Cisco AI Readiness Index: Building trust, infrastructure, and measurable value

Cisco's research shows that leading organizations treat AI as a core part of their business, not a side project

A small but steady group of companies continues to turn AI plans into measurable results. Cisco's latest AI Readiness Index shows that about 13% of organizations across Asia Pacific, Japan, and Greater China — the same share seen globally — are pulling ahead on every measure of AI value. Cisco calls them the Pacesetters.

Their consistency over three years shows that success in AI depends on structure, not speed — a system built on clear strategy, good data, and flexible infrastructure. Nearly all Pacesetters (98%) are designing networks that can handle AI's growing scale and complexity, compared with only half of other companies in the region.

This discipline matters as two forces reshape AI adoption: the rise of AI agents, which demand stronger scale, security, and oversight; and AI Infrastructure Debt, the buildup of outdated systems and underfunded upgrades that can limit long-term value.

"This year's Cisco AI Readiness Index makes one thing clear: readiness leads to value," said Ben Dawson, SVP and President for Asia Pacific, Japan, and Greater China at Cisco. "The Pacesetters prove it. They're four times more likely to move pilots into production and 40% more likely to see measurable value."

What sets pacesetters apart

Cisco's research shows that leading organizations treat AI as a core part of their business, not a side project. Almost all have clear roadmaps and funding strategies, with budgets that support both short- and long-term goals. They've also built networks ready for growth — most can scale instantly for new AI projects and plan to expand data-center capacity within a year.

Their advantage comes from execution. More than 60% have mature processes for turning pilots into production, and three-quarters have finalized their AI use cases. Nearly all track the impact of their AI investments, and most expect new revenue streams as a result. Security is also central to their approach: they are more aware of AI-specific risks and have built protections into both identity and infrastructure systems.

Because of this focus, nine in ten Pacesetters report gains in profitability, productivity, and innovation — far above the regional average.

Lessons for smaller businesses

Dawson said smaller firms can learn from this discipline. AI shouldn't sit apart from business goals — it should be part of them. He emphasized the importance of moving from pilot to production and linking results to measurable outcomes. "Measurement is key, and security is just as important for SMEs as it is for larger firms," he said.

He added that smaller businesses relying on external AI services should demand the same level of security from their providers as they do internally.

Simon Miceli, Managing Director of Cloud and AI Infrastructure for APJC at Cisco, said readiness also depends on trust and infrastructure. "There's a trust deficit we need to overcome," he said. "There's also a data gap that needs to be addressed. It's about having efficient infrastructure, getting data to a usable point, and being able to fundamentally trust the AI system."

Miceli noted that rising costs — especially infrastructure and power — remain a concern across the region.

Readiness and results

Cisco's findings link AI readiness directly to business outcomes. Dawson said industries that continue investing in digital infrastructure — such as technology and financial services — are best placed to capture new value.

Readiness levels vary widely. Only 2% of organizations in Hong Kong are fully prepared for AI, the lowest globally. Miceli said this may relate to access to computing technology, while Dawson pointed out that developing markets like Indonesia and Thailand are moving faster, seeing AI as a chance to leapfrog more established peers.

Cisco's focus on AI workloads

Cisco is aligning its technology portfolio around modern AI needs. Miceli said the company is building "secure AI factories" — systems designed to manage AI workloads end to end. "We're driving innovation in our network — high-bandwidth, low-latency systems with 800G today and moving to 1.6T soon," he said.

Cisco is also expanding its compute portfolio with GPU technology and strengthening cybersecurity to protect both infrastructure and AI models. Tools like Splunk help organizations monitor and optimize performance across the entire stack.

"There's a strong innovation agenda across our portfolio focused on supporting AI workloads," Miceli said.