Skip to Content

How ready are companies to scale AI, especially agentic systems, without hitting hidden bottlenecks?

Only a small group — just 13% of organizations, dubbed the “Pacesetters” — are truly ready. Most are racing ahead with ambition but lagging in infrastructure, governance, and measurement

Key Takeaways

  • Ambition > Readiness: While 83% of companies plan to deploy AI agents, only 34% say their infrastructure can scale to meet the demands. 
  • Readiness drives value: Pacesetters are more likely to have finalized use cases, more likely to measure impact, and 1.5× more likely to see profitability gains 
  • AI Infrastructure Debt is real: Compromises and underinvestment today are quietly accumulating — threatening to slow innovation and inflate costs tomorrow

Most companies have moved beyond ideation — 64% are piloting or finalizing use cases — but they’re doing so on shaky foundations. Rising compute demands, fragmented data, and weak security posture (only 31% feel fully capable of securing agentic AI systems) are creating a widening gap between AI ambition and operational reality.

Interestingly, most industries are focusing their AI efforts on operational efficiency and automation — not just to cut costs, but to reimagine processes end-to-end. Yet, without AI readiness, efficiency gains may plateau before true transformation takes root. 

Pacesetters stand out because they treat readiness as a discipline: 

1️⃣ They plan infrastructure ahead, rather than reacting to bottlenecks. 

2️⃣ They embed governance and change management early, avoiding stalled adoption. 

3️⃣ They treat data as a strategic asset, not an afterthought. 

As the report “Cisco AI Readiness Index 2025” aptly notes, “Value follows readiness.” Agentic AI promises transformative gains, but without a solid foundation, it risks becoming another wave of hype weighed down by technical debt. 

🔸 Strategic takeaway: If you’re scaling AI, your competitive advantage won’t come from the number of pilots you run — but from how robustly you build the infrastructure, governance, and organization culture to sustain them. 

#AIReadiness #AgenticAI #Automation #DigitalTransformation #AIAgents #AIInfrastructureDebt #AIGovernance #CIO #AIFuture #CiscoAIReadiness2025

Agentic Workforce November 18, 2025
Share this post

Archive
Are Small Language Models (SLMs) better than LLMs for building AI agents?
For the majority of specialized, repetitive agentic tasks, SLMs are set to take the lead — offering sufficient capability, lower latency, and dramatically reduced costs.