Most Companies Still Aren’t Ready for AI, But Leaders Are Starting to Capture Value

The number of companies truly ready for AI may have plateaued, with just 13 percent saying they’re prepared to operationalize the technology. That’s according to Cisco’s third annual AI Readiness Index, released earlier this month. While the topline number hasn’t shifted year over year, the context has. Cisco says the so-called “Pacesetters”—a small but disciplined group of AI leaders—are far more likely to move pilots into production and see measurable business value.

Over 8,000 AI leaders across 30 markets and 26 industries were surveyed for this year’s AI Readiness Index. Every company was measured across six pillars: strategy, infrastructure, data, governance, talent, and culture. Based on that, they were then categorized as if they belonged to a Griffyindor House: “Pacesetter” (most ready for AI), “Chasers” (moderately prepared), “Followers” (limited preparedness), and “Laggards” (unprepared).

Based on this year’s study, most companies fall into the “Followers” (48 percent) or “Chasers” (36 percent) categories. Compared with last year, the landscape is shifting slightly: the share of “Followers” has declined by three percentage points. At the same time, “Chasers” has grown by the same margin, indicating that more organizations are transitioning from cautious observation to active AI adoption.

Follow the ‘Pacesetters’

Despite the broader challenges, Cisco emphasizes that real AI impact is concentrated among “Pacesetters.” While most companies have yet to reach this level, those that have are turning AI into lasting value. According to the report, 77 percent of “Pacesetters” have finalized their AI use cases—roughly four times the global average. They are also three times more likely to track the impact of AI investments, and 1.5 times more likely to see gains in profitability, productivity, and innovation, showing that disciplined execution can make AI pilots succeed where most others struggle.

Indeed, findings from this year’s “AI Readiness Index” seem to push back, at least indirectly, on the controversial MIT study that claimed 95 percent of generative AI pilots at companies are failing. That said, Cisco’s research isn’t the evidence tech companies like Salesforce and Microsoft need to prove their AI tools and services can help businesses digitally transform. There’s more work that teams must do first to make their organizations AI-ready.

Last year, survey respondents told Cisco that they believed companies had an 18-month window to act before the costs of inaction became apparent. That concern no longer seems to be a critical one, as this year’s study examines how “Pacesetters” are capturing AI’s value in their organization. Nevertheless, demonstrating that the investment in the technology was a sound decision has raised the stakes—eight in ten companies point to sharp increases in pressure to prove tangible ROI over the past six months.

“Pacesetters” excel in this area because they’re ready and have high confidence in their initiatives. It’s believed that these companies have faith in AI to pay off. “They treat readiness as an ongoing discipline, and that’s what allows them to move further, faster,” Cisco writes. “By building the right infrastructure, governance, skills, and ways of working, they develop and deploy AI in ways that allow them to move those use cases into production where they can deliver revenue and broader impact.”

When it comes to confidence, “Pacesetters” are more likely to have identified product-market fit for use cases (85 percent versus 37 percent of other respondents), have a complete understanding of AI’s deployment risks (70 percent versus 36 percent), and have a plan on how to monetize AI and drive revenue (71 percent versus 34 percent). Cisco adds that high confidence not only leads to increased overall profitability but also benefits in other areas, such as improved customer experience, boosting team productivity, automating processes, and driving innovation.

How AI Agents Affect Preparedness

This year’s report also looks at the impact of two factors that weren’t necessarily prominent in previous years. The promotion of AI agents has spread quickly around the world, especially in the business sector, thanks to tech companies. But does the introduction of autonomous bots impact an organization’s preparedness?

Cisco’s data shows that 83 percent of respondents say they’re planning to use AI agents, with 40 percent expecting to have hybrid workforces (human and bot teams) within a year. That said, a majority of companies expressed reservations about the weak foundations of AI agents. Fifty-four percent don’t believe their networks can scale for complexity or data volume, while 15 percent think their networks are flexible or adaptable.

“Pacesetters” stand out as the exception. Their preparedness and confidence mean they’ve already laid the groundwork to scale AI agents effectively, having invested heavily in IT infrastructure, fast inference cycles, and networks designed for flexibility and adaptability.

What are the top agentic use cases? Today, there’s agreement from “Pacesetters” and everyone else that it’s autonomous software engineering (“vibe coding”). However, over the next 12 months, “Pacesetters” say it’ll be simulated humans for testing or training—autonomous agents in virtual environments—while other companies say it’ll be personal and professional productivity agents. These bots manage our schedules, emails, and task prioritization. And over the next two to three years? It’ll be industrial and robot control agents.

Paying off AI Infrastructure Debt

Another factor companies need to consider is what Cisco dubs AI infrastructure debt. It’s defined as “the accumulation of gaps, trade-offs, short-cuts, and lags in compute, networking, data management, security, and talent that compound as companies rush to deploy AI.”

It’s reminiscent of the technical debt companies grappled with in the 1990s, which later evolved into the broader concept of digital debt in the 2010s. Cisco warns that AI infrastructure debt could become a hidden drag as organizations deploy more AI agents and face growing workloads. If left unchecked, these underlying gaps could erode performance and prevent companies from capturing the full value of their AI investments.

And despite all their preparedness, “Pacesetters” won’t be immune to this.

Cisco lists early warning signs as rising costs, such as high compute costs relative to the value delivered, recurring delays in deployments, strains in talent and infrastructure resourcing, the use of outdated systems and fragmented data block scaling, and mounting workloads.

A consequence of neglecting AI infrastructure debt is on security. Without properly investing in infrastructure, companies risk potentially exposing themselves to data breaches, compliance failures, or other operational disruptions.

What Should Companies Do Then?

In simple terms: Do what the “Pacesetters” do.

Cisco advises business leaders to adopt a holistic approach to AI readiness and to act like “Pacesetters.” This means to come up with a detailed AI strategy with clear priorities—and then act on it. In addition, dedicate resources towards scaling infrastructure—don’t wait for bottlenecks to appear, plan to avoid them.

Data should be treated as a discipline, not as a hurdle. Make sure it’s clean, centralized, and can be integrated easily so AI can be trained on it.

“Pacesetters” recognize that having the full support of an organization can turn ambition into action and value. Cisco suggests executives lead the transformation effort and ensure that people are brought along and not just forced to use the technologies.

Lastly, don’t implement AI without the proper guardrails in place. This ensures that when AI agents are introduced, they can scale appropriately and do the work responsibly.

“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,” Cisco’s President and Chief Product Officer, Jeetu Patel, says in a statement. “The evidence points to a massive competitive advantage: Companies that are further along are seeing dramatically stronger returns than their peers.”

Featured Image: An AI-generated image depicting two business people, one frustrated and anxious and another holding money. Credit: Google Gemini