Leaders & Laggards: IBM Survey Shows Gulf in AI Integration
AI is transforming the business landscape, yet organisations are not reaping its benefits equally.
While AI tools are more widely accessible than ever, with large language models and advanced machine learning systems at companies' disposal, the journey to effective implementation remains elusive for many.
Only a small proportion of companies have managed to break through as AI Leaders, according to recent research from IBM, which found that only 15% of companies have fully embedded AI into their operations. The vast majority are still experimenting, unable to extend their AI efforts beyond isolated pilot projects or early testing phases.
Investment and strategy
IBM’s ‘AI in Action’ report, based on a survey conducted by The Harris Poll, takes a closer look at 2,000 large firms across major economies including the US, UK, and Japan.
The study finds that merely having access to advanced technology does not guarantee effective integration, as many organisations continue to struggle with embedding AI into their core operations, data management, and decision-making processes.
Among firms identified as ‘AI Leaders,’ 71% report an aggressive AI investment stance, embracing technologies that simulate human intelligence to enhance decision-making. This compares sharply with only 19% of AI Learners.
“Of the organisations that were considered AI Leaders, two-thirds reported that AI has already driven 25% or greater improvement in their revenue growth rate,” says Shobhit Varshney, VP & Sr. Partner, Americas AI Leader at IBM Consulting.
The gap also extends to executive alignment. Seventy-two per cent of AI Leaders report alignment on AI maturity goals between C-suite executives and IT leadership, in contrast to 36% of Learners.
Additionally, AI Leaders distinguish themselves with a structured roadmap for AI integration. Eighty-five per cent of leading companies focus their investment in four main areas: customer experience systems, IT automation, virtual assistants, and cybersecurity.
Their roadmap spans four dimensions—strategy, technical tools, data governance, and specific applications—underpinned by a strong vision and dedicated infrastructure to support these priorities.
A major differentiator for AI Leaders is their ability to build customised AI solutions, rather than relying solely on pre-packaged options.
The report shows that 61% of AI Leaders utilise Application Programming Interfaces (APIs) to develop bespoke solutions, a figure that drops to 28% among Learners. Data management is also a critical factor: 61% of AI Leaders report confidence in their ability to access and manage data for AI initiatives, compared to just 11% of Learners.
IBM sees the emphasis on customisation as reflecting broader insights on AI strategy.
“A Learner will typically copy predefined scenarios using out-of-the-box technologies. But a Leader develops custom innovations,” says Dr. Stephan Bloehdorn, Executive Partner and Practice Leader for AI, Analytics and Automation at IBM Consulting DACH.
Moving forward with AI Integration
The research highlights that successful AI implementation requires a blend of strategic foresight, investment in technical infrastructure, and a strong data governance framework. As Varshney notes, “We dove into the data to uncover how these AI Leaders were implementing AI within their businesses that could help others learn from their success.”
Conducted across five major economies with substantial enterprise resources, the findings underscore that thriving with AI calls for strategic vision, resilient infrastructure, and a commitment to innovation. The clear success of AI Leaders in enhancing technical capabilities and leveraging data signals valuable lessons for firms still navigating the learning curve of AI adoption.
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