Business models need to shift to unlock the true potential of AI, says IBM’s senior vice president

Assis told the audience at luck‘s Global Forum Exploring the full potential of AI means adopting a “systems approach” to the technology: “an approach that embraces end-to-end implementation across the organization, an approach that integrates silos, an approach that moves from experimentation and isolated pilots to company-wide adoption,” she said in Riyadh.

According to IBM research cited by Asis, two-thirds of EMEA leaders are already seeing a positive impact from AI on productivity initiatives. Saudi leaders claimed to have witnessed the greatest positive impact, with 84% of leaders in the region citing the positive impact of artificial intelligence.

However, while the majority of companies are rapidly investing in AI, some are struggling to get the technology past the pilot stage. In the past year, the number of companies running entire workflows with it has skyrocketed Artificial intelligence has almost doubledwhile the workplace in general The use of technology has also doubled Since 2023. However, a recent study by the MIT Media Lab found that 95% of organizations using AI were not seeing a clear return on those investments. This is partly due to the so-called “learning gap” – people and organizations not understanding how to use AI tools properly, rather than a problem with the underlying technology itself.

Integrating new technology into complex corporate structures can take time. According to Assis, adopting technology in a “systemic” way means considering data readiness, openness, and trust.

“AI is only as good as the data you use to train and enhance it,” she said. “We expect, or estimate, that only 1% of the data today in enterprise applications in their data centers is touched by AI. So imagine the opportunities that will be created as we scale this.”

Assis also noted that companies often operate within complex technological environments that require integration and coordination across different systems and teams. She stressed that openness, interoperability and flexibility in the places where AI workloads are deployed are essential for successful enterprise adoption of this technology.

“Companies are increasingly looking for partners, companies and solution providers who can demonstrate that they will scale this technology in a reliable and responsible way – and this requires orchestration capabilities, security at their core, and governance methods that allow them to encode their guidelines and principles into this workflow,” she said.