HARARE – Zimbabwean companies are falling behind the global artificial intelligence (AI) productivity revolution, with weak data infrastructure, fragmented digital systems, and limited board-level commitment preventing businesses from integrating AI into core operations, according to Shalom Maurukira, an analyst at Equity Axis, citing the latest national ICT survey.
While AI adoption among individuals is steadily increasing, corporate deployment remains largely experimental, exposing businesses to rising operating costs and diminishing competitiveness as regional and international rivals accelerate digital transformation.
The findings, drawn from the 2025 ICT Access by Households and Use by Individuals Survey by the Zimbabwe National Statistics Agency (ZimStat) and the Postal and Telecommunications Regulatory Authority of Zimbabwe (POTRAZ), indicate that although 31% of internet users have used AI tools, commercial application remains relatively shallow. Work-related use accounts for only 19.5% of reported AI activity, while healthcare represents 18.3%, agriculture 6.8%, security 6.2%, transport 5.2% and finance just 1.7%.
According to Equity Axis, these figures suggest that although businesses have gained access to AI technologies, they have yet to embed them into the operational processes that generate measurable productivity gains.
“Without measurable investment cases and board-level ownership, businesses risk rising costs and falling behind global competitors,” the publication noted.
AI yet to transform business operations
Globally, artificial intelligence has moved beyond simple chatbots and content generation to become a core driver of operational efficiency. Companies are increasingly using AI to optimise manufacturing, predict equipment failures, automate customer service, strengthen fraud detection, improve inventory management and enhance strategic decision-making.
Zimbabwe, however, remains at an earlier stage of digital transformation.
Many businesses continue investing in websites, mobile applications, enterprise resource planning systems and cloud computing, but have yet to integrate AI into finance, procurement, logistics, maintenance and customer analytics.
Equity Axis argues that AI only delivers meaningful commercial value when it is linked to specific business challenges.
Manufacturers, for example, can use predictive analytics to reduce costly equipment failures, while retailers can improve inventory forecasting and pricing. Banks can strengthen fraud detection and credit assessment, mining companies can optimise fleet utilisation, and agricultural firms can deploy AI-powered weather forecasting and crop monitoring to improve productivity.
Leadership rather than technology remains the biggest obstacle
The report argues that one of the greatest barriers to AI adoption is not technology itself but corporate leadership.
Many boards continue to view artificial intelligence as solely an information technology initiative rather than a strategic business investment.
As a result, AI implementation often remains confined to IT departments instead of becoming embedded across finance, operations, procurement, risk management and executive decision-making.
Equity Axis says successful AI deployment requires board oversight, capital allocation, governance frameworks and clear accountability, with technology teams providing infrastructure while business leaders define commercial objectives and measure financial returns.
Poor data infrastructure undermines AI potential
Artificial intelligence is only as effective as the data it analyses.
Many Zimbabwean companies still rely on paper records, spreadsheets, legacy accounting software and disconnected departmental databases. Such fragmented information limits management’s ability to build accurate operational insights while increasing the risk of unreliable AI outputs.
Before investing heavily in AI, many firms will first need to modernise their enterprise systems, improve cybersecurity, clean historical data and integrate business information across departments.
Without high-quality, structured data, AI cannot generate reliable commercial intelligence.
Digital skills gap widens productivity challenge
The survey also highlights a significant shortage of digital skills across the country.
More than half of Zimbabwe’s population lacks basic digital competencies, while spreadsheet proficiency stands at just 5.4%, digital document editing at 5% and programming skills below 1%.
These deficiencies limit the ability of executives to evaluate AI investments, managers to redesign business processes and employees to integrate AI into day-to-day operations.
The result is that many organisations remain dependent on small technical teams that lack the capacity to scale AI across the enterprise.
Strong investment cases remain essential
Equity Axis notes that Zimbabwe’s challenging operating environment demands disciplined capital allocation.
With liquidity constraints, high borrowing costs and volatile demand, boards require clear evidence that AI investments will improve profitability before committing resources.
Rather than focusing on broad promises of innovation, companies should build business cases around measurable operational outcomes such as reduced maintenance costs, lower fraud losses, improved energy efficiency, higher equipment utilisation, faster customer service and increased inventory turnover.
International companies already demonstrating results
Global corporations are increasingly treating artificial intelligence as a strategic investment rather than an experimental technology.
Engineering giant Siemens has implemented AI-powered predictive maintenance systems that monitor industrial equipment, detect faults before failures occur and minimise costly production interruptions.
In agriculture, John Deere’s AI-enabled “See and Spray” technology has enabled farmers to significantly reduce herbicide use through targeted chemical application, lowering costs while improving environmental sustainability.
Meanwhile, JPMorgan Chase has invested approximately US$19.8 billion in technology, data and AI during 2026, with more than 500 AI applications now deployed across its operations. The bank has reported measurable gains through lower operating costs, improved risk management and stronger revenue generation.
Although Zimbabwean companies operate on a much smaller scale, Equity Axis argues that the commercial principles remain identical.
Key sectors stand to benefit
The analysis identifies several industries where AI could deliver immediate commercial value.
Manufacturers could deploy predictive maintenance to reduce equipment downtime and improve production efficiency.
Banks and insurers could enhance fraud detection, automate compliance processes and strengthen credit risk assessment using existing customer data.
Retailers could improve demand forecasting, pricing strategies and inventory management, while mining companies could optimise fleet performance, processing efficiency and workplace safety.
Agricultural businesses could use AI-powered weather forecasting, precision farming and crop diagnostics to improve yields and reduce input costs.
Healthcare providers could enhance patient scheduling, inventory management and diagnostic support, improving both efficiency and service delivery.
Productivity gap likely to widen
Equity Axis warns that the competitive divide between companies embracing AI and those delaying adoption is likely to expand rapidly.
Businesses that integrate AI into operations are expected to benefit from lower operating costs, better customer service, faster decision-making and stronger profitability. Those that postpone implementation risk higher costs and declining competitiveness as international rivals continue to improve productivity.
“Companies that delay retain fragmented data and manual systems, making the future transition more expensive,” the publication observed.
With more than half of AI users in Zimbabwe already relying on Meta AI and nearly one-third using ChatGPT, Equity Axis argues that the behavioural barrier has largely been overcome. The next challenge for Corporate Zimbabwe is to transform individual familiarity with AI into enterprise-wide capability that delivers measurable commercial returns.
