Modernising digital foundations for scalable AI

To remain competitive and resilient in an evolving energy landscape, energy companies must take real action to revamp their digital foundations through implementing pragmatic transformation strategies. A robust, flexible and scalable digital core is essential to supporting the proliferation of rapidly advancing AI capabilities. From data infrastructure to selecting suitable AI models and building intelligent agents, leaders are moving beyond dialogue to demonstrate real solutions. Their approaches are rooted in inclusive collaboration and showcase how being realistic and ambitious can drive future success.

Attendee insights:

Gain insight into how leading executives are reconditioning their digital core to remain agile, scalable, and value-driven in the rapidly evolving energy sector.

Innovative solutions for overcoming the AI skill gap in a competitive talent market

An informal panel-style session with panellists sat in a circle surrounded by the audience. After an initial conversation, led by a facilitator and the panellists, the audience will be invited to comment on and ask questions to the wider group.

A recent IEA report on the relationship between energy and AI found there are only 22,000 AI specialists globally across all industries, and 61% of large businesses surveyed in the US and UK, reported a lack of staff with sufficient AI experience. As a result, all industries are competing for a limited skill set. Many energy companies are approaching this challenge through the upskilling and retraining of their existing workforces, as well as implementing innovative new programming such as back-to-school initiatives. However, cost-effectively achieving this, at scale, while managing the increased power demand for all of the above is a challenge.

Attendee insights:

Learn through case studies and demonstrations how digital twin technology can be used to overcome challenges when it comes to implementing pre-emptive physical asset monitoring.

Enabling AI in the energy systems of tomorrow

AI has and will continue to revolutionise the energy sector, driving digitalisation and predictive capabilities. To maximise the increased efficiency and productivity AI and machine learning can deliver, open technology standards that foster greater data interoperability will be essential to overcome many of the cybersecurity and data management concerns. Organisations like the Trusted Energy Interoperability Alliance (TEIA) - which aims to create standards and agreed-upon formats and protocols for secure and interoperable data communications within the energy system—and the Open AI Energy Initiative (OAI) - an open ecosystem of AI-based solutions for the energy and process industries - are working toward this. To mitigate risks, businesses must standardise security formats, and compliance requirements for energy hardware and software, and develop internal AI specialists to deliver transformation at scale.

Attendee insights:

In this Action session, gain exclusive insights into the standards being developed by the TEIA and OAI and how they can be implemented by businesses to achieve an interoperable and trusted energy ecosystem.