REPORT AI Infrastructure Readiness Assessment Report Apr 14, 2026 STT GDC SHARE Link copied! In BriefMind the Gap: Bridging the AI Infrastructure Readiness DivideWhy Most Organisations Are Stuck Between Ambition and Execution—And What It Means for Asia’s Digital FutureWhilst Asia is winning at AI ambition, the data reveals a maturity gap: organisations have successfully deployed initial AI solutions, but most are now navigating the infrastructure requirements needed to scale from pilot to production.53% prioritise AI for revenue growth71% remain trapped in "Building" stage—unable to move pilots to production54% cite infrastructure limitations as their #1 barrier to AI success Read the report As organisations in Asia move beyond the initial rush to deploy AI, many are encountering significant roadblocks to their ambitions of transforming operations and generating new revenue streams. Getting AI right, as many are discovering, requires getting crucial foundations in place. The core challenge for the region’s organisations is no longer about vision but about execution and infrastructure readiness.To strengthen AI adoption, Asian organisations must progress up the AI infrastructure maturity scale across critical parameters for their digital infrastructure. Success depends on deepening efforts in strategic alignment and ambition, organisational readiness, data governance and compliance, and most critically, AI infrastructure as a fundamental building block.This report offers more than a market overview. It provides a practical guide for organisations to understand their current AI infrastructure maturity, benchmark themselves against industry leaders, and create a roadmap to advance up the AI infrastructure maturity ladder. By doing so, they can realise their ambition to become modern, AI-powered organisations prepared for the future.Future AI Infrastructure Planning - StagesFuture-ready 17%12%Explorers71%Builders16%Integrators1%LeadersEXPLORERAI initiatives are ad-hoc and exploratory; infrastructure lacks basic support, and efforts are hindered by talent deficits and fragmented governance. Much of the focus is on establishing a basic AI vision and understanding infrastructure gaps.BUILDERA broad AI vision is documented, and initial operational solutions are deploying. Infrastructure is sufficient for current needs but requires better integration and formalisation of data governance. The focus is on scaling talent and basic compute.INTEGRATORAI is a core driver; infrastructure is robust, scalable, and optimised for high-demand workloads, enabling seamless deployment. The focus is on optimising performance, scalability, and achieving regulatory confidence.LEADERAI is fully embedded, transforming business models, and driving market leadership. The infrastructure is hyper-optimised, highly resilient, and proactively managed for sustainability. Pioneering innovation and driving market leadership are the focus here.The 71% have AI vision but lack the infrastructure foundation to execute it. They're stuck between proof-of-concept and production value.Asia's Approach to AI Adoption Reveals An Infrastructure GapWhile Asia is winning at AI ambition, the data reveals a maturity gap: organisations have successfully deployed initial AI solutions, but most are now navigating the infrastructure requirements needed to scale from pilot to production.Asia is clear on the benefits of AI88% Asian organisations that have embarked on their AI journey53% Prioritise AI for revenue growth But lack the infrastructure needed to scale beyond the AI pilots17% Have infrastructure capable of supporting AI at scale71% Remain trapped in the “Building” stage — unable to scale pilots to production54% Cite infrastructure limitations as #1 barrier to achieving their AI ambitions The Three Questions Every Organisation Must AnswerWhere should AI run?Distributed architecture across mature and emerging markets—mature for governance, emerging for capacity and growth.How Should AI be deployed?Hybrid-by-design approach using specialised infrastructure partners to deliver AI-ready capacity without the capital burden or typical 12-18 month build cycles.Who will run your AI infrastructure?Strategic partnerships that combine an organisation’s domain expertise with a provider’s infrastructure operational excellence.Read the report Is your organisation ready for scale?Complete our AI Infrastructure Readiness Assessment to understand your current stage and receive a tailored guide on your AI Infrastructure journey.take the Assessment