• Discussing how to share and harden successful “personal” tools so they can scale safely inside the company.

Move from presentation to problem-solving in these highly interactive, peer-driven roundtables. This is your opportunity to roll up your sleeves and tackle your most pressing AI implementation challenges with a small group of fellow operators facing the same hurdles.

Choose one topic that aligns with your most urgent priority.

• Starting Your First Agentic AI Pilot Without Over-Promising.
• Supply Chain and Contractor Management – Using AI Without Breaking Relationships.
• OT Cyber and AI – Joint Playbooks for IT, OT and Security.
• Proving AI's Bottom-Line Impact: From Unit Economics to Portfolio ROI
• Fueling GenAI with OSDU: Taxonomies, Security, and Speed
• Governing Autonomous Agents: Approval Matrices, Audit Trails, and Rollback
• Winning Hearts and Minds: Change Management for AI on the Frontlines -
• The Data Defects That Derail AI: Prioritizing Quality for Trusted Answers
• Your AI Vendor Blueprint: Build, Buy, or Bolt-On for 2026-2028
• LLMs vs. Small Models: Matching the Tool to the Operational Task
• AI at the Edge: Solving Power, Connectivity, and Harsh Environment Challenges

• Framing AI proposals around reliability, emissions, safety and cost, not just “innovation.”
• Building simple but credible financials, from unit economics to portfolio impact.
• Structuring approvals, co-funding and vendor contracts in a way that works for Canadian operators.

• Using RPA, AI and workflow automation to streamline HR, finance and other support functions.
• Choosing when to use pre-built vendor tools versus custom in-house solutions.
• Governance and change practices that keep shared services and business units aligned.

• 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.

• Building retrieval systems that can reach OT and IT data sources cleanly and safely.
• Curating metadata and taxonomies that match how Canadian operators plan, operate and maintain assets.
• Linking data quality metrics directly to financial and operational outcomes so fixes are funded.

• Automating triage, routing and simple resolution in IT and operations support centers.
• Learning from historical tickets to suggest likely fixes and supporting technicians with context.
• Measuring improvement in resolution times, satisfaction and freed-up expert capacity.

• Capture one concrete commitment per attendee for the next 90 days.
• Share top actions from Canadian operators to create peer pressure and inspiration.
• Close the conference with clear next steps rather than generic “see you next year.”