CERAWeek by S&P Global 2024: Navigating AI and the digital revolution

In a CERAWeek session on Monday, March 18, entitled, “Navigating A.I. and the Digital Revolution,” S&P Global President and CEO Doug Peterson conducted an extensive conversation with Accenture Chair and CEO Julie Sweet. Peterson and Sweet covered a lot of ground, as they examined the evolution of artificial intelligence to where it is today.

In her opening, Sweet presented a question to attendees: “Is using generative A.I. one of your top three priorities going into 2024?” The answer from the room full of attendees was overwhelmingly “yes.”  However, she asked another question in a similar vein: “If generative A.I. did not already exist, would you still consider its development and use it as a top-three priority?”  Put that way, the response was considerably lower; in her words, “about zero to five percent” still said “yes.”

There has been a massive shift in the advent of generative A.I. in the last few years, Sweet noted, and the present represents a critical juncture for companies looking to take advantage of it.  However, unlike many industries already looking to use A.I. broadly, the energy industry—including oil and gas—has been the caveat to this attitude. Saudi Aramco has been ahead of the curve on A.I. usage thus far, but even that firm’s adoption of the technology pales against the scale of other industries.

The energy industry faces enormous opportunities with generative A.I., but there is considerable preparation needed to make use of this new technology, according to Sweet.  The Accenture executive laid out some of the key ways that the company has been changing in response to A.I., starting with the introduction of TQ (Technology Quotient). For Accenture, A.I. pre-existed the more recent generative A.I., and TQ allowed them to assess and train more than 6,000 employees on core technologies like A.I..

Where to begin? A big mistake, Sweets stressed, is trying to do too much or do things in areas that do not scale with generative A.I.  Spending money without a clear path to generative A.I. is another common mis-step, but there is a long list of where the technology could be used, Sweet pointed out. She said discipline is needed to focus on specific areas—especially in early stages. For Accenture, she presented a simple rule: “If we as a company can do it, can we replicate it with other clients?”  If the company can, then better benefits can be passed on faster to clients.”

There are three main areas that Sweet emphasized when considering how the energy industry can be ready for generative A.I.: companies need their technology stacked, A.I. rotation and talent rotation.  The first of these elements, she noted, is a simple formula: “You need a digital core with the right cloud, right security, right data backbone, and the right applications.”  As she mentioned before, many companies haven’t modernized yet with a data cloud, and without the necessary data foundation, they cannot take advantage of generative A.I. 

The second key area concerns A.I. rotation, which encompasses a company’s ability to change their processes and ways of working to integrate and maintain compliance for generative A.I. Companies need enough flexibility within these processes to use generative AI efficiently. 

And third, as she referenced earlier with TQ, talent rotation allows a company to have the employee talent to take advantage of generative A.I., which includes training. She noted that companies have a responsibility to “bring employees along” with training and education on A.I., which would allow them to access talent in this area and thus more easily rescale as the technology matures. For Accenture’s part, spending in this area has totaled more than $1 billion thus far, with more than $3 billion to be added to that number in the coming years. In her words: “Thriving communities can only thrive, if we invest in people.”

Implementing guardrails. Of course, as with any new technology, the possible risks often present themselves right next to any potential benefits. Such is the case with A.I., and when asked about the topic, Sweet was quick to stress the importance of guardrails. “[The data] cloud is plumbing at the end of the day,” she said, in contrast to AI, which “can change every enterprise fundamentally.” She characterized the technology as “dynamic,” and as such, the responsibility aspect of it goes beyond the standard data management protocols of previous digital advancements. Similar to her earlier comments about creating a firm technological foundation for A.I., Sweet said that setting guardrails and responsibility measures into place should be the foundation of compliance.

In her closing, she put into words what most companies recognize—that AI represents one of the “most exciting times to lead companies.”  Breakthroughs in many areas—like improving operations efficiency, reducing greenhouse gas emissions, and so on—are that much more possible. Indeed, Sweet pointed out, A.I. is already being used to improve operations, production and exploration, the latter in seismic data analysis. A.I. represents huge opportunities for the future, and the energy industry needs to get involved and use those opportunities to enhance the core of what it does.