Economic Growth At Risk As SME AI Adoption Lags Without Targeted Development Support

Rowen Pillai | image supplied

He argues that in a low-growth environment, ESD should be treated as an economic development tool rather than a compliance requirement, with a stronger focus on closing the digital gap between large firms and small suppliers.

AI adoption among SMEs remains low

Small and medium-sized enterprises (SMEs) play a central role in job creation and economic activity, yet AI uptake in the sector remains limited. In manufacturing in particular, low adoption is restricting productivity gains and innovation.

Many SMEs face barriers including limited access to modern technology, low awareness of how AI can be used in their operations, and shortages of relevant digital skills. Smaller firms often lack the capacity to assess, procure and implement AI tools on their own, increasing the risk that parts of the economy are excluded from technology-driven growth.

Rethinking ESD beyond compliance

Pillai says ESD programmes have often been treated as box-ticking exercises, with short-term interventions that do not integrate SMEs into corporate value chains in a meaningful way. Generic training without technical or financial backing has had limited impact on long-term business sustainability.

He believes ESD funds can instead be directed more deliberately towards AI-related support for SMEs, focusing on awareness, tools, mentorship and infrastructure.

Four focus areas for ESD-funded AI support

Pillai highlights four areas where corporate ESD spend could be more targeted:

Practical AI education

Investment in low-cost, applied AI training for SME owners and staff could improve organisational readiness, which is a key factor in successful adoption. Programmes should focus on real business use cases rather than theory, delivered through partnerships with vocational institutions and online platforms.

Collaborative innovation hubs

Closer collaboration between corporates, academic institutions, technology hubs and SMEs could help develop affordable, locally relevant AI tools. Stronger public-private cooperation would be needed to ensure solutions are accessible beyond major urban centres.

Mentorship and pilot projects

Corporates with in-house AI expertise could play a more active role in mentoring SMEs, helping them identify suitable use cases and manage implementation. ESD funding could also be used for pilot projects and proof-of-concept initiatives to demonstrate measurable business value.

Digital infrastructure

AI adoption depends on reliable connectivity and access to cloud resources. Targeted investment in digital infrastructure, particularly in underserved areas, would be necessary to ensure SMEs can make practical use of AI technologies.

Business case for corporates

Pillai positions this approach as commercially relevant for large companies, not philanthropic. AI-enabled SMEs could improve operational efficiency, decision-making and service quality, contributing to more resilient and competitive supply chains.

He adds that AI adoption must be managed responsibly, with attention to data privacy and ethical considerations, but says inaction risks widening the gap between large firms and smaller suppliers.