OTC 2025: Digital transformation offshore
OTC 2025 day three kicked off with a keynote speaker panel on the ongoing challenges of digital transformation in the offshore sector. To truly leverage the time and cost savings that digital innovation offers, several key issues need to be addressed, per the panelists: understanding the importance of data across multiple industry verticals, ensuring that data is accessible and applicable, and integrating existing technologies like digital twins, AI, and automated and unmanned applications.
Across various digital technologies, a critical keystone must be addressed to provide a suitable digital foundation: quality data and access to it. As Expert Partner Jim Claunch, Bain & Co., noted, “we are an industry that makes money horizontally, but…our operations are set up vertically, in silos.” This siloing of data presents an issue very quickly when operators look to apply the technological advances available. “No one likes to talk about data,” Claunch pointed out, “…but data is at the core [of digital transformation and AI].”
However, utilizing existing data to its fullest potential is a complex challenge, with data management still moving slow, per Claunch. Part of the battle is shifting attitudes towards the surrounding infrastructure for digital technologies, as was pointed out by Senior Managing Director Vivek Chidambaram, Accenture. “We have found it very hard to communicate with the IT organizations in our companies, to support evolving workflows,” he noted, emphasizing the need for a shift from in-depth knowledge for a single vertical to broadly applicable horizontal knowledge, when it came to supporting rapidly changing technologies and its associated workflows.
Another critical component of utilizing data involves greater data efficiency and efficiency on the part of hardware used to process it. As Claunch pointed out, “the cost [for components and hardware] is too high,” and as energy demands grow, that is likely to also raise costs. “We are very early in the age of AI,” Chidambaram noted, emphasizing that now the focus needs to be on making current computation more efficient and less energy demanding. In addition to lowering costs where possible, another key area is maximizing the value from AI and other digital advances. For example, while the concept of a digital twin has been around for a while, “the digital twin today is primarily diagnostic,” according to Claunch. This is set to change in the coming months and years, he said, as better integration and advances allow for more real time data and predictive maintenance applications.
The other key component of leveraging AI technology in particular involves what Claunch named, “agentic AI." Agentic AI, or more simply, an AI agent, is designed with a specific purpose in mind and, if paired with multiple other agents, can overcome the limitations of a singular LLM. As one example, Claunch noted that by implementing agentic AI, predictive maintenance could be implemented that could take multiple factors into account, from predicted wear and tear of components to maintenance schedules, to upcoming weather conditions that might exacerbate the work life of a component or the location and travel time for repair or replacement materials. Further, Chidambaram added that the use of cascading agents to complete a series of specific but difficult tasks can further extend agentic AI’s utility.
With the capabilities that AI and digital technologies as a whole present to reduce emissions and increase production in the offshore energy sector, “we’re already behind…we’re playing catchup,” said Claunch. Now—according to Claunch—it’s up to the offshore industry to “lean in.”
