Organizations Struggle with AI Readiness Despite Increasing Urgency

Organizations unprepared for the AI onslaught must do these 4 things

Only 13% of executives surveyed - fewer than last year - feel ready to capture AI's potential. They lack skilled staff, higher-capacity infrastructures, and AI-ready data. When it comes to artificial intelligence initiatives, business leaders are feeling pressure to act -- and act fast. However, neither their organizations nor technology infrastructures are ready for the surge in AI applications. A survey of 7,985 senior business leaders, released by Cisco, finds 98% report increased urgency to deliver on AI and 85% believe they have less than 18 months to act. More than half (59%) give it only 12 months. Also: 5 ways to achieve AI transformation that works for your business However, at this point, only 13% say they are fully ready to capture AI's potential -- no better than the paltry 14% reporting such readiness last year. They lack skilled staff, higher-capacity infrastructures, and AI-ready data. Doubts about AI's ability to deliver returns remain on the list tool. While 50% of respondents cite pressure from the CEO and their leadership team to get moving with AI, there has been somewhat of a waning of enthusiasm about the transformative power of AI at this level. This year, 66% of respondents report that their organizations' boards are "receptive" and 75% say their leadership teams are "receptive" -- down from 82% for both last year, the survey shows. "A large number of respondents in our survey noted that their AI investments have not yet delivered the gains they expected," the survey's authors report. Nearly 50% of respondents reported not seeing any gains or gains below expectations in areas such as assisting, augmenting, or automating a process or operation. The results highlight that while companies are keen to adopt and deploy AI, the ability and readiness to fully leverage it remains limited. The lack of visible results also may be due to organizations not having the right processes in place to accurately measure the impact of AI, with just over a third (38%) of respondents saying they have clearly defined metrics to do so." The money keeps flowing to AI technologies and projects. At least 50% of those surveyed say as much as 10% to 30% of their current IT budget is dedicated to AI. Also: Want generative AI LLMs integrated with your business data? You need RAG AI skills are a major concern for companies wanting to move forward with AI. Only 31% of organizations claim their talent is at a high state of readiness to fully leverage AI. Twenty-four percent say their organizations are under-resourced in terms of in-house talent necessary for successful AI deployment. This shortage has had another unintended consequence, the survey finds. Intensified competition for skilled talent is driving up costs, cited by 48% of respondents as a major challenge. About 54% are allocating more budget to hire new talent, and 40% say their organizations are investing in upskilling and reskilling existing talent. Another 51% report hiring external vendors to train their staff, compared to 39% who say they have internal training programs. Infrastructure readiness -- or the lack thereof -- for AI is another concern. Only 21% report having the necessary GPUs to meet current and future AI demands. Only 30% have the capabilities to protect data in AI models with end-to-end encryption, security audits, continuous monitoring, and instant threat response. Also: Why data is the Achilles Heel of AI (and every other business plan) "The low readiness levels when it comes to infrastructure are worrying, especially as 93% of respondents predict that the workload of their organizations' infrastructure will increase with the deployment of AI-powered technologies," the report's authors point out. Meanwhile, 54% acknowledge their infrastructure has limited or moderate scalability and flexibility to accommodate these increasing needs. Plus, only one-third (32%) of respondents report high readiness from a data perspective to adapt, deploy, and fully leverage AI technologies. Most companies (80%) report inconsistencies or shortcomings in the pre-processing and cleaning of data for AI projects. This remains almost as high as a year ago (81%). Additionally, 64% report that they feel there is room for improvement in tracking the origins of data. Measuring AI's impact on growth and revenues is another problematic area. While 87% of executives say their organization has a process in place to measure AI's impact, only 38% have clearly defined metrics. In terms of financial preparedness, 81% (down from 84% last year) have a financial strategy to support AI deployment in place, but only 43% say they have a long-term financial plan. Also: Gen AI could speed up coding, but businesses should still consider risks The report's authors make the following recommendations to bring organizations and technology up to speed with burgeoning demands for AI:

