This past February, 150 senior operations, digital, data and AI leaders from across the energy sector gathered for the 2025 AI in Energy Summit, to learn how AI, Data, ML and Generative AI can be leveraged to drive asset, supply chain, and operational efficiencies.

Through 10+ real-world operator case studies, 4 dedicated tracks, four 90-minute operator-led workshops, multiple keynotes, and much more, the AI in Energy Summit provided the valuable insights to show industry leaders how to:

• Create an AI strategy
• Maximize AI based maintenance and asset management
• Identify use cases for Gen AI
• Build the data foundation for AI
• Scale AI projects
• Build, buy, or both? How to future proof your AI investment
  

Download your free copy of the event guide today to explore why your peers connected this past February 24-25, 2025 in Houston, and what you missed!

The second edition of the AI in Energy Summit was a bustling hub of learning, networking and collaboration, attracting 150 senior operations, digital, data and AI leaders.

On February 24th and 25th, discussions not only highlighted the optimal applications for AI operability to enhance and revolutionize operations but also addressed often overlooked holistic elements.

In our 2025 Post Event Report, we summarised in one handy document, the summit's;

• 5 Key Takeaways
• Key Audience Stats 
• Highlights from our Conference Chair
• 2025 Agenda Highlights
• And, an update on AI in Energy 2026!

Our commitment will always remain the same - to avoid the hype and give you the practical tools you need to put AI into practice in your operations.

Asset reliability is a critical key performance indicator in any asset-driven business. An IBM study revealed that hybrid AI/ML models, combined with generative AI, can enable operational teams to prioritize and reduce serial failures by 25%–50% while increasing site reliability by 10%–15%.

Dow Chemical Company is currently leveraging GenAI capabilities to automatically extract key failure information that enables the analysis of reliability metrics from multiple sources and sites, including both structured and unstructured data.

Featuring exclusive insights from Technical Leaders and Executives at Dow, download the case study to:

• Learn how Gen AI can address operational challenges such as improving data quality and streamlining processes in asset-driven industries
• Understand how Dow is leveraging AI to extract, clean, and analyze maintenance data
• Learn how new AI tools can complement rather than replace existing systems, ensuring continuity while enhancing capabilities and resource optimization
  

An IBM study stated that about 74% of energy and utility companies globally are either implementing or exploring AI, with the majority intending to leverage it to improve operational efficiency. Generative AI (Gen AI) enables the industry to dig deeper into its data and extract valuable insights in a faster, easier, more accessible way.

Ahead of the AI in Energy Summit this past February, we sat down with event speaker Partha Chatterjee, Principal, Data Analysis at Shell to better understand how to improve operational efficiency through AI.

Read as Partha reveals practical strategies and lessons learned for operators looking to leverage Gen AI for real-time decision-making, with a vision for using Gen AI tools to streamline complex workflows.

Key takeaways include:

• Implementing Gen AI in operational settings and how it shapes digital strategies
• Key considerations when training Gen AI in industrial settings
• What ROI to expect from incorporating AI or Gen AI within operations

This case study features industry insights from bp, ASUG and Chevron Phillips Chemical Company. Explore individual perspectives into the strategic deployment of AI, illustrating how organizations can leverage technology to unlock new opportunities, drive sustainable growth, and shape the future of energy operations. Hear insights from:

• Martin R. Gonazelz, Innovation and Technology Principal, bp
• Laura Tibodeau, Global Digital Innovation & Transformation Leader, ASUG
• Ra Inta, Head of Data Science, Chevron Phillips Chemical Company

Download the Case Study today.

Interest in AI is at an all-time high, especially within the energy sector. Many companies are already piloting AI-powered applications to decarbonize operations, improve safety and overall operational efficiency. However, to push into the next frontier of efficiency and sustainability, the industry needs a clear vision and mission on how to harness the true innovative potential of AI and understand how it fits within their current digital strategy.

Ahead of our upcoming AI in Energy Summit in Houston, from June 17-18, we’ve highlighted the top five applications of AI in the energy sector, delving into renewable energy, smart grids and more.

Download our handy fact sheet today.