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 hasdeclinedin 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:

Getting their data centers ready

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.

Getting their workplace infrastructure ready

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.

Getting their workforce ready

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.

Getting ready to protect against new threats from AI

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 nowmulti-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.