Just 17% of organisations in Asia Pacific, Japan, and Greater China (APJC) are fully prepared to deploy and leverage AI-powered technologies, according to Cisco’s inaugural AI Readiness Index*. The Index, which surveyed over 8,000 global companies, was developed in response to the accelerating adoption of AI. Carl Solder, CTO ANZ Cisco, noted that there has been much hype generated around Gen AI because "for the 1st time, foundational technology is directly in hands of end users. "The real impact comes from companies that leverage foundational technology to build products and services," he said.
The report highlights companies’ preparedness to utilise and deploy AI, and has uncovered critical gaps across key business pillars and infrastructures that pose serious risks for the near future.
The new research has found that while AI adoption has been slowly progressing for decades, the advancements in generative AI, coupled with public availability in the past year, are driving greater attention to the challenges,
changes and new possibilities posed by the technology. While 84% of respondents believe AI will have a
significant impact on their business operations, it also raises new issues around data privacy and security.
The Index findings show that companies experience the most challenges when it comes to leveraging AI alongside their data. In fact, 80% of respondents admit that this is due to data existing in silos across their organisations.
There is also positive news. Findings from the Index revealed that companies in APJC are taking many proactive measures to prepare for an AI-centric future. When it came to building AI strategies, 95% of organisations already have a robust AI strategy in place, or are in the process of developing one.
More than three quarters (76%) of organisations are classified as either Pacesetters or Chasers (fully/partially prepared), with 4% falling into the category of Laggards (not prepared). This indicates a significant level of focus by C-Suite executives and IT leadership, Cisco said. The company suggested that the findings could be driven by the fact that a majority of respondents (97%) said the urgency to deploy AI technologies in their organisation had increased in the past six months, with IT infrastructure and cybersecurity reported as the top priority areas for AI deployments.
“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,” said Liz Centoni, Executive VP and GM, Applications and Chief Strategy Officer, Cisco.
“Organisations also need to be able to observe with context how AI is being used to ensure ROI, security, and especially responsibility.”
Highlights of the report include:
Alongside the finding that 17% of companies are Pacesetters (fully prepared), the research found that 46% of companies in APJC are considered AI-unready: Laggards (unprepared) at 4% of the total, and Followers (limited preparedness) at 42%.
Six pillars govern AI readiness for business:
Urgency
Over two thirds (67%) of respondents in APJC believe they have a maximum of one year to implement an AI strategy before their organisation begins to incur significant negative business impact.
Strategy
Step one is strategy, and organisations are well on their way. More than three quarters (76%) of organisations are classified as either Pacesetters or Chasers (fully/partially prepared), with 4% falling into the category of Laggards (not prepared). Additionally, 95% of organisations already have a highly defined AI strategy in place or are in the process of developing one, which is a positive sign, but shows there is more to do.
Infrastructure
Networks aren’t equipped to meet AI workloads. Nearly all (95%) businesses globally are aware that AI will increase infrastructure workloads, but in APJC, only 34% of organisations consider their infrastructure highly scalable. Meanwhile half (51%) indicate that they have limited or no scalability at all when it comes to meeting new AI challenges within their current IT infrastructures. To accommodate AI’s increased power and computing demands, about three quarters (72%) of companies will require further data centre graphics processing units (GPUs) to support future AI workloads.
Data
Organisations cannot neglect the importance of having ‘AI-ready’ data. While data is the backbone needed for AI operations, it is also the area where readiness is the weakest, with the greatest number of Laggards (15%) compared to other pillars. Eight in 10 respondents claim some degree of siloed or fragmented data in their organisation. This poses a critical challenge as the complexity of integrating data that resides in various sources and making it available for AI applications can impact the ability to leverage the full potential of these applications.
Talent
Boards and leadership teams are the most likely to embrace the changes brought about by AI, with 82% and 84% respectively showing high or moderate receptiveness. However, there is more work to be done to engage middle management where 22% have either limited or no receptiveness to AI, and among employees where close to a third (29%) of organisations report employees are limited in their willingness to adopt AI or are outright resistant.
The need for AI skills reveals a digital divide. While 91% of respondents said they have invested in upskilling existing employees, 18% alluded to an emerging AI divide, expressing doubt about the availability of enough talent to upskill.
Governance
AI policy adoption has had a slow start. Nearly two thirds (65%) of organisations report not having comprehensive policies in place, an area that must be addressed as companies consider and govern all the factors that present a risk in eroding confidence and trust. These factors include data privacy and data sovereignty, and the understanding of and compliance with global regulations. Additionally, close attention must be paid to the concepts of bias, fairness, and transparency in both data and algorithms.
Culture
Little preparation, but high motivation to make a priority: this pillar had the lowest number of Pacesetters (9%) compared to other categories driven largely by the fact that 18% of companies have not established change management plans yet and of those that have, 63% are still in progress.
C-Suite executives are the most receptive to embracing internal AI changes and must take the lead in developing comprehensive plans and communicating them clearly to middle management and employees who have relatively lower rates of acceptance. The good news is that motivation is high. More than eight out of 10 (81%) said their organisation is embracing AI with a moderate to high level of urgency. Only 1% said they were resistant to change.
Explore*The Cisco AI Readiness Index is based on a double-blind survey of 8,161 private sector business and IT leaders across 30 markets, conducted by an independent third-party surveying respondents from companies 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’ organisation. 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 identified four groups at different levels of organisational readiness – Pacesetters (fully prepared), Chasers (moderately prepared), Followers (limited preparedness), and Laggards (unprepared).
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