Cisco’s inaugural AI Readiness Index exposes a stark reality – a mere 14 percent of organizations worldwide are fully prepared to harness the potential of AI-powered technologies. The survey, encompassing insights from over 8,000 global companies, underscores the urgent need for heightened AI readiness in the face of a technological revolution that is reshaping industries and daily life.
Despite 84 percent of respondents acknowledging the profound impact AI will have on their business operations, the findings shed light on pressing issues concerning data privacy and security. The survey reveals that a staggering 81 percent of organizations grapple with challenges stemming from siloed data, hindering the seamless integration of AI technologies.
On a positive note, nearly a third of respondents emerge as ‘Pacesetters,’ demonstrating full preparedness in deploying AI. This suggests a substantial commitment from C-Suite executives and IT leadership, potentially fueled by the increasing urgency reported by 97 percent of respondents to deploy AI technologies in the past six months. Notably, IT infrastructure and cybersecurity emerge as the top priorities for organizations embarking on AI deployments.
Liz Centoni, Executive Vice President and General Manager, Applications, and Chief Strategy Officer at Cisco, warns, “As companies rush to deploy AI solutions, they must assess where investments are needed to ensure their infrastructure can best support the demands of AI workloads.” Centoni emphasizes the importance of contextual observation to guarantee ROI, security, and responsibility in AI usage.
Among the survey’s key findings, 61 percent of respondents believe they have a maximum of one year to implement an AI strategy before facing significant negative business impacts. Additionally, while 95 percent of businesses acknowledge that AI will increase infrastructure workloads, only a meager 17 percent boast fully flexible networks capable of handling the ensuing complexity. Alarmingly, 23 percent of companies admit to limited or no scalability in meeting new AI challenges within their existing IT infrastructures.
