Cisco AI Readiness Index

Intentions outpacing abilities

Introduction Measuring Readiness Global Readiness Learn More Methodology

The acceleration of artificial intelligence is fundamentally changing our world. In a global survey of private sector professionals involved in AI integration and/or deployment, we found that:

It’s no surprise, then, that in the past six months,

As companies worldwide navigate the evolving AI landscape, the question remains: are they prepared to fully adopt, deploy, and harness the power of AI?

While planning is underway and intentions are good, organizations have more work to do considering only:

Businesses need to be AI-ready

Businesses need to be AI-ready in a way that is flexible, scalable, and provides industry-wide interoperability. Cisco’s AI Readiness Index measures the readiness of global companies to deploy AI solutions across six pillars:

Strategy

How clearly defined is an organization’s AI strategy, who owns it, and how is it being prioritized?

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Infrastructure

What is an organization’s compute power, network performance, cybersecurity capabilities, and readiness to support increased power consumption?

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Data

What is the quality and centralization of in-house data, the sophistication and scalability of analytics tools, the proficiency of staff in leveraging AI data sets and analytics tools, and the quality and reliability of external data?

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Governance

How and where is data being stored, processed, and evaluated for policy compliance?

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Talent

Do companies currently have adequate talent to match their AI goals, and what are the steps being taken to ensure proficiency?

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Culture

How receptive is each level of the company to the changes triggered by AI, and how are the possibilities that AI brings being communicated through change management?

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Strategy Infrastructure Data Governance Talent Culture

Strategy

95% of organizations have an AI strategy in place or under development, but not all deployment strategies are the same. The parts of the business and their prioritization among IT leaders is revealing of the rapid – and rapidly evolving – timeline of AI deployments:

Where are companies deploying AI?

#1

/

0%

IT Infrastructure

is the #1 area of the business intended for AI deployment, with 84% of IT professionals planning moderate or advanced deployments for infrastructure purposes.

#2

/

0%

Cybersecurity

is a close #2, with 83% planning moderate or advanced deployments.

Infrastructure

AI/ML deployments dramatically increase the number of needed, power-intensive GPUs: 77% of organizations will need more GPU resources to support AI workloads. The scale of the network is unprecedented. Organizational infrastructure must scale to support the tremendous amount of bandwidth AI models need to train, add new workloads, and accommodate the powerful inference solutions that appear in the market.

0%

of IT leaders believe AI will increase their infrastructure workloads.

However, only

13%

say their networks can scale to accommodate any AI computational needs.

Data

AI depends on data. It doesn’t work without the underlying data powering its functionality. However, the majority of respondents fell at the middle of the spectrum when it came to their data practices. A centralized, hygienic, sophisticated, and secure approach to data is crucial when it comes to AI readiness.

Not AI-ready

19% - Fully centralized data
22% - Efficient data access protocols and procedures

AI-ready

59% - Consistently or mostly pre-processed, clean, and ready-to-use data
69% - Well-integrated analytics, data sources, and AI platforms

Governance

While AI can benefit society, business, and economies; it also creates new challenges for customers, users, and other stakeholders. Because AI can automatically generate insights that influence critical decisions and actions, it’s imperative to implement clear governance over how AI-based solutions are developed, deployed, and operated.

Bias in AI is top-of-mind for many organizations; 95.5% of them have some mechanism in place to detect biases and ensure fairness in AI algorithms.

Talent

In a challenge to the notion that AI will replace jobs, the data reveals that AI can be a channel for worker growth. AI implementation demands new skills, and even companies who are well-resourced need more (or different) talent to be successful. A top priority for organizations across the globe is to build a future-ready AI workforce.

0%

of companies plan to invest in upskilling existing employees on AI

0%

say their current staff need guidance or significant training on planned AI technologies

Culture

79% of organizations see a moderate or high level of urgency to embrace AI; however, the willingness to adopt AI varies greatly depending on one’s level in the organization. Companies must create a dynamic conversation around the possibilities of AI—and how each role plays a part—to pave the path for willingness and engagement.

Receptive

82% - Board
82% - Leadership

Resistant

23% - Middle Management
31% - Employees

A look at global readiness

When it comes to global AI readiness, intentions might outpace abilities, as 86% of organizations worldwide are not fully ready to integrate AI into their businesses. Globally, respondents score highest for readiness in Strategy; plans, budgets and good intentions for AI implementation are taking the lead. However, scores trail significantly across other categories, and respondents’ scores are lowest for Culture and Data.

This indicates that companies are still wrestling with how to address AI across their organizations—not just from a technology perspective, but also among the humans who are ready (or not) to use that technology.

Find out how peers in your region, industry, and market compare when it comes to AI readiness:

Overall Strategy Infrastructure Data Governance Talent Culture

Global readiness

Pacesetters ?Chasers ?Followers ?Laggards ?

Pacesetters ?

Chasers ?

Followers ?

Laggards ?

The impact of AI readiness

AI is multifaceted, and it helps to have a trusted business partner that’s multifaceted as well — one to help bridge the gap from strategic vision to executing at scale. Organizations that have the capabilities to leverage AI’s full value will not only have a competitive edge but will also be perfectly aligned to thrive in the AI-dominated future.

Download full report See how you compare

Liz Centoni

EVP, Chief Strategy Officer and General Manager, Applications

Methodology

The Cisco AI Readiness Index is based on a double blind survey of 8,161 global private sector businesses and IT leaders involved in AI integration and/or deployments across 30 markets.

The research was carried out by an independent research company between September and October 2023.

Each company's scores were determined by their level of deployment and clarity in the six different pillars. These scores for each area were combined, taking into account the importance of each area, to create an overall score for each company in their respective markets.

The companies were placed in four stages of readiness based on their overall score:

Fully Prepared – Pacesetters
Companies that have a score higher than 86 (out of a maximum of 100)
Moderately Prepared – Chasers
Those with a score between 61 and 85
Limited Preparedness – Followers
Those with a score between 31 and 60
Unprepared - Laggards
Those with a score between 0 and 30