Artificial intelligence is becoming part of everyday life for most people. From mobile banking and fraud detection to healthcare and government services, AI is increasingly shaping how businesses operate and how people interact with digital services.
But according to Alan Turnley-Jones, Chief Executive Officer for Middle East and Africa at NTT DATA, many organisations are making a fundamental mistake in their AI journey by focusing on the technology itself rather than the business problems it is meant to solve.
Speaking to TechArena during an interview in Nairobi, Turnley-Jones said successful AI adoption starts with identifying clear business outcomes before selecting the technology.
“The biggest risk around AI adoption is viewing it as a technology solution,” he said. “If you’re only looking at it from a technology perspective, it’s quite limited in its applicability.”
Instead, he urged organisations to ask practical questions: How can AI improve customer experience? How can it optimise business processes? How can it increase revenue?
“Start with the business requirement. The technology comes afterwards.”
AI Success Depends on Trust
Turnley-Jones believes the conversation has shifted beyond what the technology can do to whether people trust it.
He compared the challenge to Kenya’s successful adoption of mobile money, noting that millions of Kenyans embraced digital payments because they trusted the system to protect their money and personal information.
“The same principle applies to AI,” he explained. “People need to trust how their data is being used and that it’s being used responsibly.”
He said that trust is becoming a competitive advantage for businesses deploying AI.
“As AI becomes more widely adopted, consumers want confidence that their data is safe and that organisations are using it in a responsible and ethical way.”
Trust Beyond Corporate Data
The challenge for most enterprises goes beyond protecting customer information. Corporate data often represents a company’s intellectual property and competitive advantage, making governance around AI even more critical.
While consumer AI tools are increasingly being used in everyday work, Turnley-Jones warned organisations to clearly define what information employees can safely use with public AI services and what must remain within secure enterprise environments.
“Many corporations have data that differentiates them from their competitors,” he said. “You need to make certain that if you’re using AI within your corporate environment, that information is protected.”
This is where concepts such as Trusted AI and Sovereign AI become increasingly important, ensuring data is handled in accordance with local laws, regulations and organisational governance while maintaining security and customer confidence.
Kenya Is Well Positioned to Lead
Turnley-Jones described Kenya as one of Africa’s strongest candidates to lead the continent’s next phase of AI adoption.
He pointed to the country’s culture of innovation, high levels of digital adoption and successful track record in technologies such as mobile money as evidence that Kenya has the right foundations.
“Kenya is a hub for innovation,” he said. “Kenyans embrace technology and new ways of working relatively quickly.”
He believes combining digitally savvy citizens with expanding technology infrastructure creates an opportunity for Kenya to pioneer new AI applications across industries including financial services, healthcare and the public sector.
Measuring AI by Business Outcomes
One of the biggest challenges organisations face is proving return on investment from AI projects.
Turnley-Jones argued that ROI should never be measured by the deployment of an AI tool itself but by the business outcomes it delivers.
“If you’re using AI to increase revenue or reduce losses, those become real, tangible business benefits that are measurable,” he said.
He noted that in some cases, organisations can begin seeing measurable returns within weeks once an AI solution has been implemented against a clearly defined business process.
Infrastructure, Skills and Cybersecurity Remain Critical
Despite growing enthusiasm around AI, Turnley-Jones said Africa still needs continued investment in digital infrastructure to fully realise the technology’s potential.
That includes connectivity, local data centres and cybersecurity capabilities that can support increasingly data-intensive AI workloads.
“As AI becomes more embedded in organisations, cybersecurity becomes a critical component of everything we do.”
He also highlighted the growing demand for AI skills across the continent.
While organisations are investing in training employees to become more productive using AI tools, there remains a shortage of highly specialised technical talent needed to build AI infrastructure and deploy enterprise-scale solutions.
“There are definitely skills gaps that exist in the market,” he said, noting that investments in training will be essential as AI adoption accelerates.
Africa Should Add Local Intelligence
Rather than choosing between global AI platforms and locally developed solutions, Turnley-Jones believes Africa should leverage both.
Global technology providers can supply the underlying AI capabilities, but African organisations should enrich those models with local knowledge, languages, regulations and market realities.
“There are nuances and challenges that we face in Africa that other parts of the world don’t,” he said. “Equally, there are opportunities that Africa has.”
That localisation will ultimately make AI more relevant and valuable for African businesses and citizens.
Advice for CEOs
With many executives feeling pressure to launch AI initiatives, Turnley-Jones offered a simple piece of advice: don’t invest in AI because everyone else is doing it.
Instead, leaders should first identify where AI can create measurable business value before selecting any technology.
“I would push back into my business and ask, What opportunities do we have? How are we going to increase revenue or improve efficiency?” he said.
“Starting with those business objectives and then determining the best technology to enable them is the way to go.”
For organisations still unsure where to begin, his recommendation was equally straightforward.
“Go and test it. Go and experience it yourself. The more you understand what AI can do, the easier it becomes to identify where it can create value for your business.”
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Also Read: NTT DATA’s 2026 Global AI Report shows how top performers turn AI vision into value
