- Speaking at the Fortune Global Forum in Riyadh, IBM’s Ana Paula Assis says companies must transform their operating models to realize the full potential of artificial intelligence. She said companies need a systemic, organization-wide approach that integrates data, technology and trust to realize the benefits of technology. Although AI adoption is growing rapidly, most organizations still struggle to realize measurable returns due to knowledge gaps and limited integration.
Ana Paula Assis, senior vice president and chairman of Europe, Middle East and Africa and Growth Markets, said artificial intelligence has the potential to improve productivity within organizations, but only if business models have shifted. International Business Machines Corporation.
Assis told the audience wealthof global forum In Riyadh, exploring the full potential of AI means taking a “systemic approach” to the technology: “One that is implemented pervasively across the organization, one that integrates silos, one that moves from just experiments and isolated pilots to company-wide adoption,” she says.
IBM research cited by Assis shows that two-thirds of EMEA leaders already see a positive impact of artificial intelligence on productivity initiatives. Saudi leaders claim they see the greatest positive impact, with 84% of leaders in the region citing the positive impact of AI.
However, while most companies are investing in AI at a rapid pace, some have struggled to get the technology past the experimental stage. Number of companies running the entire workflow in the past year Artificial Intelligence has almost doubledwhile the overall workplace Usage of the technology has also doubled Since 2023. However, a recent study from the MIT Media Lab found that 95% of organizations using artificial intelligence do not see a clear return on these investments. This is partly due to the so-called “learning gap” – where people and organizations don’t understand how to use AI tools properly – rather than a problem with the core technology itself.
Integrating new technologies into complex corporate structures can take time. Adopting the technology in a “systems” approach means considering data readiness, openness and trust, Assis said.
“AI is only as good as the data you use to train and enhance it,” she said. “We estimate, or we estimate, that only 1% of the data currently residing in enterprise applications in our own data centers will be impacted by AI. So imagine the opportunities that will be created when we expand that scope.”
Assis also pointed out that enterprises often operate in complex technology environments that require integration and coordination across different systems and teams. She emphasized that openness, interoperability and flexibility in the deployment of AI workloads are critical for enterprises to successfully adopt the technology.
“More and more companies are looking for partners, companies and solution providers who can demonstrate that they will scale this technology in a trustworthy, responsible way – which requires orchestration capabilities, core security and a governance approach that allows them to encode their guidelines and principles into these workflows,” she said.