Artificial intelligence has reached a tipping point. Globally, the AI market is expected to surpass $1,8-trillion by 2030, with generative AI alone attracting nearly $34-billion in private investment this year.
Companies across sectors are racing to embed AI into operations, but proving return on investment (ROI) remains a key hurdle
While 84% of businesses investing in AI report some form of ROI, only a fraction have achieved sustained value at scale. For South African executives navigating budget constraints and talent shortages, the question is not “should we invest in AI?” but “how can we prove it works?”
According to Dumi Moyo, marketing director for Africa at SAP, there’s good news: AI doesn’t have to be a leap of faith.
“With the right strategy and the right tools, AI deployments deliver measurable ROI quickly across a range of business functions. One of the most effective ways to get there is by embedding AI directly into business applications, avoiding costly integrations and accelerating time-to-value.”
Embedded AI upends traditional implementations. Instead of requiring custom data pipelines, standalone platforms, and complex integrations, embedded AI delivers intelligence directly into the flow of work
“A native approach means faster deployment, less disruption, and clearer outcomes,” says Moyo. “For example, SAP has built more than 295 AI-powered scenarios into business applications that span supply chain, procurement, finance, customer experience and HR, empowering business users to complete navigational and transactional tasks up to 90% faster.”
Strategy for AI ROI
A recent study of 1600 businesses in eight countries conducted by SAP found that businesses investing in AI expect on average a 16% ROI in 2025, nearly doubling to 31% in 2027
Moyo says businesses typically have high expectations of the ROI they will receive from AI projects, with nearly half of global companies expecting AI initiatives to deliver positive ROI faster than other investments
“It is critical that organisations align their AI projects with the key pillars of cost savings, decision time, risk and revenue. By prioritising embedded AI, companies can secure significant ROI while unlocking broader innovation benefits across the organisation.”
He shares insights into how AI initiatives built on four key pillars can show provable, measurable return-on-investment for organisations:
Pillar 1: Reduce manual effort and waste to drive cost savings
Cost reduction is often the first benefit that organisations receive from AI investments. “AI allows teams to redirect hours toward higher-value work by automating repetitive and rule-based tasks,” says Moyo. “SAP data shows that companies achieve up to 20% operational cost reduction in key functions like accounts payable and HR through effective AI deployments.”
In procurement functions, organisations are cutting administrative workload and improving sourcing outcomes by automating statements of work (SOWs) and supplier research, while in finance, AI accelerates reconciliations, optimises cash collections, and automates journal entries, thereby reducing close cycles and improving liquidity
“A good approach here is to quantify the time saved across manual processes and to calculate the cost of labour hours that have been freed up and reinvested into more strategic work thanks to AI,” says Moyo
Pillar 2: Improve decision time for faster insight and action
AI tends to thrive when speed and accuracy matter most. By analysing large datasets, surfacing trends, and recommending next steps, AI shortens the gap between information and action
“Data shows that embedded AI improves forecasting and demand planning in the supply chain, resulting in less downtime and a 25% productivity bump for planners,” says Moyo
Organisations are also using generative AI to accelerate their hiring processes and producing job descriptions and candidate rankings in real-time. Finance also benefits from AI-generated insights that help CFOs and analysts make faster, more confident decisions using cleaner data
“Organisations should measure reductions in cycle times, from planning to resolution, and link them to improved responsiveness or reduced delays,” says Moyo. “This provides a clear path to ROI and its impact on core business performance.”
Pillar 3: Reduce risk through better controls and compliance
In a volatile business climate, organisations typically seek greater risk mitigation across their operations. According to Moyo, AI plays a growing role here
“AI embedded into core business processes can flag anomalies, detect fraud patterns, and monitor compliance thresholds in real time. AI agents are increasingly being used in risk reduction, for example by scanning procurement data for irregularities and highlighting non-compliant purchases.”
AI agents such as SAP’s Joule can also bolster procurement processes by suggesting suppliers with stronger reputations, and support finance teams by reducing bad debt write-offs through improved collection strategies. In HR, AI-driven insights reduce legal risk by providing bias-aware hiring recommendations and fairer performance reviews
“To quantify the benefits that AI brings to risk reduction, companies should track aspects such as risk events avoided, compliance costs reduced, or error rates minimised,” says Moyo
Pillar 4: Grow revenue through personalisation and conversion
According to Moyo, organisations should look beyond back-office efficiency to maximise AI value. “A smart AI strategy will consider front-end growth by prioritising customer experiences. For example, AI fuels personalisation by recommending products, predicting churn, and guiding service agents with next-best actions to enhance customer satisfaction and drive retention.”
Organisations that embed AI into their core business processes can connect sales, service and marketing data to build richer customer profiles, increase upsell success and reduce attrition. Organisations also accelerate their campaign rollouts through AI-powered content generation, while smart selling tools shorten deal cycles and increase the average basket size
“This results in higher revenue per customer interaction, as well as more predictable sales pipelines,” says Moyo. “Here, ROI is readily quantified through tracking lead conversion rates, customer churn, and average order value.”
This article first appeared on ITOnline/