Not Ready For AI? Time To Lay The Groundwork

Our recent Cisco AI Readiness Index, found that only 13% of organizations report themselves ready to capture AI's potential, even though urgency is high. Companies are investing, but close to half of respondents say the gains aren't meeting expectations. Here's how organizations can get themselves better prepared. I believe that in the next few years, there will be only two kinds of companies: those that are AI companies and those that are irrelevant. You might think that AI has not lived up to the hype of the last few years but let me remind you that when the cloud started, a lot of people thought that it was over hyped. The same was thought of the internet too. The fact is, when truly transformational movements come along, the full extent of the impact is usually overestimated in the near term but greatly underestimated over the long term. This is especially true with AI. According to one estimate, over $200B has been spent on training the most recent language models, but global revenue being realized is only about one-tenth of that, and mostly attributable to just a few companies. Some customers I speak with know exactly how they are going to win the age of AI. Many others aren't clear what they need to do. But they know they need to do it fast. We just released our latest AI Readiness Index, and it highlights that story perfectly. The survey tells us that the vast majority of organizations aren't ready to take full advantage of AI, and their readiness has declined in the last year. This is not surprising to me. The pace of AI innovation is moving so fast, that readiness will reduce if you are not keeping up. Despite that, there is intense pressure from CEOs to do something: 85% of organizations say that they have no more than 18 months to deliver value with AI. Most organizations know that they need a strategy to set their direction and clarify where they should expect to see ROI. So, what can they do to be ready to move fast when their strategy becomes clear? Here are a few things our customers doing: The processing, bandwidth, privacy, security, data governance, and control requirements of AI are forcing organizations to think deeply about what workloads should run in the cloud, and what should run in private data centers. In fact, many organizations are repatriating workloads back to their own private clouds. However, their data centers are not ready. Even if you are not building out GPU capabilities today, you need to be thinking about your data center strategy: Are your current workloads running on optimized, energy-efficient infrastructure? Are you going to add AI capabilities to existing data centers or build new ones? Are you ready for the high-bandwidth, low-latency connectivity requirements of either strategy? These are questions that every organization needs to be thinking about today to improve preparedness. AI will transform everywhere we work and connect with customers- campuses, branches, homes, cars, factories, hospitals, stadiums, hotels, etc. The reality is that our physical and digital worlds are converging. IT, real estate, and facilities teams are investing billions in new infrastructure -- sensors, devices, and new power solutions that deliver amazing experiences for employees and customers while giving them the data and automation to massively improve safety, energy efficiency, and more. But this is just the start. Imagine a world where future workplaces include advanced robotics, even humanoids! Are your workplaces ready with the network infrastructure required to deliver the bandwidth and device density that this new world will require? Are they ready to do inferencing "at the edge" to handle future compute and bandwidth requirements to power robotics and IoT use cases? Do you have security deeply embedded in your infrastructure to defend against modern threats? These are all strategies that should be considered today. The first wave of language-based AI has changed how we get information and handle some basic tasks, but it hasn't really changed our jobs. The next wave will be much more transformational. Solutions based on agentic workflows, where AI agents with access to critical systems can work together with those systems to get information and automate tasks, will have an impact on how we perform our work and our roles in getting work done (e.g., are we doing tasks or reviewing and approving them?). And yes, in some cases, AI will transform roles. As leaders, now is the time to be thoughtful about what this world will look like and start preparing for this future -- from the impact on culture to the impact on privacy and security. While much attention has been paid to the use of AI as a new attack vector, and as a new way to defend against those attacks, we also need to be thinking about AI safety more broadly. Unlike previous systems, where an attack could cause downtime or lost data;, an attack or improper use of an AI-based system can have much worse downstream impacts. We are moving from a world that used to be just multi-cloud, to now multi-model, and as a result, the attack surface is much larger, and the potential damage from an attack is much greater. . Imagine the impact of a prompt injection attack that corrupts back-end models and affects all future responses, or creates unanticipated responses that cause an agentic system to damage your reputation, or worse? I believe that over the next year, AI safety is going to take centerstage and organizations are going to need to develop strategies now. Given the complexity of putting all of these foundational elements together, it's understandable that more organizations haven't moved faster and feel they are less ready than last year. But I believe that there are decisions you can make today to get ready, even if your overall AI strategy is not fully clear.

Companies are feeling the urge to get up to speed with AI - but many simply aren't ready

Lack of skills and proper infrastructure also remain a challenge for many Many companies are desperate to use AI in their workplace, but simply don't have the skills or talent required to do so effectively, new research has claimed. Covering nearly eight thousand companies, the latest AI Readiness Index from Cisco has found only 13% of companies feel they are fully ready to capture the potential of AI tools. This is even a fall from the previous year, but comes alongside a growing urgency from bosses to ensure they don't fall behind when it comes to the advantages AI technology can bring. The study found nearly all companies (98%) said there was an increased urgency to deploy AI over the past 12 months, despite readiness for the technology declining. This readiness was not helped by the apparent shortfall in back-end technology, with networks in particular not equipped to meet the strain of AI workloads, as the study found only 21% of companies believed they had the necessary GPUs to meet current and future AI demands. Security was also a concern, as less than a third (30%) of firms said they had the capabilities to protect data in AI models with end-to-end encryption, security audits, continuous monitoring and instant threat response. However this is not to say that the outlook is necessarily bleak for firms looking to use AI, as budgets are set to evolve as the technology landscape changes. The study found roughly 30% of IT budgets will be dedicated to AI, nearly double the current fuigure, and nearly half of companies say although AI implementations across top priorities have fallen short of expectations so far, nearly two-thirds (59%) believe the impact from AI investments will surpass expectations after five years. Nearly two-thirds (66%) of boards are also reportedly highly or moderately receptive of focusing more on AI in the future, potentially signalling further support - although the study did note this was down from 82% last year. "Eventually there will be only two kinds of companies: those that are AI companies, and those that are irrelevant. AI is making us rethink power requirements, compute needs, high-performance connectivity inside and between data centers, data requirements, security and more," said Jeetu Patel, Chief Product Officer at Cisco. "Regardless of where they are on their AI journey, organizations need to be preparing existing data centers and cloud strategies for changing requirements, and have a plan for how to adopt AI, with agility and resilience, as strategies evolve."