Artificial Intelligence surged to the forefront of business strategy in 2024, but a stark reality emerged: most companies were not ready to fully leverage it. Cisco’s 2024 AI Readiness Index revealed a profound gap between the urgent push to adopt AI and the actual preparedness of organizations.
Now in 2025, AI technologies and use cases have evolved at breakneck speed – from generative AI models embedded in workflows to autonomous “AI agents” performing tasks. Business leaders are grappling with how to harness this momentum while shoring up strategy, infrastructure, data management, governance, talent, and culture.
This article takes a look at Cisco’s 2024 findings and compares them with the current AI landscape in 2025, highlighting key shifts and insights for executives planning their next moves.
Table of Contents
Urgency vs. Readiness: A Year of Acceleration and Pressure
Skyrocketing Demand, Sobering Readiness
Cisco’s 2024 report painted a picture of overwhelming executive urgency accompanied by low organizational readiness. Nearly all companies felt increased pressure to deliver on AI initiatives, and most believed they had less than 18 months to act before seeing negative business impacts. Yet only a small percentage of organizations claimed to be fully prepared to capture AI’s potential, a slight drop from an already low percentage the previous year. In other words, barely one in seven companies globally was at a high level of AI readiness, even as the clock ticked on AI deployment timelines.
2025: Adoption Surges Despite the Gap
Fast-forward to 2025, and AI adoption has only accelerated. The advent of powerful generative AI tools in 2023 triggered widespread experimentation, and by early 2024, more than half of organizations were using generative AI regularly. Overall AI integration across business functions also jumped significantly. This surge reflects a shift from AI experimentation to meaningful adoption.
Leaders Feel the Heat
The urgency noted in 2024 has only intensified amid this rapid uptake. CEOs and boards now recognize that failing to capitalize on AI could be an existential threat. Many executives believe that, eventually, there will be only two kinds of companies: those that are AI companies and those that are irrelevant. This mindset is driving leadership teams to treat AI as a strategic priority. In fact, half of organizations in 2024 said their AI push was being driven directly by CEO and top leadership pressure. That top-down impetus remains strong in 2025, though the ownership of AI projects is shifting internally, with CIOs increasingly taking the helm of AI initiatives.
The Readiness Gap Persists
Despite greater adoption, the fundamental readiness gap highlighted by Cisco hasn’t vanished overnight. Most companies are still struggling to connect pilot successes to scaled, organization-wide impact. Even though nearly all companies plan to increase AI investments, only a small fraction of leaders would call their firms “AI mature,” meaning AI is fully integrated and delivering significant business value. In 2025, business leaders still face the challenge Cisco identified: how to rapidly improve their strategic and operational readiness for AI so that urgency and execution finally align.
Strategy and Investment: From Planning to Execution
Clear AI Strategy as a Differentiator
One of the six pillars Cisco measured was Strategy, and the index showed mixed progress on this front. Fewer than two-thirds of organizations had a clear AI strategy in place by late 2024. Leaders overwhelmingly agree that AI cannot be deployed effectively without a plan – yet many firms entered the AI race ad hoc. Security use cases were a common starting point, with cybersecurity ranking as the top priority for AI deployment. Still, having some use cases is not the same as having an enterprise-wide AI roadmap. The most prepared firms distinguished themselves by aligning AI projects with defined strategic goals and setting aside a dedicated budget for AI initiatives.
Rising Budgets and Bets
Even without perfect strategies, companies are doubling down on AI investments. In Cisco’s survey, half of businesses had already earmarked 10–30% of their IT budgets for AI projects in 2024. Looking ahead, respondents anticipated about 30% of IT spending would go to AI within five years, nearly double current levels. This trend is visible in 2025, as large enterprises are pouring significant capital into AI, with many planning to invest tens or even hundreds of millions of dollars in generative AI over the next year. Clearly, the boardroom mandate is to invest in AI now or risk falling behind.
