AI adoption rises, but real returns remain uneven
Artificial intelligence has quickly moved from a buzzword to a boardroom priority across industries. Organisations worldwide are investing heavily in AI tools, launching pilots, and building strategies to stay competitive in an increasingly digital economy. However, despite rising budgets and ambitious plans, many companies are struggling to translate AI investments into meaningful results.
A new report from Cloudflare suggests the problem may not be AI itself—but the digital infrastructure supporting it.
According to the Cloudflare 2026 App Innovation Report, organisations that modernise their applications are nearly three times more likely to see tangible returns from AI compared to those relying on outdated systems. The findings highlight a critical shift in understanding: AI success depends less on experimentation with new tools and more on the readiness of underlying applications.
The report is based on insights from more than 2,300 senior technology and business leaders across the Asia-Pacific (APAC), Europe, the Middle East, and the Americas. It provides a global snapshot of how organisations are evolving their application environments to support AI-driven transformation.
Application modernisation emerges as the key differentiator
One of the most striking findings from the report is the strong correlation between modern application environments and AI success. Organisations that are ahead of schedule in modernising their apps report significantly higher confidence in their AI outcomes.
In the APAC region, the connection is even stronger. A remarkable 92% of technology leaders surveyed said that modernising software was the single most important factor in improving their organisation’s AI capabilities.
This highlights a growing realisation: AI cannot operate effectively on top of fragmented, outdated, or inflexible systems. Instead, it requires a robust digital foundation that allows rapid access to data, seamless integration, and scalability.
Legacy applications, on the other hand, often slow down AI projects, creating bottlenecks that prevent solutions from moving beyond trial phases.
From AI experiments to integrated intelligence
In the early days of AI adoption, organisations focused heavily on experimentation. Proof-of-concept projects, chatbots, and automation pilots dominated AI roadmaps. But the Cloudflare report shows that the industry mindset is evolving.
Today’s leading organisations are no longer treating AI as a standalone innovation project. Instead, they are embedding AI directly into core business applications, workflows, and customer-facing platforms.
In APAC, 90% of organisations that are ahead in application modernisation have already integrated AI into their existing systems. Nearly 80% plan to expand AI integration further within the next year.
This shift reflects a more mature approach to AI. Rather than testing what AI can do, organisations are now focusing on how AI can enhance everyday operations—from improving internal productivity to driving revenue-generating activities.
Why modern applications matter for AI performance
AI systems rely heavily on real-time data, fast processing, and flexible integration capabilities. Modernised applications provide these essentials by leveraging cloud-native architectures, APIs, and microservices.
When organisations operate on modern platforms, AI tools can:
- Access clean, structured data more efficiently
- Integrate seamlessly across departments and platforms
- Scale without major infrastructure changes
- Deliver real-time insights and automation
In contrast, organisations with legacy infrastructure often struggle with fragmented data, manual workflows, and slow system performance. These challenges make it difficult for AI to deliver consistent or scalable results.
The report describes application modernisation as a self-reinforcing cycle:
Modern applications enable AI success, and AI success then justifies further modernisation investments.
The confidence gap between leaders and laggards
One of the key differences between organisations seeing strong AI returns and those struggling lies in confidence.
Leaders in application modernisation report significantly higher confidence in:
- Their infrastructure’s ability to support AI
- Their teams’ technical capabilities
- Their organisation’s readiness for digital transformation
This confidence translates into faster decision-making and more ambitious AI deployment strategies.
On the other hand, organisations that lag behind tend to move cautiously. They often hesitate to scale AI projects due to concerns about stability, security, or integration complexity.
As a result, AI initiatives in these organisations remain limited to isolated use cases rather than becoming part of core operations.
The hidden cost of delaying modernisation
The report also highlights the risks of delaying application modernisation.
Organisations that postpone upgrades often end up modernising reactively—usually after a major security incident, system failure, or operational disruption. This reactive approach is not only more expensive but also more disruptive.
