Businesses adopting artificial intelligence (AI) without first identifying the problems they want to solve risk wasting resources, the Chief Executive Officer of NTT DATA for the Middle East and Africa, Alan Turnley-Jones, has warned.
Turnley-Jones said many organisations were making the mistake of treating AI as a technology solution rather than a tool for addressing specific business challenges.
Speaking in an interview with TechArena in Nairobi, he said companies should first identify how AI could improve customer experience, streamline operations, increase revenue or reduce losses before deciding which technology to deploy.
“The biggest risk around AI adoption is viewing it as a technology solution. If you’re only looking at it from a technology perspective, it’s quite limited in its applicability,” he said.
“Start with the business requirement. The technology comes afterwards.”
He also identified trust as a major factor that would determine how widely businesses and consumers embrace AI, particularly as the technology increasingly handles personal information and sensitive corporate data.
Drawing a comparison with Kenya’s mobile money industry, Turnley-Jones said the widespread adoption of digital payments was built partly on public confidence in the security of the system.
He argued that the same principle applied to AI, noting that consumers needed assurance that their personal information was being handled securely and responsibly.
“The same principle applies to AI. People need to trust how their data is being used and that it’s being used responsibly,” he said.
The NTT DATA executive also warned organisations against exposing sensitive corporate information through public AI platforms, stressing that proprietary data could represent a company’s intellectual property and competitive advantage.
He said businesses needed clear policies defining the information employees could share with publicly available AI tools and the data that must remain within protected enterprise environments.
See also: Google Faces Criminal Investigation Over Forest Clearing for AI Data Centre
The issue, he added, has increased the importance of Trusted AI and Sovereign AI, which focus on responsible data handling, security, governance and compliance with local regulations.
Turnley-Jones described Kenya as well-positioned to lead Africa’s next phase of AI adoption, citing its technology culture, digital infrastructure and experience with mobile money services.
He said the country’s willingness to embrace new technologies could support AI applications across financial services, healthcare and government operations.
However, he stressed that businesses must measure the success of AI investments through tangible outcomes rather than the number of tools or systems deployed.
According to him, organisations should assess whether AI projects are generating additional revenue, reducing operational costs, preventing losses or improving efficiency.
“If you’re using AI to increase revenue or reduce losses, those become real, tangible business benefits that are measurable,” he said.
He added that some businesses could begin recording measurable returns within weeks of implementing AI solutions targeted at clearly defined processes.
Despite the opportunities, Turnley-Jones said Africa would need sustained investment in digital infrastructure, including reliable connectivity, local data centres and cybersecurity capabilities, to support wider AI adoption.
He also highlighted the shortage of specialised technical skills needed to develop AI infrastructure and deploy enterprise-level solutions, calling for increased investment in training.
On the development of AI solutions for African markets, he argued that the continent should combine global AI platforms with local knowledge rather than rely exclusively on either international or homegrown technologies.
He said incorporating African languages, regulations, cultural contexts and market conditions into AI systems would make the technology more relevant to local businesses and consumers.
Turnley-Jones advised business leaders not to invest in AI simply because competitors were doing so, urging them to identify opportunities where the technology could deliver measurable value.
He also encouraged executives to experiment with AI tools themselves to better understand their capabilities and identify practical applications within their organisations.
About the Author
Cecilia Attah is a tech analyst with a degree from Benue State University. She covers tech news and startups at TechRegard with a focus on how technology is transforming Africa and shaping the global landscape.
