The AI Economy: How Prepared Are You for AI?

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The AI Scramble

At the speed at which artificial intelligence is moving today, companies believe time is running out to take advantage of its capabilities. There’s one problem: They need more time to prepare for AI. In its second annual AI Readiness Index, Cisco finds a gap between the urgency organizations feel and how ready they are.

Nearly 8,000 senior business leaders participated in this year’s survey, and 85 percent believe they have just 18 months to implement their AI strategies before facing disruption. However, fewer companies feel prepared for the technology, with only 13 percent expressing readiness—down from 14 percent last year.

Why 18 months? The report only emphasizes that companies believe that’s how long they have before seeing negative impacts from not executing. And with the rapid pace of AI development, that duration feels generous.

According to Cisco, this state results from companies not investing enough in six critical areas, which it believes are vital to be “AI-ready.”

Strategy:

Having a clear strategy for using AI will lead to success, but organizations need to ensure that it’s effectively defined. Cisco recommends that companies continually monitor and reassess their strategy, ensure it has the support of executive leadership, and be committed to the long-term vision.

The AI Readiness Index also found that companies will continue to invest dollars in AI projects despite current efforts’ “lukewarm results.” Respondents state that they will allocate roughly 30 percent of their IT budget to AI in the next five years, doubling what it is today. Though it might feel counterintuitive—nearly 50 percent say AI implementations have “fallen short of expectations this year”—59 percent believe their investment will surpass expectations after five years.

Infrastructure:

Companies need to have the proper networks in place to handle AI workloads. Cisco reports that infrastructure readiness declined significantly this year, with gaps emerging in compute, data center network performance, and cybersecurity. It’s believed that only 21 percent of companies have the GPUs needed to meet their AI demand, and 30 percent have the capabilities to protect the infrastructure.

Cisco recommends that organizations invest in “scalable and adaptive infrastructure to handle AI computational demands” and embrace new technologies that improve cloud efficiency and AI deployment speeds.

Data:

Your AI will only work effectively if the data used to train the models is good. Nearly a third of companies report they’re ready from a data perspective to “adapt, deploy, and fully leverage AI technologies.” An overwhelming majority (80 percent) claim they’ve experienced inconsistencies or shortcomings in the pre-training process—a similar percentage from the year prior.

To address this, Cisco suggests companies take advantage of advanced data integration and management tools to “break down data silos and ensure seamless data flow across the organization.”

Governance:

Thirty-one percent of companies say their AI policies and protocols are “highly comprehensive.” However, a plurality reported a “lack of talent with expertise in AI governance, law, and ethics in the market” within their organizations. The absence of subject matter experts can hinder a company’s AI readiness—avoid the inexperienced guiding the inexperienced.

The solution: Check in to review and update policies, strengthen data governance protocols, and actively promote ethical AI practices.

Culture:

Without a top-down embrace of AI, companies won’t be motivated to prepare themselves for what happens next. Cisco warns that boards have become less receptive to how the technology can transform their organizations. And if desk workers see upper management not caring about AI, why would they invest time in trying to use it to improve their productivity?

Cisco’s advice is unsurprising: Encourage AI adoption across departments, offer incentives, and reward workers for developing successful initiatives.

Talent:

Less than a quarter of respondents say there’s “not enough talent available in their sector with the right skillsets to address the growing demand for AI.” The same percentage report they’re understaffed. Without the appropriate staffing in place across infrastructure, data, and governance, companies could be doomed to fail before they even start implementing AI.

To counter this pattern, Cisco suggests that companies foster talent development, establish employee career paths, and encourage a culture of professional development learning.

“Eventually, there will be only two kinds of companies: Those that are AI companies and those that are irrelevant,” Jeetu Patel, Cisco’s Chief Product Officer, says in a statement. “AI is making us rethink power requirements, compute needs, high-performance connectivity inside and between data centers, data requirements, security, and more.”

He adds, “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.”

If you want to see how “ready” your company is, Cisco offers a self-assessment tool.

Click here to read the 2024 AI Readiness Index (PDF).

Related Reading:

Featured Image: An AI-generated image of a frustrated person consumed by time. Image credit: Adobe Firefly

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