Cisco Launches New Research, Highlighting Seismic Gap in Companies' Preparedness for AI
A mere 14% of organizations
globally are fully prepared to deploy and leverage Artificial Intelligence
(AI)-powered technologies, according to Cisco's inaugural AI Readiness Index released. The Index, which surveyed over 8,000 global
companies, was developed in response to the accelerating adoption of AI, a
generational shift that is impacting almost every area of business and daily
life. The report highlights companies' preparedness to utilize and deploy AI,
showcasing critical gaps across key business pillars and infrastructures that
pose serious risks for the near future.
The new research
finds 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, 81% of respondents admit that this is due to data existing
in silos across their organizations.
However, there is
also positive news. Findings from the Index revealed that companies are taking
many proactive measures to prepare for an AI-centric future. When it came to
building AI strategies, almost one-third of respondents were categorized as
Pacesetters (fully prepared), which indicates a significant level of focus by
C-Suite executives and IT leadership. This could be driven by the fact that
most (97%) respondents said the urgency to deploy AI technologies in their
organization has increased in the past six months, with IT infrastructure and
cybersecurity reported as the top priority areas for AI deployments.
"The race to
AI Readiness is on, with organizations under intense pressure to shift from
strategic planning to execution mode in order to capitalize on the
transformative potential that AI represents," said Liz Centoni, Executive
Vice President and General Manager, Applications and Chief Strategy Officer,
Cisco. "To realize the benefit of AI-powered products and services,
companies need solutions that secure and observe their AI models and toolchains
to ensure performance, secure sensitive data and systems, and deliver
trustworthy and responsible AI outcomes."
Key
Findings
Alongside the stark
finding that overall, only 14% of companies are Pacesetters (fully prepared),
the research found that more than half (52%) of companies globally are
considered Laggards (unprepared) at 4%, or Followers (limited preparedness) at
48%. Some of the most significant findings include:
· URGENCY: One
year maximum before companies start to see negative business impacts. 61% of respondents believe they have a maximum of one year to
implement an AI strategy before their organization begins to incur significant
negative business impact.
· STRATEGY :
Step one is strategy, and organizations are well on their way. 73% of organizations benchmarked as either Pacesetters or Chasers, and
only 4% were found to be Laggards. Additionally, 95% of organizations 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
are not equipped to meet AI workloads. 95% of
businesses are aware that AI will increase infrastructure workloads, but only
17% of organizations have networks that are fully flexible to handle this
complexity. 23% of companies 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, more than
three-quarters of companies will require further data center graphics
processing units (GPUs) to support current and future AI workloads. In addition,
30% say the latency and throughput of their network is not optimal or
sub-optimal, and 48% agree that they need further improvements on this front to
cater to future needs.
· DATA: Organizations
cannot neglect the importance of having data 'AI-ready.' While data serves as the backbone needed for AI operations, it is also
the area where readiness is the weakest, with the greatest number of Laggards
(17%) compared to other pillars. 81% of all respondents claim some degree of
siloed or fragmented data in their organization. This poses a critical
challenge as the complexity of integrating data that resides in various sources
and making it available for AI implications can impact the ability to leverage
the full potential of these applications.
· TALENT: T here is a significant mismatch in leadership and employee
expectations with respect to AI. Boards and Leadership Teams
are the most likely to embrace the changes brought about by AI, with 82% of
both groups 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 (31%) of
organizations report employees are limited in their willingness to adopt AI or
outright resistant. The need for AI skills reveals
a new-age digital divide. While 90% of respondents said they
have invested in upleveling existing employee skillsets, 29% expressed doubt
about the availability of sufficiently skilled talent.
· GOVERNANCE: AI
policy adoption's slow start. 76% of
organizations report not having comprehensive AI 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 only 21% have comprehensive change
management plans for widespread AI adoption. 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. Nearly eight out of 10 (79%) say their organization is
embracing AI with a moderate to high level of urgency. Only 2% said they were
resistant to change.
Cisco
AI Readiness Index
The new 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' 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).
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