AI Adoption in Business: The Gap Between Ambition and Success

A minority of businesses have won big with AI. What are they doing right?

Numerous studies show most businesses don't see ROI with AI.Those that do prioritize long-term stability, Cisco says."Pacesetters" emphasize trust and treat AI like an OS. We're currently living through a paradoxical moment. Businesses are embracing AI, yet very few of them, it seems, are deriving much benefit from the technology. What are those select few doing right? Also: I unleashed Copilot on my Microsoft and Google accounts - here's what happened This is the question telecommunications company Cisco set out to answer in its third annual "AI Ready Index," published Tuesday. Following a survey of more than 8,000 business leaders, all of whom are charged with overseeing their organizations' internal AI efforts across twenty-six countries, the Index sought to identify the factors leading to success in the early days of the AI boom -- and, in turn, those causing the vast majority of businesses to remain stagnant. Many businesses have had to learn in recent years that adopting AI to automate certain organizational tasks or employees' day-to-day workflows won't necessarily translate to financial gain. The technology may make workers more productive in some respects, but it also presents a whole host of risks -- some of them involving cybersecurity, some of them legal, some of them psychological. In some cases, AI actually creates more work for supervisors. Also: AI use is up, but organizations still aren't seeing gains, Atlassian study finds There's now a growing pile of evidence that most businesses -- almost all of them, in fact -- have been struggling to achieve meaningful ROI through their internal AI efforts. Most infamously, a MIT study published in August found that 95% of businesses' AI initiatives have essentially gone nowhere, while a recent study from Atlassian showed that even more (96%) "have not seen dramatic improvements in organizational efficiency, innovation, or work quality" from AI, despite the fact that the technology is being used by more individual workers than ever. The MIT and Atlassian studies offer some theories to explain why so few enterprises have successfully profited from their AI initiatives. Cisco does the same by highlighting a small minority of what it calls "Pacesetters" that have been using AI successfully and confidently. Pacesetters have consistently represented about 13% to 14% of the businesses that have been surveyed for each of the company's Indexes over the past three years. Cisco's description of a Pacesetter is reminiscent of that of a sharp-eyed investor, someone who is able to forgo instant gratification in order to patiently build out the habits and technological support that will sustain long-term growth. Also: Your colleagues are sick of your AI workslop These comparatively successful outliers "adopt a disciplined, system-level approach that balances strategy, infrastructure, data, governance, people and culture," Cisco wrote in its full report. "They plan ahead, invest early, and embed AI into the core of how they operate to help them keep pace with AI's accelerating evolution and deliver lasting value." Pacesetters treat AI as more of a new operating system for their organizations rather than merely a new device to be added to employees' technological arsenals. It's not a hammer -- instead, it's a new set of blueprints that will redefine the business' digital ecosystem. That implies a level of heightened ambition, which, according to Cisco, requires a great deal of patience, attention to detail, and creativity. Also: AI is making cybercriminal workflows more efficient too, OpenAI finds Almost all Pacesetters (99%), for example, have developed what Cisco describes as an "AI roadmap" to guide their internal use of the technology over time, compared to just over half (58%) of all other businesses that were surveyed. Additionally, 87% of Pacesetters said they're "highly aware of AI-specific threats" to their organizations' cybersecurity (compared to 42% of other respondents), while 75% said they're "fully equipped to control and secure AI agents" (compared to 32%). Trust in their internal AI tools "is part of the Pacesetters' value equation," Cisco wrote in a press release published Tuesday. Want more stories about AI? Sign up for AI Leaderboard, our weekly newsletter. On that note, a study published in September by data analytics company Statistical Analysis System (SAS) and the International Data Corporation (IDC) found that one of the key factors inhibiting companies from achieving ROI from their internal AI initiatives was a lack of trust in the technology itself. Implementing AI successfully also requires a willingness to focus on automating some of the more mundane aspects of running a business. Investing in an AI-powered customer service tool might be less headline-grabbing than, say, launching a full-blown video ad generated by Sora, but it will probably deliver more value over the long run. Also: Even the best AI agents are thwarted by this protocol - what can be done That conclusion is supported by recent data from market research firm Forrester, which indicates that the most fruitful business applications of AI will be those that operate behind the scenes. A new list from venture capital firm Andreessen Horowitz (a16z) highlighted the top 50 AI startups that enterprise customers are currently investing in, many of which are relatively unknown companies offering niche automation services.

