- Speaking at Fortune’s Global Forum in Riyadh, IBM’s Anna Paula Assis said businesses need to transform their operating models to realize the full potential of AI. He said businesses need a systematic, organization-wide approach that integrates data, technology and trust to realize the benefits of technology. Although AI adoption is progressing rapidly, most organizations still struggle to achieve measurable benefits due to knowledge gaps and limited integration.
Ana Paula Assis, IBM’s senior vice president and chair of EMEA and growth markets, says AI has the potential to improve productivity within organizations, but only if business models are transformed.
Assis told the audience: luckExploring the full potential of AI means taking a “systemic approach” to the technology, she said at the Global Forum in Riyadh, “an approach that encompasses broad implementation across the organization, an approach that integrates silos, an approach that moves from simple experimentation and isolated pilots to enterprise-wide adoption.”
According to an IBM study cited by Assis, two-thirds of EMEA leaders are already seeing a positive impact from AI in their productivity efforts. Leaders in Saudi Arabia claimed to have seen the greatest positive impact, with 84% of leaders in the region citing the positive impact of AI.
But while the majority of companies are rapidly investing in AI, some are struggling to get the technology past the pilot stage. Over the past year, the number of companies using AI to run their entire workflow has nearly doubled, and from 2023 onwards, the amount of technology used across the workplace will also double. However, a recent MIT Media Lab study found that 95% of organizations using AI are not seeing a clear return on their investments. This is partly due to the so-called “learning gap,” or people not understanding how to properly use AI tools, rather than an issue with the core technology itself.
Integrating new technology into a complex corporate structure can take time. According to Assis, adopting this technology in a “systematic” way means considering data readiness, openness, and trustworthiness.
“AI is only as good as the data you use to train and scale it,” she said. “We estimate or estimate that only 1% of the data currently residing in enterprise applications in our data centers is processed by artificial intelligence. So imagine the opportunities created by expanding this reach.”
Assis also pointed out that companies often operate within complex technology environments that require integration and coordination between different systems and teams. She emphasized that openness, interoperability, and flexibility in where AI workloads are deployed are essential to successful technology adoption by enterprises.
“Enterprises are increasingly looking for partners, companies, and solution providers who can demonstrate that they intend to scale this technology in a trusted and responsible manner. That requires orchestration capabilities, core security, and a governance approach that allows guidelines and principles to be encoded into workflows,” she said.
