How Shell’s Former AI Chief Will Accelerate AI for Oil & Gas

Decarbonisation and energy optimisation are areas that many industries are working to improve, with the energy sector one of those most in the spotlight.

The intersection of AI and heavy industry is becoming increasingly crucial to digital transformation. The International Energy Agency (IEA), in its Why AI and Energy Are the New Power Couple report, emphasises that AI’s ability to analyse vast, complex datasets and optimise operations is revolutionising the way energy systems are managed, making grids smarter, more resilient and more efficient. 

Although a lot of the IEA’s focus here is on the electricity sector, renewables integration and grid management, oil and gas is still feeling the benefits of AI.

Dan Jeavons, following two decades at oil and gas giant Shell — his last role being its AI boss — has moved to join Applied Computing as its President, marking what could be a pivotal moment for the energy sector’s digital future.

Orbital: Transforming oil and gas 

In his new role at Applied Computing, Dan will help drive the expansion of its flagship product, Orbital — an AI platform that delivers optimisation solutions for refineries and petrochemical facilities.

Applied Computing’s Co-Founder and Chief AI Officer Dr Sam Tukra says: “Orbital is an AI system designed specifically for the industrial world."

“It combines deep learning, physics and language understanding to provide transparent, real-time decisions operators can trust, because transformation doesn’t just need intelligence, it needs credibility.”

The key benefits of deploying Orbital are:

• Real-time optimisation: Orbital employs models that integrate real-world physics and engineering principles, enabling dynamic process optimisation for refineries and chemical plants
• Data utilisation: Unlike many legacy systems that use just a fraction of available process data, Orbital claims to harness nearly all data points — offering substantially greater operational insight and accuracy
• Industry results: In live deployments, Orbital reportedly delivers 75% cost savings versus traditional cloud-based platforms and can pay for itself in as little as 10 weeks. For example, in pilot projects, it improved carbon prediction accuracy by more than 50% compared to incumbent models

“Orbital is by far the most advanced AI model I’ve seen for industrial environments," Dan says.

“Its ability to integrate physics into leading edge AI makes the product stand out. The team is set up to tackle the complexity of real-world energy challenges head-on — not with hype, but with precision, speed and impact."

“The energy transition requires more than vision — it requires execution — and Applied Computing has built something that actually works, today. 

“I’m deeply honoured to join this team at such a critical moment.”

The need for AI in the energy transition

Due to the scale and urgency of the energy transition, digital technologies — especially AI — are considered critical enablers for decarbonising legacy infrastructure and optimising increasingly complex energy systems. 

With its ability to enhance operational efficiency, predictive maintenance and decision-making, AI is enabling companies to respond to fluctuating energy demands and stricter environmental regulations.

“From optimising renewable energy generation to managing distributed energy resources and market integration, AI enables the agility, intelligence and data analytics advancements needed to lead in new energy business models,” IBM says in its Oil and Gas in the AI Era thought leadership post off the back of its IBM Institute for Business Value (IBM IBV) survey.

Its research finds that 56% of executives say AI will enable new technology capabilities that fundamentally transform their business model and 70% agree it will improve their ability to navigate market disruptions. These include demand shifts, geopolitical instability and the emergence of green hydrogen and other lower emission alternative fuels and products.

“Leveraging AI marks a fundamental shift in how oil and gas companies can gain an edge but requires a balance between investments in productivity and innovation,” IBM says.