Cisco: Most companies don't know what they're doing with AI

Contrary to popular belief, you can't succeed in business (or AI) without really trying. Many orgs are jumping on the AI bandwagon without the infrastructure they need to make it work or track results, Cisco says. Most haven't even defined what they want their AI agents to do. The networking hardware manufacturer found in its 2025 AI Readiness Index that most companies are planning to deploy additional AI agents in the next few years, and 86 percent expect it to improve employee productivity within three years, but those expectations don't necessarily match the reality of what it takes for such an initiative to succeed. According to Cisco, part of that reality is the need to invest in new hardware, particularly networking gear. Per the company, 54 percent of respondents said their infrastructure can't scale for rising workloads driven by AI adoption, and just 15 percent said that their networks were "flexible or adaptable" in a way that would facilitate the new AI era of business. That's not all, though, and Cisco tells The Register that infrastructure is "only one part of the AI readiness index equation." The rest, a spokesperson explained in an email, includes strategy, data, governance, human talent and company culture. Take agentic AI, for example. 83 percent of those surveyed said that their companies intend to develop or deploy AI agents, and 40 percent expect AI agents to be working alongside humans within a year. Putting aside the fact that AI agents are still getting stuff wrong most of the time, very few businesses seem prepared to bring agentic AI into the enterprise fold. Per the report, only 31 percent of companies say that they're prepared to control and secure agentic AI systems, while only 32 percent have identified which human tasks they want agents to supplement or take over. "A wave of technology can leave behind a trail of shortcuts, compromises, and underinvestment that later become bottlenecks," Cisco noted, and it has a name for that phenomenon: AI infrastructure debt, a new iteration of the old-fashioned concept of technical debt. Instead of shaky code and poorly written software leading to a business bottleneck, AI infrastructure debt is all about not having the necessary things in place to actually make AI investments more than window dressing. "As history with technical debt shows, what looks like an acceptable compromise in the early phases can snowball into systemic drag," Cisco said in the report. "Organizations know their infrastructure isn't ready for the surging workloads, they acknowledge that their security measures are still fragile, and their workforce plans are out of sync with the technology." Shaky foundations mean that AI value is hard to determine too, says Cisco. Only 32 percent of firms have a process in place to measure the success or failure of their AI investments, meaning that the much-reported lack of AI ROI could be skewed as well. Nonetheless, companies are pushing ahead, says Cisco. Cisco's study splits its cohort of respondents into two pools: Companies that are making responsible decisions when integrating AI into their operations, and everyone else. That former category only makes up between 10 and 15 percent of companies, and those are the ones that Cisco says other firms should look to when thinking about how their own AI initiatives should look from the ground up. Unlike most respondents, which still lag in IT infrastructure, data preparedness, and governance, those are all strong points for what Cisco calls its "Pacesetter" companies. Among these firms setting the pace for AI adoption, 74 percent report high or full readiness in IT infrastructure, 93 percent in data management, and 84 percent in governance - well above the averages for everyone else. Identifying use cases and figuring out how to measure the effectiveness of AI investments is also a consideration for most pace-setting companies. The result, Cisco said, is far more confidence in the effectiveness of AI for those companies. But who are the pacesetters? If they're giant companies able to eat losses on bad AI bets, then this isn't so much a measure of ambition or planning as it is a measure of resources. Cisco told us that's not the case - pacesetters are found in a cross section of companies. "Pacesetters make up 10-15 percent of companies across every size bracket, and even the largest firms have as many laggards as leaders," Cisco told us. "What really seems to distinguish Pacesetters is discipline and execution: they plan, fund, and measure AI systematically, and get more consistent results." In other words, planning AI initiatives is just like planning any other major business transformation initiative: Build those castles on sand and they're not going to stay upright. "As we move into an always-on, agentic era, the companies we surveyed expect the strain on networks, compute, and security to rise," Cisco said in an email conversation. "The evidence suggests that readiness - built on a secure, scalable foundation - might play a big role in helping organizations keep pace."

