Cisco's 2024 AI Readiness Index: Urgency Rises, Readiness Falls
Rhea-AI Summary
Cisco's 2024 AI Readiness Index reveals a widening gap between AI deployment urgency and organizational readiness. While 98% of companies report increased urgency to deploy AI, only 13% are fully prepared to implement their AI strategies, down from 14% last year. The study, involving 8,000 organizations, shows that 85% believe they have less than 18 months to demonstrate AI impact. Key infrastructure challenges include only 21% having necessary GPUs for AI demands and 30% having adequate data protection capabilities. Companies plan to allocate 30% of IT budgets to AI in the next five years, despite current implementations falling short of expectations.
Positive
- Companies plan to double AI investment to 30% of IT budgets in next 5 years
- 42% of respondents achieved advanced security deployment for AI
- 40% report advanced infrastructure deployment readiness
Negative
- Overall AI readiness declined from 14% to 13% year-over-year
- Only 21% have necessary GPUs for current and future AI demands
- Only 30% have adequate data protection capabilities for AI
- 80% report data preprocessing inconsistencies for AI projects
- Board receptiveness to AI decreased from 82% to 66%
- 24% report insufficient in-house talent for AI deployment
News Market Reaction 1 Alert
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Second annual report shows the race to get AI right is on, with a critical focus on networking infrastructure
News Summary:
- Leaders feel the pressure;
98% report increased urgency to deliver on AI and85% believe they have less than 18 months to act. - Networks are not equipped to meet AI workloads; only
21% of companies report having the necessary GPUs to meet current and future AI demands. - Only
13% say they are fully ready to capture AI's potential – down from14% last year.
Most notably, the report highlights a huge chasm between the urgency companies feel to deploy AI and their readiness to do so. Nearly all companies (
"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."
Key Findings
Alongside the finding that only
- URGENCY: Companies feel they only have 18 months to showcase the impact of AI. Nearly all (
85% ) companies say they only have 18 months to start demonstrating the impact of AI. More than half (59% ) give it only 12 months. - STRATEGY: Companies agree that AI cannot be deployed effectively in an organization without a clear strategy. Cybersecurity is the top priority for AI deployment with
42% of respondents having achieved advanced security deployment. Infrastructure follows at40% , and data analysis and data management tied for third at39% . - INVESTMENT: Companies are doubling down on AI despite lukewarm results from current AI projects. In the next five years, respondents anticipate that roughly
30% of IT budgets will be dedicated to AI, nearly double what it is today. Close to half of companies say AI implementations across top priorities have fallen short of expectations this year, yet59% believe the impact from AI investments will surpass expectations after five years. - INFRASTRUCTURE: Networks are not equipped to meet AI workloads. The largest decline was in infrastructure readiness, with gaps in compute, data center network performance, and cybersecurity, amongst other areas. Only
21% of organizations have the necessary GPUs to meet current and future AI demands and30% have the capabilities to protect data in AI models with end–to–end encryption, security audits, continuous monitoring and instant threat response. - DATA: Companies report feeling less ready to manage data effectively for AI initiatives, compared to a year ago. Nearly a 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. - TALENT: A lack of skilled talent is a top challenge across infrastructure, data, and governance, underscoring the critical need for skilled professionals to drive AI initiatives. 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. Twenty-four percent of all respondents also say that there is not enough talent available in their sector with the right skillsets to address the growing demand for AI. - GOVERNANCE: Effective AI governance is more crucial than ever, yet respondents feel that it has become more difficult. When asked about the comprehensiveness of their organizations' AI policies and protocols,
31% of the organizations said they are highly comprehensive. Fifty-one percent of respondents identified "the lack of talent with expertise in AI governance, law and ethics in the market" as a challenge in improving their readiness from the governance perspective. - CULTURE: There has been a noticeable reduction in cultural readiness to embrace AI. A lack of receptiveness to AI's changes has contributed to the decline in cultural readiness: boards have become less receptive to embracing the transformative power of AI, with
66% of them being highly or moderately receptive, down from82% last year while30% of organizations report employees are limited in their willingness to adopt AI or are outright resistant.
Cisco AI Readiness Index:
The Cisco AI Readiness Index is conducted by an independent third-party and based on a double-blind survey of 7,985 senior business leaders, with responsibility for AI integration and deployment at organizations across 30 markets with 500 or more employees. The Index assessed respondents' AI readiness across six key pillars: strategy, infrastructure, data, talent, governance and culture.
Companies were examined on 49 different metrics across these six pillars to determine a readiness score for each, as well as an overall readiness score for the respondents' organization. Each indicator was assigned an individual weightage based on its relative importance to achieving readiness for the applicable pillar. Based on their overall score, Cisco has identified four groups at different levels of organizational readiness – Pacesetters (fully prepared), Chasers (moderately prepared), Followers (limited preparedness) and Laggards (unprepared).
Additional Resources:
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SOURCE Cisco Systems, Inc.