-    Optimizing production and maintenance in older assets despite infrastructure limitations
-    Identifying the types of assets that benefit most from AI-driven upgrades in legacy fields and how to prioritize them
-    Overcoming challenges in retrofitting AI technologies into aging infrastructure while minimizing disruption to operations
 

-    Discovering innovative frameworks that enable effective oversight of autonomous AI agents
-    Designing scalable governance strategies to maintain control across decentralized operations
-    Implementing robust management protocols to mitigate risks and ensure compliance
-    Unlocking hyper productivity by seamlessly integrating AI agents while preserving organizational control
 

-    Reviewing how AI is applied across different timelines and stages of operations:
     o    Horizon 1 (short-term, immediate applications like efficiency gains)
     o    Horizon 2 (mid-term, such as integrating larger datasets for predictive capabilities).
     o    Horizon 3 (long-term, transformative uses like full automation)
-    Discussing the challenges and benefits of adopting AI technologies at each stage

-    Understanding how AI algorithms are revolutionizing document processing in areas such as contract reviews, regulatory compliance, and data analysis
-    Building a knowledge base with AI to capture internal expertise and ensure knowledge retention, especially with an aging workforce
-    Real-world examples of AI applications in document management and knowledge sharing

-    Exploring real-world applications developed by SoftServe to automate energy processes
-    Automating procurement and data processing to drive operational efficiency
-    Improving CCTV monitoring and analytics for enhanced situational awareness
-    Optimizing decision-making and cost reduction through AI-driven autonomous agent

The lightning rounds will showcase case studies from speakers who each have 15 minutes to present their update on the Problem, challenge + solution

-    Faster, Safer, Better: Unlocking Operational Efficiencies with GenAI and Agentic AI
     Diti Sood, Bolo AI
-    Technical Use Case: AI for Workforce Augmentation: Empowering Engineers and Field Personnel
     Giang Mai, Bp
-    The Imperative of AI Literacy to Unlock Return on AI Investments
      Catalina Herrera, Dataiku

-    Celebrating the contributions of women in AI and the challenges they face in the traditionally male-dominated oil and gas industry
-    Practical strategies for increasing diversity and inclusion within AI roles
-    Case studies of successful women leaders in AI and their impact on the industry
 

-    Building audit-ready, transparent AI systems that can demonstrate compliance with new regulations
-    Establishing internal AI governance frameworks to monitor performance and mitigate risks
-    Aligning AI investments with regulatory requirements while ensuring a focus on innovation
 

The lightning rounds will showcase case studies from speakers who each have 15 minutes to present their update on the Problem, challenge + solution

-    Taking Action on Predictive Models with Agentic AI 
     Justin Swansburg, DataRobot
-    The journey of unification of data platforms at Bp
-    Session by Cohere

-    Highlighting strategies for data standardization using data mesh and data fabric
-    Overcoming data silos to enable cross-departmental AI applications
-    Understanding the role of unified data frameworks in driving more accurate AI models

The lightning rounds will showcase case studies from speakers who each have 15 minutes to present their update on the Problem, challenge + solution

-    The Future of Predictive Maintenance: A Convergence of Physics & Machine Learning 
      Ruzbeh Homji, Mechademy
-    The Role of DEI in Shaping AI and Machine Learning
     Srimoyee Bhattacharya, Shell Oil Company
-    Reserved session
 

-    Providing first-hand insights from the CURT POC, including challenges faced, solutions developed, and measurable impacts on knowledge ownership, attribution, and monetization.
-    Adapting iSPAI’s platform and its AI agent, Giblet, to meet the unique needs of Oil and Gas, building on the success of iSPAI in Construction.
-    Exploring the ways decentralized AI and blockchain technologies can address knowledge gaps, boost workforce capabilities, and drive new revenue opportunities in Oil and Gas.
 

-    Addressing user concerns by mitigating fears related to job displacement, data privacy, and technology reliability
-    Developing and implementing effective onboarding and training programs to equip users with the necessary skills for working alongside AI systems
-    Fostering a supportive culture by engaging leadership, encouraging continuous feedback, and providing ongoing support to maintain user engagement and adaptability
 

-    Exploring approaches to AI security, focusing on risk mitigation strategies for AI models in critical operations
-    Discussing integration challenges related to security protocols and how to protect AI systems from threats
-    Including examples of risk management frameworks that have been successfully applied to AI deployments in sensitive environments
 

In the Oil and Gas industry, bridging the gap between field operations and corporate data holdings is critical for efficiency and decision-making. This session demonstrates a system that integrates Augmented Reality (AR) and AI agents to provide field workers with access to real-time data and corporate systems. The system enables workers to visualize, interact with, and create data directly in the field, while maintaining connectivity to digital twins and internet-based services. Learn how this approach supports connected workflows and enhances decision-making in the field.

-    Assessing the current landscape of AI agents, focusing on practical applications and immediate benefits being realized today.
-    Discussing the evolution of agentic AI into more sophisticated autonomous systems, addressing uncertainties and challenges along the way.
-    Considering how these technologies could reshape the oil and gas industry, paving the way for greater innovation and automation in the future.
 