Cisco is warning of AI Infrastructure debt. Here's why - and what it means for enterprise buyers

For the latest edition of Cisco's AI Readiness Index, Cisco surveyed more than 8,000 business leaders representing 30 markets globally and 26 industries. This is the third year of the survey and over that time it has identified a small group of companies which it calls the Pacesetters who are fully prepared for AI, being, among other things, three times more likely than the other companies surveyed to measure the impact of their AI investment. Consequently, they are in a position to report gains in profitability, productivity and innovation from their finalised AI use cases. However, even these companies, according to Cisco, are not immune from AI Infrastructure Debt. The concept of technology debt is, of course not a new one, it simply means that organizations are storing up future costs and problems by cutting corners to get systems up and running more quickly. An example occurred earlier this century when organizations lifted and shifted existing applications and plopped them onto a cloud infrastructure. In so doing some infrastructure costs were quickly reduced, but the applications themselves were not designed to run in this type of environment which created new security vulnerabilities among other things. Cisco is identifying a similar problem for AI deployment. As the report notes: AI Infrastructure Debt is 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. With 83% of companies surveyed planning to deploy AI agents, workloads rising and readiness levels stalling, AI Infrastructure Debt could quickly become the silent bottleneck preventing companies from realizing the value they expect. As companies are rushing to deliver AI pilots and scale up to prove the value of the AI investment, important steps are often set aside such as modernizing the infrastructure, tightening governance and addressing security steps. Cisco believes this technical debt is already beginning to show in rising costs finding that "AI is becoming increasingly expensive relative to the value delivered, Pacesetters also face high costs, which grow as they scale advanced deployments." It also notes recurring delays as "most companies struggle to move from pilot to production." There is resource strain as talent and infrastructure gaps slow AI adoption and readiness gaps as "outdated systems and fragmented data block scaling." The security risks are typically where technical debt becomes acutely visible and Cisco says: The Index shows that only 31% of organizations feel fully capable of securing agentic AI systems, and fewer than half feel confident in safeguarding sensitive data or preventing unauthorized access. Cisco suggests that the behaviour of the Pacesetter cohort is worth emulating in order to be better prepared for AI deployment. The Index shows that Pacesetters are: Cisco's takeaways for companies wishing to avoid AI Infrastructure Debt includes investing in new data centre capacity in the next 12 months, having clean, centralized data with real-time integration for AI agents as well as controlling agent actions with guardrails and live monitoring. This is because "most respondents plan to deploy AI agents, that will act autonomously and connect with other business applications," which means, "a misaligned or breached agent presents both a data risk and an operational one." Cisco also highlights the need for having strong in-house AI talent and a full change management plan for AI. And yet the Index finds that "while companies are bullish about deploying agents, only 32% say they've already identified which human tasks will be handled by AI and factored that into workforce planning." As Cisco comments: This lack of clarity risks leaving organizations unprepared, both for reskilling and for the creation of entirely new AI governance, monitoring and safety roles. Cisco concludes: Taken together, the data shows a contradiction between ambition and infrastructure. Organizations know their infrastructure is not ready for the surging workloads, they acknowledge that their security levels are still fragile, and their workforce plans are out of sync with the technology. Nevertheless, they are pushing ahead. Of course, it could be argued that anxiety about this gap between ambition and readiness is precisely what is slowing down the realization of scaled production AI use cases. Most organizations, are self-aware enough to know they are not ready. However, there is always a tension between vendor exhortations to adopt new technology and organizational ability to properly get value from the new technology. Cisco's virtuous role in the current market situation is to urge enterprises to prepare to avoid the AI Infrastructure Debt. While Cisco's altruism is driven by a vested interest in enterprises investing in AI infrastructure readiness at the network level, the survey findings land responsibly. For when it comes to agentic AI, it may well pay to be more tortoise than hare in order to win the deployment race.

AI-ready Enterprises Build Lasting Competitive Edge, Finds Cisco's Global Study

The combination of foresight and foundation is delivering real, tangible results at a time when two major forces are starting to reshape the landscape: AI agents, which raise the bar for scale, security, and governance; and AI Infrastructure Debt, the early warning signs of hidden bottlenecks that threaten to erode long-term value. "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% 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."