For many organisations, the AI debate has moved on from whether to adopt the technology to a harder question: why do the results feel uneven? New tools are in place, pilots are running, and budgets are rising, yet clear AI returns remain elusive. According to Cloudflare’s 2026 App Innovation Report, the difference often has less to do with AI itself and more to do with the state of the applications underneath it.
The report, based on a survey of more than 2,300 senior leaders in APAC, EMEA, and the Americas, points to application modernisation as the clearest divider between organisations seeing real AI value and those still struggling. Companies that are ahead of schedule in modernising their applications are nearly three times more likely to report a clear payoff from their AI investments. In APAC, the link is even more explicit: 92% of leaders say updating their software was the single most important factor in improving their AI abilities.
Modernisation, not experimentation, drives AI returns
The finding re-frames AI success as a foundation problem not a tooling problem. AI systems depend on fast access to data, flexible architectures, and reliable integration points. Legacy applications, fragmented infrastructure, and brittle workflows make it harder for AI projects to move beyond isolated use cases. Modernised applications, by contrast, give organisations room to experiment, scale, and adapt without constant rework.
The report describes this relationship as a reinforcing cycle. Organisations modernise applications to support AI, then use AI results to justify deeper modernisation. Leaders in this group report far higher confidence that their infrastructure can support AI development, and that confidence translates into action. In APAC, 90% of leading organisations have already integrated AI into existing applications, compared with much lower levels among those behind schedule. Around 80% plan to increase that integration further over the next year.
The shift marks a change in mindset, as earlier waves of AI adoption focused on testing and pilots. Now, the emphasis is on integration. AI is not treated as a standalone project but as part of everyday systems, from internal workflows to customer-facing applications. The report shows that leading organisations are using AI to improve internal processes, build content-driven applications, and support revenue-generating work, while lagging organisations remain more cautious and fragmented in their approach.
The cost of delay shows up in security and confidence
The cost of falling behind is becoming clearer as well. Organisations that lag on modernisation tend to modernise reactively, often after a security incident or operational failure. In APAC, these organisations report lower confidence in both their infrastructure and their teams’ ability to support AI. That lack of confidence slows decision-making and limits how far AI projects can go. Instead of expanding use cases, teams spend time managing risk, fixing gaps, and dealing with technical debt.
Security plays a central role in this dynamic. The report shows that organisations with strong alignment between security and application teams are far more likely to scale AI successfully. Where that alignment is weak, security issues consume time and attention, pushing modernisation and AI work further down the priority list. Many lagging organisations report difficulty tracking risks in applications and APIs, which makes it harder to move quickly without increasing exposure.
For leaders, security is treated as part of application design not an add-on. That approach reduces the amount of reactive work needed after incidents and frees teams to focus on building and improving systems. Over time, this also lowers the operational drag that can stall AI efforts. The report suggests that reliability has become a practical limit on speed: organisations that cannot maintain stable, secure systems struggle to move AI projects into production.
Fewer tools, clearer foundations, faster AI integration
Another pressure point highlighted in the APAC data is tool sprawl. Nearly all organisations report challenges in managing large and complex technology stacks, but leaders are responding more aggressively. About 86% of APAC leaders say they are actively cutting redundant tools and addressing shadow IT. The goal is not just cost control, but clarity. Fewer platforms and integrations make it easier to modernise applications, apply consistent security controls, and integrate AI without friction.
Developer time is also a factor. In organisations with a modernised foundation, developers spend more time maintaining and improving systems that already work. In lagging organisations, developers are more likely to rebuild from scratch or spend time on configuration and remediation. That difference affects how quickly new AI abilities can be introduced and refined. When teams are tied up fixing problems, AI becomes harder to prioritise.
Taken together, the findings suggest that AI success is less about racing to deploy new models and more about removing the obstacles that slow everything else down. Application modernisation creates the conditions for AI to deliver value, while fragmented systems and reactive practices limit what AI can achieve. Without that foundation, organisations find it harder to turn AI investment into measurable AI returns.
For APAC organisations, the message is that AI investment without modernisation tends to produce shallow results. Modernisation without integration plans risks becoming an ongoing rebuild. The organisations seeing the strongest returns are those that treat application updates, security alignment, and AI integration as connected work, not separate initiatives.
The report does not suggest a single path forward, but it does draw a clear line between organisations that act early and those that wait. The advantage not comes from having AI, but from having applications ready to use it.
(Photo by Julio Lopez)
See also: Controlling AI agent sprawl: The CIO’s guide to governance
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Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and co-located with other leading technology events. Click here for more information.
AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.
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