MIMOS AIDT Workshop Charts Research-to-Revenue Pathway for AI Innovation

KUALA LUMPUR, MALAYSIA, 3 November 2026 — The journey from laboratory research to investable AI solutions took centre stage at a 3 November workshop for MIMOS stakeholders, bringing technology readiness, industry demand and commercialisation into one conversation. The programme placed practical commercialisation questions alongside technology readiness and institutional strategy. The session examined how promising research can be assessed against real market problems, customer demand, ownership rights and routes to adoption. Participants were introduced to structured AI opportunity assessment and the distinction between a technically interesting prototype and a venture-ready proposition. A phased approach was emphasised: identify priority opportunities, establish clear problem statements, review IP and data requirements, validate use cases with potential customers and design pilots with measurable outcomes. Subsequent investment or venture decisions would depend on evidence from these stages.

Research-to-revenue pathway

The 3 November programme provides an opportunity to distinguish promising laboratory work from technologies ready for adoption. Research excellence alone does not demonstrate customer willingness to pay, regulatory suitability, data availability or operational integration. The proposed evaluation sequence therefore begins with an inventory of use cases and underlying intellectual property, followed by market discovery, practical feasibility checks and clear ownership of subsequent decisions.

From workshop to measurable pilots

Following the workshop, a disciplined Stage 3 sandbox approach could concentrate resources on one or two use cases with an explicit problem statement, a baseline measurement and an agreed success threshold. Such pilots would test not only whether the AI works technically but whether it changes decisions, saves staff time or improves service quality. Any pilot selection, resources and reporting arrangements would require MIMOS approval.

Evidence before investment

The programme’s “From Research to Revenue” framing matters because research IP must cross several different thresholds before it can support an investable company. A research team may demonstrate technical performance, yet a commercial sponsor must still establish a buyer, an addressable operational problem, freedom to use the underlying IP and a viable delivery model. The workshop materials connect research, decisioning, industry and investment; they do not treat a patent or prototype as evidence of customer demand. For MIMOS, the next useful management output would be a prioritised opportunity register recording asset ownership, technology maturity, market relevance and pilot sponsorship.

What success would look like

A credible follow-through would define one or two priority use cases, a measurable baseline and a clear decision on who can authorise a sandbox. Their value would lie in showing whether a solution changes a process, improves decision quality or creates a commercial proposition. Lessons should be captured even when a test does not justify deployment.

“Research creates economic value when institutions can translate it into solutions that users will adopt. Our objective is to help teams move from ideas to clearly defined use cases, accountable pilots and credible commercialisation pathways.”

Prof Dr M Nazri Muhd, Group Executive Chairman, Centre for AI Innovation (CEAI), Global, Chief AI Advisor, AI & Design Thinking (AIDT) Lab @ KSI Strategic Institute for Asia Pacific (KSI)

Next steps

The organisation will continue to assess relevant opportunities in line with stakeholder priorities and applicable approvals. Further details about any confirmed agreements, programme dates, products or implementation milestones will be communicated through official channels. This announcement does not constitute an offer of securities, a guarantee of financial performance or confirmation of a transaction not yet executed.

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CEAI Global works across AI strategy, innovation, capability development and commercialisation initiatives.