South African CIOs transform AI hype into measurable business results

South African CIOs are adopting a more pragmatic approach to AI investments, focusing on targeted high-impact deployments rather than broad implementation. Financial services group Sanlam and manufacturers like Lactalis Southern Africa exemplify this strategic shift, allocating AI budgets toward solutions that deliver measurable business outcomes. This evolution marks a departure from earlier experimentation phases as organizations now demand tangible returns on their AI investments while leveraging the technology to enhance customer experiences and operational efficiency.

The big picture: Enterprise AI investment is accelerating, with Foundry‘s AI Priorities Study 2025 showing nearly half of organizations now allocating dedicated AI budgets, up from 36% in 2023, with almost a quarter of IT spend going toward AI initiatives.

• South African tech leaders are taking a measured approach, ensuring AI investments deliver tangible results rather than implementing technology for technology’s sake.
• IT departments are increasingly partnering with business units like customer service and marketing to align AI adoption with broader organizational goals.

What they’re saying: Sanlam’s group CIO Theo Mabaso emphasizes targeting AI investments where they’ll have maximum impact rather than simply increasing budgets.

• “After a period of experimentation, launching multiple AI outcomes and learning by doing, we’ve figured out where the objective AI value is concentrated, and have thus narrowed our focus to delivering fewer but higher impact AI outcomes that deliver ROI for the group,” Mabaso explains.
• Werner Leithgöb, IT director at Lactalis Southern Africa, compares current AI hype to Amazon Alexa: “When the Amazon Alexa first came out, everybody thought it was so awesome… But I guarantee that 99% of consumers who have one use it purely to stream music.”

Strategic focus: Organizations are moving beyond experimentation to deliberately target specific business challenges with AI solutions.

• Jenny Mohanlall, senior director for IT at DHL South Africa, emphasizes that “it’s about leveraging it to solve real problems, drive efficiency, and create meaningful impact.”
• Predictive capabilities are transforming customer service, with AI anticipating customer needs and proactively addressing issues before they escalate.

Real-world implementation: Sanlam’s AI-powered financial coaching product demonstrates how targeted AI deployments can deliver measurable business outcomes.

• The company’s “Coach” product utilizes 40 LLMs to provide personalized financial guidance, facilitating 45,000 unique conversations in its first few months and driving loan application conversion rates three times higher than web or WhatsApp channels.
• In logistics, AI is helping companies analyze historical data, weather patterns, and traffic conditions to predict demand and optimize delivery routes in real-time.

Data foundations: IT leaders recognize that successful AI implementation requires solid data infrastructure before deployment.

• “AI thrives on data, so if your data is a mess, your AI is also going to be a mess,” notes Leithgöb, who is prioritizing data organization while slowly introducing tools like Microsoft Copilot to familiarize users.
• Organizations report productivity gains through tools like GitHub CoPilot and LLMs that review contracts, but they’re cautious about large-scale deployments without clear metrics.

Why this matters: As AI moves from experimental to operational, organizations that strategically deploy AI to address specific business challenges while building proper data foundations will gain competitive advantages in cost reduction, operational efficiency, and customer experience.