A new global study by Cisco reveals that organizations leading in AI adoption are making distinct infrastructure decisions that enable them to realize value faster and more sustainably. According to Cisco’s 2025 AI Readiness Index, 97% of the world’s most AI-ready companies—referred to as “Pacesetters”—have deployed AI at scale and achieved measurable returns on investment.
In contrast, nearly half of Indian companies risk falling behind due to what Cisco calls “AI infrastructure debt”—the accumulated technical and operational bottlenecks caused by short-term infrastructure planning.
Simon Miceli, Managing Director, Cloud and AI Infrastructure, Asia Pacific, Japan and Greater China at Cisco, said that while AI leaders are re-architecting their systems from the ground up, many Indian firms are still building reactively. “The 45% of Indian companies without this level of architectural foresight risk accumulating AI Infrastructure Debt—the shortcuts and gaps that compound into bottlenecks that cripple innovation and competitiveness,” he said.
The Cisco study identifies four key infrastructure choices that set Pacesetters apart from the rest:
1. Solving for power constraints before they occur:
More than half of Indian organizations expect AI workloads to grow by over 50% in the next three to five years, yet 45% are building AI capacity without corresponding power infrastructure. Globally, 96% of Pacesetters have already developed dedicated systems to optimize power consumption.
2. Treating network as the foundation:
While many companies focus primarily on compute power, Pacesetters invest heavily in network infrastructure. Eighty-one percent of global leaders rate their networks as “optimal” for AI workloads, compared to only 27% in India. Cisco warns that as AI workloads double, network capacity could become the next major bottleneck.
3. Driving continuous optimization beyond deployment:
AI leaders treat model deployment as the starting point, not the endpoint. Seventy-two percent of Pacesetters monitor and retrain models automatically, enabling faster updates and reduced downtime. In India, only 33% of organizations follow continuous optimization practices.
4. Embedding security from day one:
Security remains one of the biggest gaps in India’s AI ecosystem. While 91% of Indian organizations are deploying autonomous AI agents, just 37% have the necessary security frameworks to protect them. In comparison, 75% of global Pacesetters secure their AI systems through embedded, infrastructure-level encryption and continuous monitoring.
Cisco’s findings suggest that AI maturity is increasingly defined not by how much companies spend on technology, but by how early and strategically they invest in infrastructure. Firms that build reactively, the report notes, risk compounding inefficiencies across operations, security, and compliance.
“The infrastructure choices companies make today determine what they can become tomorrow,” the report concludes, adding that early movers are already gaining structural advantages that will be difficult to replicate later.
