AI-ready leaders move faster and earn more, finds Cisco report

Cisco’s third annual AI Readiness Index has revealed that the world’s most AI-prepared companies, termed “Pacesetters,” are three times more likely to move pilot projects into production and 72 percent more likely to achieve measurable value from their AI investments.

The study, which surveyed over 8,000 AI leaders across 30 markets and 26 industries, identifies that only 17 percent of organisations in India and 13 percent globally fall into this elite category. These firms are characterised by a strategic, disciplined approach that combines strong infrastructure, data readiness, and a forward-looking AI roadmap.

“We’re moving past the era of question-answering chatbots and stepping into the next major phase of AI: agents that independently execute tasks,” said Jeetu Patel, Cisco’s President and Chief Product Officer. “Today’s study shows that over 80 percent of companies are prioritizing agentic solutions, with two out of three reporting that these systems are already meeting or exceeding their performance goals. The evidence points to a massive competitive advantage: companies that are further along are seeing dramatically stronger returns than their peers.”

According to the report, 98 percent of Pacesetters are designing their networks for AI scalability compared to 59 percent in India. Nearly all of them (99 percent) have a defined AI roadmap, while 91 percent have a clear change-management plan in place.

The findings highlight that Pacesetters make AI central to business strategy rather than treating it as an experiment. They also invest aggressively in infrastructure, with 77 percent planning new data-centre capacity in the next year. Importantly, 95 percent of these leaders track the impact of their AI projects, and 71 percent are confident that their use cases will generate new revenue streams.

Cisco’s report also explores the rise of AI agents, noting that 91 percent of Indian organisations plan to deploy them soon, with 41 percent expecting to integrate them into their workforce within a year. However, most still lack the secure infrastructure needed to sustain autonomous, learning AI systems.

The study introduces a new concept called AI Infrastructure Debt, referring to the buildup of underfunded systems and deferred upgrades that can erode the long-term value of AI. Cisco warns that without addressing this issue, many companies risk falling behind as workloads grow and data becomes harder to centralise.