Rackspace Technology® (NASDAQ: RXT), a leading end-to-end,
multicloud technology solutions company, today announced a new
research report that finds that while Artificial Intellegence and
Machine Learning (AI/ML) are on nearly every organization's radar
much work remains to be done to tap their full potential. Rackspace
Technology polled 1,870 global IT leaders, across industries,
including manufacturing, financial services, retail, government,
and healthcare to understand the dynamics of AI/ML uptake.
While 62% of respondents said that AI/ML is a high priority for
their organization, and 70% of all respondents reported positive
impacts of on brand awareness and reputation, as well as revenue
generation and expense reduction, 36% agreed that measuring and
proving the technologies’ business value remains a challenge.
“As AI/ML budgets continue to increase, we are seeing projects
proliferate across more areas of the organization, and it’s clear
that the AI/ML is advancing in its importance and visibility,” said
Jeff DeVerter, Chief Technology Evangelist, Rackspace Technology.
“At the same time, the research makes clear that many organizations
still struggle with getting stakeholder buy-in, addressing issues
of data quality, and finding the skills, resources and talent to
take advantage of the AI/ML’s full potential.”
According to the report – AI/ML is a Top Priority for
Businesses, but are They Realizing Its Value? – AI/ML ranks among
the top two most important strategic technologies for
organizations, alongside cybersecurity. 72% of respondents say they
are employing AI/ML as part of their business strategy, IT strategy
or both, while 69% of respondents are allocating between 6% and 10%
of their budget to AI/ML projects. This compares to a reported
spend (as a percentage of overall budget) of between 1% and 10% in
last year’s survey.
AI/ML Projects are Accelerating
AI/ML are being used by organizations in an increasingly wide
variety of contexts, including improving the speed and efficiency
of processes (52%), personalizing content and understanding
customers (44%), increasing revenue, gaining competitive edge and
predicting performance (42%), and understanding marketing
effectiveness (36%).
In an indication of the increasing maturity of the technologies,
66% of respondents said their AI/ML projects have gone past the
experimentation stage and are now either in the
"optimizing/innovating" or "formalizing" states of implementation.
Most organizations are also citing a wider range of use cases,
including computer vision applications, automated content
moderation, customer relationship management, and biomedical
applications.
Progress, and Challenges
With regard to AI/ML adoption, 33% of respondents cite
difficulties aligning AI/ML strategies to the business – a
year-over-year increase of 10%. In addition, the cost of
implementation rose from 26% to 33%, while 31% of respondents of
nascent AI/ML technologies as a barrier, representing an increase
of 13%.
“The fact that many organizations are having trouble aligning
AI/ML strategies to the business and navigating the plethora of new
tools available indicates that projects are often falling victim to
poor strategy,” added DeVerter. “Garnering support from the right
stakeholders, coming to consensus on deliverables, understanding
the resources necessary to get there, and setting clear milestones
are critical components to keeping projects on track and seeing the
desired return on investment.”
Organizational Understanding
From a talent perspective, more than half of respondents said
they have necessary AI/ML skills within their organization. At the
same time, more than half of all respondents say that bolstering
internal skills/hired talent and improving both internal and
external training are on their agenda.
Comparing departments, 69% of respondents say IT staff grasp
AI/ML benefits while 43% say that operations, R&D, customer
service, senior management and boards understand the technologies.
Sales, HR and marketing departments are considered by respondents
to be the least AI/ML-savvy.
For more information on the trends that will shape AI/ML in 2022
and to download a copy of the full report, visit
https://www.rackspace.com/lp/solve-ai-ml-research-report-2022
Survey Methodology
The survey was conducted by Coleman Parkes Research in September
2021. Findings are based on the responses of 1,870 IT
decision-makers across manufacturing/logistics, retail,
hospitality/travel, energy, healthcare/pharma/biomedical,
government, media/entertainment and financial service sectors in
the Americas, Europe, Asia and the Middle East. Most of the
companies/organizations polled were founded before the year 2000,
have from 101 to 999 employees, and an annual revenue between $50m
and $1b. They also have anywhere from two to 15 employees dedicated
to cybersecurity and they spend 5% to 15% of their IT budget on
cybersecurity.
About Rackspace Technology
Rackspace Technology is a leading end-to-end multicloud
technology services company. We can design, build and operate our
customers’ cloud environments across all major technology
platforms, irrespective of technology stack or deployment model. We
partner with our customers at every stage of their cloud journey,
enabling them to modernize applications, build new products and
adopt innovative technologies.
Contact:
Natalie Silva
publicrelations@rackspace.com
An infographic accompanying this announcement is
available
at: https://ml.globenewswire.com/Resource/Download/0a1a3599-4626-4298-909f-23842b537db9
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