-    Spotlighting AI-driven approaches to streamline supply chain logistics, inventory management, and demand forecasting
-    Reducing supply chain disruptions through predictive analytics and AI-enabled process automation
-    Case studies showing how AI has transformed supply chain operations in oil and gas
 

The lightning rounds will showcase case studies from speakers who each have 15 minutes to present their update on the Problem, challenge + solution
-    Transforming Oil & Gas: Efficiency, Safety, and Compliance Through UiPath Agentic Automation
     Gavin Keeler, UiPath
-    Production Optimization and Downtime Reduction through AI/ML in Permian 
     Amit Kumar, ExxonMobil
-    Reserved session

This exclusive lunchtime session will feature members of the 2025 AI in Oil & Gas Advisory Board sharing their insights on AI’s rapidly evolving role in our industry. We’ll explore the key trends, challenges, and opportunities shaping AI adoption, from sustainability and operational efficiency to workforce integration. Come ready to engage, ask questions, and gain strategic guidance from leaders at the forefront of AI innovation in oil and gas.

-    Uncovering how the OSDU’s open data standards enable robust AI-driven insights for upstream operations.
-    Examining real-world examples where AI applications accelerate data sharing, reduce inefficiencies, and foster cross-industry collaboration.
-    Identifying next steps for integrating AI solutions into your organization’s digital strategy.
 

The lightning rounds will showcase case studies from speakers who each have 15 minutes to present their update on the Problem, challenge + solution
-    Human-in-the-Loop vs. Fully Automated AI: Finding the Balance
-    Lessons Learned from Real AI/GenAI Pilots in Oil & Gas
-    Utilizing BKO AI’s Common Model for Intelligent Connectivity
     Ramzi Deek, BKO AI

Each round table has a different topic, and attendees can select the round table they want to participate in. Round table leaders will spend the first 15 minutes meeting the delegates and providing a case study/lessons learned log/industry update and then moderating a 30-minute discussion with the group where they can give feedback and ask questions. The final 10 –15 minutes will be spent agreeing on 3 -5 industry recommendations. A selection of these recommendations will be shared with the whole audience, and all of them will be summarized in the post-event report.

1. Adapting AI Solutions for Legacy Systems: Overcoming Integration Challenges
   Don Murray, Safe Software
2. Demystifying AI: Bridging the Knowledge Gap
   George Danner, Business Laboratory
3. Data Democratization: Empowering Teams with Data-Driven Insights
   Catalina Herrera, Dataiku
4. Optimizing AI for Edge Computing: Extending AI Capabilities Beyond the Cloud
5. Building Trust in AI Models: Transparency and Explainability
   Tanima Dutta, ONGC Videsh
6. Scaling AI Applications: From Pilots to Enterprise-Wide Adoption
   Sean Mee, OutSystems
7. Empowering Middle Management in AI Implementation: Bridging Strategy and Execution
   Sean Barnes, WSS Solutions
8. Ensuring Data Quality for AI: Proactive Data Management
   Quinn Lewis, Denodo
9. Exploring AI-Driven Predictive Maintenance: Real-World Use Cases
   Justin Swansburg, DataRobot
10. Balancing Automation with Human Expertise in AI-Driven Decision Making
    Gavin Keeler, UiPath
11. Future-Proofing AI Investments: Adapting to Rapid Technological Change
    Dr. Riad Efendi, Technip FMC
12. Using Publicly Available Data to Analyze Hiring Trends and Patterns
    Abhijeet Narvekar, The FerVID Group
13. Predictive Analytics Performance Metrics: Understanding What Success Looks Like
    Ruzbeh Homji, Mechademy
14. The Future of Autonomous AI Agents in Oil & Gas: Governance and Scalability
    Michael Bachman, Boomi
15. Houston, We Have a Solution: Bridging Gaps for Scalable AI & MLOps Innovation
    Pinar Celan, Domino Data Lab

The lightning rounds will showcase case studies from speakers who each have 15 minutes to present their update on the Problem, challenge + solution
-    Explainable AI and Model Transparency in Operational Decision-Making
     Praneeth Reddy Amudala Puchakayala, Regions Bank
-    Production Optimization and Downtime Reduction through AI/ML in Permian 
     Amit Kumar, ExxonMobil
-    The Future of O&G Contracts:  Smart, Automated, and Secure
     Cam Sinclair, Smartchain
 

-    Adapting AI to the Workforce: How the millennial and Gen Alpha workforce will engage with AI tools and what training will be necessary for them to succeed
-    Understanding the expectations of a younger, more tech-savvy workforce and how AI can cater to their working styles
-    Preparing for a Generational Shift: How AI can help transition knowledge from older workers to the younger generation, ensuring continuity in expertise
 

- What is AI and how to integrate it in O&G Asset Management
- The foundation of a digital transformation and AI integration
- A single source of truth for seamless data flows, informed decision-making, and asset performance monitoring.
- Data driven insights on predictive maintenance, risk management and operational efficiency.

-    Understanding when to apply Machine Learning for structured problem-solving and how Generative AI can address unstructured data needs
-    Exploring how ML can supplement Generative AI to create more reliable, explainable, and accurate outputs in oil and gas applications
-    Practical Examples where ML and Generative AI have worked together to optimize operational performance, reduce costs, or drive efficiency