In APAC, organisations that lag behind report:
- Lower confidence in their infrastructure
- Greater difficulty supporting AI initiatives
- Higher levels of technical debt
- Increased operational risk
Instead of innovating, teams spend significant time managing crises, patching vulnerabilities, and fixing system failures.
This reactive cycle slows down AI adoption and prevents organisations from achieving long-term digital transformation goals.
Security: the cornerstone of scalable AI
Security plays a critical role in the relationship between application modernisation and AI success.
The Cloudflare report reveals that organisations with strong alignment between security teams and application teams are far more likely to scale AI effectively.
When security is built into application design from the beginning, organisations experience fewer disruptions and can move faster with AI deployments.
However, in organisations where security is treated as an afterthought, teams often struggle with:
- Tracking vulnerabilities across applications and APIs
- Managing security incidents
- Ensuring compliance during AI integration
These challenges create friction that slows innovation and increases risk.
The report suggests that reliability has become a practical limit on AI speed. Without stable and secure systems, organisations simply cannot move AI projects into production at scale.
Tool sprawl: a growing challenge for digital teams
Another major obstacle highlighted in the report is the growing complexity of technology stacks.
Many organisations have accumulated dozens—or even hundreds—of tools, platforms, and integrations over time. While each tool may solve a specific problem, the overall complexity can make modernisation and AI integration extremely difficult.
In APAC, nearly all organisations surveyed reported challenges related to tool sprawl. However, leading organisations are taking proactive steps to address the issue.
About 86% of APAC leaders said they are actively reducing redundant tools and tackling shadow IT.
The goal is not just cost savings. A simpler, more streamlined technology environment makes it easier to:
- Modernise applications
- Implement consistent security policies
- Integrate AI across systems
How developer productivity shapes AI outcomes
Developer efficiency is another critical factor in AI success.
Organisations with modernised applications report that their developers spend more time improving existing systems and building new features.
In contrast, developers in lagging organisations spend a disproportionate amount of time on:
- Rebuilding outdated systems
- Fixing configuration issues
- Managing technical debt
- Responding to incidents
This difference has a direct impact on AI progress. When developers are tied up with maintenance tasks, AI innovation becomes a lower priority.
Modern application environments free up developer time, allowing teams to focus on strategic initiatives like AI integration and automation.
AI success is about removing obstacles, not adding tools
One of the most important takeaways from the Cloudflare report is that AI success is not about deploying the latest models or tools.
Instead, it is about removing the obstacles that prevent AI from delivering value.
Organisations that focus solely on AI experimentation without addressing underlying infrastructure issues often experience disappointing results.
By contrast, organisations that prioritise application modernisation, security alignment, and integration strategy are more likely to achieve measurable AI returns.
APAC organisations face a critical crossroads
For organisations across the APAC region, the report delivers a clear message: AI investment without modernisation leads to limited impact.
At the same time, modernisation without a clear AI integration plan can become an endless rebuild process.
The organisations seeing the strongest results are those that treat modernisation, security, and AI integration as interconnected initiatives rather than separate projects.
The future belongs to AI-ready organisations
The Cloudflare report does not prescribe a single roadmap for success, but it draws a clear distinction between organisations that act early and those that wait.
The advantage does not come from simply adopting AI. It comes from having applications that are ready to support AI at scale.
As AI continues to evolve, organisations with modern, secure, and integrated application environments will be best positioned to unlock its full potential.
Those that delay may find themselves stuck in a cycle of experimentation without impact.
Conclusion: Modern foundations define AI winners
The AI race is no longer about who adopts the technology first. It is about who builds the right foundation to make AI work.
Cloudflare’s findings make one thing clear: application modernisation is the missing link between AI investment and AI value.
For organisations worldwide, the message is simple yet urgent:
Before asking what AI can do, ensure your applications are ready to support it.