Lukewarm ROI, Long-Term Optimism
A striking insight from Cisco’s 2024 report was that many AI initiatives had yet to meet expectations. Close to half of companies said their AI implementations in top-priority areas fell short of hoped-for results. Early returns on AI investments were described as “lukewarm.” However, this reality check has not deterred spending – instead, it has fostered a longer-term view. Many organizations believe the impact of their AI investments will surpass expectations after five years. In other words, leaders are willing to weather some early disappointments, confident that AI’s transformative value will materialize with time and experience.
Infrastructure and Technology: Scaling Up for AI Demands
Infrastructure Strains in 2024
One of the most eye-opening declines in Cisco’s readiness index was in the Infrastructure pillar. Between 2023 and 2024, infrastructure readiness dropped significantly, indicating that many IT environments were not keeping pace with AI’s computational and performance needs. The report cited gaps in compute capacity, data center network performance, and even cybersecurity preparedness for AI workloads. Only a small percentage of companies reported having the necessary GPU and specialized hardware resources to meet current and future AI demands.
Bridging the Compute Gap
In 2025, businesses are addressing these infrastructure challenges with urgency. The scramble for GPUs that defined 2023’s AI boom has led many companies to explore alternative paths: cloud-based AI services, custom AI chips, and more efficient model architectures. Cloud providers have heavily marketed their AI infrastructure as a solution, allowing companies to rent high-performance AI compute power rather than building everything in-house. Nonetheless, large enterprises are also investing in expanding their own data center capabilities for AI.
Emerging Technologies Push the Limits
The pace of AI innovation is further testing enterprise tech environments. New AI agents – software bots that can autonomously execute tasks or make decisions – are emerging in pilot programs. Over half of large organizations are now exploring or experimenting with AI agents, though only a small percentage have actually deployed them in production so far. These agents, which can schedule meetings, handle customer inquiries, or even manage aspects of IT operations, often need real-time processing and integration with multiple systems.
The 2025 Outlook: Closing the Readiness Gap
Comparing Cisco’s 2024 AI Readiness Index to the state of play in 2025 reveals both encouraging progress and persistent gaps. AI capabilities and adoption have leapt ahead – what was cutting-edge a year ago is quickly becoming standard practice. Organizations are deploying AI in more business areas, seeing tangible benefits like cost reductions and new revenue streams, and the fear of missing out on AI is driving bold action. However, the foundational work to truly capitalize on AI is still a work in progress for most.
The key shifts from 2024 to 2025 that business leaders should heed when planning AI integration include:
- From exploration to execution: The era of tentative AI pilot projects is ending. Leaders are moving into full-scale implementation of AI solutions.
- Bigger bets on AI, but smarter ones: Budgets for AI are growing rapidly, but organizations are balancing investment with governance.
- Infrastructure and data foundations as strategic assets: Many organizations are prioritizing AI-ready infrastructure and improving data governance.
- Navigating compliance and ethics is non-negotiable: AI regulations are tightening, making responsible AI a requirement, not an option.
- Empowering people to drive AI: A combination of upskilling and cultural readiness is key to ensuring smooth AI adoption.
Ultimately, AI success in 2025 is no longer just about having AI – it’s about being truly ready for AI. With the right preparation, companies can turn the hype into lasting results and navigate the new AI-powered economy with confidence.
- Sources:
- Cisco, 2024 AI Readiness Index (Report findings) investor.cisco.com
- McKinsey, State of AI 2024 (Global survey results) mckinsey.com
- KPMG, 2025 AI Pulse Survey (Executive insights on investments and leadership)kpmg.com
- World Economic Forum, Why corporate integrity is key to AI’s future (Ethical AI statistics) weforum.org
- DLA Piper, EU AI Act Updates (Regulatory timeline and requirements) dlapiper.com
- Deloitte, Leadership & AI Governance Survey 2024 (Workforce training stats)www2.deloitte.com
