-    Reviewing the Digitalization and AI landscape and its importance to the Oil & Gas sector
-    Highlighting how the industry has revolutionized operations to optimize operational processes 
-    Showcasing innovations that have successfully leveraged Digitalization and AI to improve leading levels of efficiency, sustainability, and safety in operations
 

-    Emphasizing the role of policies, research facilities, academia, and innovation hubs in driving initiates
-    Discussing potential obstacles and hurdles faced by the Canadian digitalization and AI ecosystem
-    Identifying emerging trends that can be adapted to excel in ongoing and future projects
 

-    Evaluating AI-driven monitoring solutions that continuously gather and analyze data in real-time
-    Exploring the types of AI algorithms utilized to analyze data for potential safety risks
-    Using scenario planning to prepare for potential safety incidents
-    Addressing the process of integrating AI-powered safety protocols into existing operations

-    Highlighting how technologies improve energy efficiency to minimize emissions and meet regulatory requirements.
-    Optimizing operations, including refining, extraction, and production, to reduce emissions
-    Presenting specific successful projects that have significantly contributed to emissions reduction 

-    Evaluating data collection, storage, and management techniques
-    Establishing the critical role that model and metric evaluation play in the success of AI and digitalization projects and developing strategies to achieve this.
-    Choosing the right algorithm or model architecture to train and validate datasets efficiently
-    Understanding the ethical considerations when handling data to avoid data breaches
 

-    Acknowledging common apprehensions and misconceptions surrounding the adoption of new technologies
-    Developing Hands-On Training and Simulation using Augmented and Virtual reality
-    Discussing strategies for encouraging ongoing skill development and familiarity with evolving AI technologies
 

-    Defining quality data in the context of Al and Digitalization 
-    Understanding the challenges associated with data collation 
-    Establishing data quality metrics and benchmarks 
-    Best practices for leveraging external sources for data collection
 

The lighting round will showcase 5 case studies from speakers who each have 10 minutes to present their update on the Problem, challenge, plus the solution. There will be a short group Q&A with the audience at the end.

•    Case study: Operational tech and leveraging predictive maintenance and analysis- using historical data to make decisions  
•    Case study: Cybersecurity concerns and data integrity
•    Case Study: Oil field crisis response and management
•    Case study: Integrating data from multiple systems for informed decision-making
•    Start-ups will showcase the latest developments in AI models and discuss effective techniques to increase operational efficiency, highlighting real-life examples from operators.

-    Understanding how data has become a critical asset in the industry, influencing exploration and production to operations and sustainability efforts
-    Discussing the complexities of handling large and diverse data sets and the need for skilled individuals who can extract meaningful insights
-    Explaining what it means to be a data storyteller and the skills required
 

-    Identifying the challenges and unexpected expenses companies may face during technology adoption
-    Prioritizing scalability to reduce long-term costs and embrace ROI
-    Understanding the social, environmental, and economic benefits of technology  
-    Providing insights into the criteria for selecting technology vendors and partners

-    Exploring the elements that make up a digital twin, including data integration, sensors, modeling, and simulation
-    Unlocking new possibilities for further innovation and integration of digital twins 
-    Discussing how AI algorithms process and interpret data from digital twins to provide real-time insights and predictions 

-    Maximizing the Capabilities of Digital Twins for optimized operations.
-    Overcoming Unexpected Costs in Implementation ensuring a streamlined and cost-effective integration process.
-    Understanding the Social, Environmental, and Economic Benefits of Implementation promoting safety, sustainability, and economic growth in the industry.
 

Each round table has a different topic, and attendees can select the round table they would like 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. All the recommendations will be summarized in the post-event report.

Topic options:
-    Strategies for Maximizing Asset Reliability
-    Utilizing AI technologies to improve safety protocols and crisis response in oil and gas field operations 
-    Ethical and legal considerations of AI
-    Innovations in Predictive Maintenance and Analysis for Operational Excellence
-    Emissions Reduction and Sustainability: AI's Role in Achieving Targets
-    Strategies for training, upskilling, and reskilling the workforce of the future 
-    Data Management Challenges in Oil & Gas: From Collection to Deployment

-    Reviewing the pros and Cons of internal and third-party deployment 
-    Developing a hybrid approach to technology implementation 
-    Case studies highlighting successful implementation, key takeaways, lessons learned, and best practices

-    Reviewing the current landscape of staff shortages and training challenges in the oil and gas sector
-    Exploring how technology, including AI and digitalization, can be leveraged to bridge staffing gaps and enhance training programs
-    Highlighting successful strategies and initiatives implemented by companies to address staff shortages and training requirements
 

-    Discussing the path forward to the industry ensuring a collective approach towards embracing digital transformation
-    Preparing for technology shifts proactively adapt to evolving technological landscapes
-    Highlighting latest advancements in AI and digitalization technologies and how they are reshaping the landscape of the oil and gas industry

-    Exploring the convergence of AI and digitalization in supply chain operations
-    Addressing the potential benefits, challenges, and considerations for implementation
-    Discussing the role of AI in enhancing visibility, resilience, and efficiency in supply chains