According to the inaugural AI Readiness Index by Cisco (NASDAQ: CSCO), released today, only 14% of global organizations are fully ready to implement and utilize Artificial Intelligence (AI) technologies. This information was disclosed in SAN JOSE, California, on Nov. 14, 2023. The Index was developed in response to the significant shift in AI adoption across various sectors, impacting both business operations and daily life. It involved a survey of over 8,000 multinational corporations. The report emphasizes the readiness of businesses to adopt and integrate AI, highlighting crucial gaps in infrastructure and core business functions that may pose significant challenges in the near future.
Recent studies indicate a growing focus on the challenges, transformations, and emerging opportunities associated with AI technology, driven by advancements in Generative AI and increased accessibility. While 84% of respondents recognize the substantial impact of AI on their business operations, concerns regarding data security and privacy have also been raised. The Index findings reveal that businesses encounter the most significant obstacles when integrating AI into their workflows, with 81% of respondents attributing these challenges to data fragmentation across their organizations.
Despite these challenges, there are positive developments to note. The Index reports that companies are proactively preparing for an AI-centric future. Nearly one-third of respondents were classified as Pacesetters, indicating full readiness in developing AI strategies. This demonstrates a strong commitment from C-Suite executives and IT leadership. The majority of respondents (97%) acknowledge the increasing necessity of implementing AI technologies within their organizations, with a particular focus on IT infrastructure and cybersecurity as top priority areas for AI integration.
Liz Centoni, Executive Vice President, General Manager, Applications, and Chief Strategy Officer at Cisco, emphasized the urgency for organizations to transition from planning to execution in order to leverage the transformative potential of AI. Companies require solutions that can secure and monitor their AI models and toolchains to ensure efficiency, protect sensitive data and systems, and deliver reliable AI outcomes to fully realize the benefits of AI-driven products and services.
Key Findings from the Index include:
- URGENCY: Businesses must implement an AI strategy at least a year in advance to avoid negative impacts on the economy, as highlighted by 61% of respondents.
- STRATEGY: While progress has been made in developing AI strategies, there is still room for improvement, with only 4% of organizations identified as Laggards. 95% of businesses have or are in the process of developing a well-defined AI strategy.
- INFRASTRUCTURE: Despite the awareness of increased AI workloads, only 17% of organizations have fully adaptable networks to handle this complexity. Additional investments in data center GPUs are needed to support current and future AI workloads.
- DATA: Data readiness for AI operations remains a significant challenge, with 81% of respondents reporting fragmented or dispersed data within their organizations. This fragmentation hinders the full utilization of AI applications.
- ABILITY: Discrepancies exist in the acceptance of AI between management and employees. While Boards and Leadership Teams show high receptivity to AI changes, there is a need to engage middle management and employees more effectively.
- GOVERNANCE: Many organizations lack comprehensive AI policies, which are essential for addressing trust and compliance issues related to AI implementation.
- CULTURE: While enthusiasm for AI adoption is high, detailed change management strategies are needed to ensure successful integration throughout the organization.
The Cisco AI Readiness Index is based on a comprehensive study involving 8,161 IT and business leaders from 30 different industries. The evaluation considers six key pillars—strategy, infrastructure, data, skills, governance, and culture—to assess organizations’ readiness for AI implementation. The study categorizes businesses into four groups based on their readiness levels: Pacesetters, Chasers, Followers, and Laggards.
