An Olympic-sized effort: CIOs prep for AI disruption in 2026

AI disruption is expected to continue in 2026, pushing companies to adapt to the evolving technology and to scale up with the market.

That was the consensus of leaders from the International Olympic Committee, Moderna and Sportradar, who discussed their AI strategies and 2026 plans at a panel held at the recent Reuters Next leadership summit in New York City.

Moderator David Wong, chief product officer at Thomson Reuters, asked each how their organizations invest in AI and what significant investments they intend to make in the technology next year. One takeaway? The decision to build AI in-house or buy into third-party resources goes beyond potentially cutting costs.

“Internally, we use AI to optimize processes and, of course, to basically make ourselves more efficient, ” said Nicolo D’Ercole, executive vice president for AI and technology at Sportradar. His company uses AI to support its developers and elevate productivity. AI is also put to work for public and customer-facing needs, he said.

When it comes to those external needs, D’Ercole said the company uses AI in two ways: to build products and leverage its data. “We really rely on the most common foundation models, like the Gemini, the OpenAI models, the Anthropic models. We use all of them, kind of depending on the use case,” D’Ercole said.

Sportradar develops data services and other tech resources for professional sports leagues including the NBA, NASCAR and the MLB. For those products, D’Ercole said his company looks beyond third-party AI and builds its own models for specific sports, trained to use data to predict what may happen in the next few seconds in a game.

For now, D’Ercole said, companies that are not primary developers of AI can have a tough time delivering in-house models at the scale of major players. “It’s very hard … to compete with the large language model builders for the generic use case,” he said. Even if a company finds momentary success with an in-house AI model for general needs, the major players in AI keep moving and continue to pull in huge investments, he explained, discouraging others from trying to develop for generic AI uses in-house.

However, when it comes to specific use cases with proprietary data, D’Ercole said it can be worth building AI models in-house if the organization believes it can make a difference.

Moderna’s  prescription for AI internal adoption

Moderna leverages AI to redefine work, said Tracey Franklin, chief people and digital technology officer at the pharmaceutical and biotech company. “We are applying AI to most areas of the business. But how we’re doing that is looking at what we call a flow of work.”

Franklin said that redefinition of work includes exploring software, robotics and AI, combined with the human element. Further, she said her role at the company was shaped around such considerations.

Traditional human resources management tends to focus on workforce planning, Franklin said, while the IT team focuses separately on IT portfolio planning. Moderna combined those elements rather than keep them siloed. “We’ve brought that together to say that’s just how work gets done in the future, as we have a broad-based approach to AI,” she said.

[link VIDEO]

Moderna was an early adopter of this recent upswing in AI. “We have a partnership with OpenAI, and we moved quickly to democratize that across the organization,” Franklin said. This meant every single employee started to use AI, she said, with the potential for further development and use to be explored.

Franklin said Moderna refined its AI strategy further to include assessing related software already in use, such as SAP and Workday, to understand what those vendors have on their roadmaps regarding AI. Moderna continues to look at what it can feasibly build in-house.

“We’re identifying what’s unique to our company and where we can focus our effort and our time and our engineers to really have that unique advantage,” she said.

IOC: A marathon rather than a sprint to AI gold

AI is already part of the international sports scene. Ilario Corna, chief information and technology officer for the International Olympic Committee (IOC), said his organization launched the Olympic AI agenda in April 2024 after six months of lead-up work.

“For us, it was very important to go out as broad as possible to understand where we should apply, where we should not apply AI,” Corna said.

The Olympic AI agenda contains five points of focus:

“Everything that we do needs to attach one of those five action items,” Corna said.

The IOC has used off-the-shelf AI in its pursuits, he said, as well as some in-house development. This includes a model in the works for video analytics for each sport based on the differences in each type of competition.

Small models, big adoption in 2026? It’s all about culture

D’Ercole said he expects the tech race to continue among the big providers with their signature, marquee large AI models, but there may be more adoption and scale to come from lower-cost alternatives.

“What is maybe more interesting is that the smaller models — the Gemini Flash, the GPT Nano and the Claude 2, all of them — will become good enough to be applied in day-to-day applications in technology,” he said.

Corna concurred that smaller models have the potential to see accelerated adoption in 2026. He also said that open source models are gaining popularity.

Franklin said that if a company decides to build its own AI, it should be built into the culture.

“It has to be the way that you operate. If it’s important to you as an organization and you want to advance it, it should be critical that you develop your culture around the use of technology and innovation,” she said.

Adoption and interest in AI tend to increase in an organization when employees see they can use it to innovate and upskill themselves, Franklin said. She went on to say that leading with cost for AI is ill-advised to motivate a company to explore its capabilities. “No one gets excited about cost and cost savings,” Franklin said. “That’s not a driver of an employee. A driver of an employee is innovation.”