AI through the looking glass

Security concerns paramount

Across the breadth and scope of AI insights that have covered the pages of FOCUS, one of the major overarching concerns continues to be the security of sensitive and private data. For fleet managers, this can include customer addresses and goods being transported.

As Elkington noted in March last year, any information put into ChatGPT (for example, when producing a report) is an immediate breach of a fleet operator’s data policy. The solution he put forward was for organisations to adopt closed-loop AI systems that do not share information externally. He equated this to “a walled garden, which helps you maintain control of your data.”

Segooa highlighted Microsoft’s pledge to train one million South Africans in AI and cybersecurity by 2026 as a step in the right direction. In September, iAfrica.com reported that this target had been achieved. In addition, it noted, other key achievements included 50,000 industry-recognised AI certifications issued to young professionals; 300,000 youth trained through a partnership with the Youth Employment Service (YES); and 200 SMMEs and 2,000 individuals equipped with advanced AI and digital capabilities.

2026: AI in transportation at an inflection point

Looking ahead as we move into the second half of the decade, US software, hardware and services technology company Trimble has released its annual Transportation Pulse Report 2026.

The report emphasises that the transportation industry is at an AI inflection point as adoption accelerates.

Surveying more than 230 supply chain and logistics executives across Europe and North America, the report finds that both shippers and carriers are already using AI to improve transport planning, pricing and execution. Their priorities differ, however. While 86% of shippers expect AI to have a major impact on transport planning and optimisation over the next three to five years, carriers place greater emphasis on pricing and lane optimisation, with 59% identifying this as AI’s primary source of value.

The report further highlights other opportunities, including the rise of “Agentic AI” – autonomous software agents that monitor data, make decisions and execute tasks within defined boundaries. Despite the potential of automation, however, Trimble stresses that many shippers and carriers still see AI’s primary role as augmenting human decision-making rather than replacing it. “Still, this marks a turning point,” it says. “Logistics teams are in the early stages of trusting systems to act on their behalf and not just provide insights.”

(A)I on Industry

AI is unsurprisingly at the forefront of industry discussions and projections, and our Eye on Industry section kicks off with Trimble’s Chris Keating unpacking transport industry predictions for 2026 on page 86.

Keating says that the industry’s relationship with AI is maturing and that we are moving from experimentation to real adoption: “In 2026, AI will move into mainstream applications such as predictive maintenance, network optimisation and dynamic pricing. Conversations about full autonomy are already happening at the operational level,” he emphasises, adding that “AI as colleague” is replacing “AI as tool”. He does, however, echo the ongoing concerns about security concerns, warning: “A major global breach involving data exposure from unsafe AI use appears to be a question not of if, but of when.”

Keating reminds us that data quality is the true enabler of automation – a sentiment echoed by RS South Africa’s De Wet Joubert on page 102, where he describes how AI is driving efficiency, predictive insight and smarter decision-making in the maintenance, repair and operations supply chain. “When data is complete, accurate and contextualised, AI can forecast component failures, optimise inventory and improve overall supply chain reliability,” Joubert says, adding, “Organisations that embrace AI strategically, align it with core processes and invest in data quality will not only improve efficiency, but also unlock entirely new ways of operating.”

On page 94, the 2026 Air Freight Outlook Report from market analytics platform Xeneta highlights the growing influence of AI in the sector, with 43% of global merchandise trade growth in the first half of last year coming from AI-related goods like semiconductors, processors and finished computers – despite these accounting for only about 15% of total trade. “Much of this cargo is high-value, time-sensitive hardware – key air freight selling points – putting AI investment at the centre of demand in 2026,” the report notes.

The fact that major US tech firms are predicted to increase their annual capital spending to over US$500 billion this year is also telling, with the report stating that much of this expenditure will be on AI data centres and their connection networks, adding that accounting for investment peaks in previous technology waves, there appears to still be substantial room for growth in AI investments.

On page 98, we investigate the potential for digital twins (DTs) to transform how we approach transport infrastructure planning, implementation and management. Again, AI and machine learning (ML) models will undoubtedly play a significant role in the evolution of this technology. Future systems, say researchers, could leverage advanced analytics and AI to provide deeper insights and optimise transportation networks throughout their lifecycle, amongst a plethora of other potential applications.