New Global Rackspace Technology Study Uncovers Widespread Artificial Intelligence and Machine Learning Knowledge Gap
January 28 2021 - 10:05AM
Rackspace Technology™ (NASDAQ: RXT), a leading end-to-end,
multicloud technology solutions company today announced the results
of a global survey that reveals that the majority of organizations
globally lack the internal resources to support critical artificial
intelligence (AI) and machine learning (ML) initiatives.
The survey, “Are Organizations Succeeding at AI and ML?” was
conducted in the Americas, APJ and EMEA regions of the world, and
indicates that while many organizations are eager to incorporate AI
and ML tactics into operations, they typically lack the expertise
and existing infrastructure needed to implement mature and
successful AI/ML programs.
This study shines a light on the struggle to balance the
potential benefits of AI and ML against the ongoing challenges of
getting AI/ML initiatives off the ground. While some early adopters
are already seeing the benefits of these technologies, others are
still trying to navigate common pain points such as lack of
internal knowledge, outdated technology stacks, poor data quality
or the inability to measure ROI.
Additional key findings of the report include the following:
- Organizations are still exploring how to implement
mature AI/ML capabilities — A mere 17% of respondents
report mature AI and ML capabilities with a model factory framework
in place. In addition, the majority of respondents (82%) said they
are still exploring how to implement AI or struggling to
operationalize AI and ML models.
- AI/ML implementation fails often due to lack of
internal resources — More than one-third (34%) of
respondents report artificial intelligence R&D initiatives that
have been tested and abandoned or failed. The failures underscore
the complexities of building and running a productive AI and ML
program. The top causes for failure include lack of data quality
(34%), lack of expertise within the organization (34%), lack of
production ready data (31%), and poorly conceived strategy
(31%).
- Successful AI/ML implementation has clear benefits for
early adopters — As organizations look to the future, IT
and operations are the leading areas where they plan on adding AI
and ML capabilities. The data reveals that organizations see AI and
ML potential in a variety of business units, including IT (43%),
operations (33%), customer service (32%), and finance (32%).
Further, organizations that have successfully implemented AI and ML
programs report increased productivity (33%) and improved customer
satisfaction (32%) as the top benefits.
- Defining KPIs is critical to measuring AI/ML return on
investment — Along with the
difficulty of deploying AI and ML projects comes the difficulty of
measurement. The top key performance indicators used to measure
AI/ML success include profit margins (52%), revenue growth (51%),
data analysis (46%), and customer satisfaction/net promoter scores
(46%).
- Organizations turn to trusted partners — Many
organizations are still determining whether they will build
internal AI/ML support or outsource it to a trusted partner. But
given the high risk of implementation failure, the majority of
organizations (62%) are, to some degree, working with an
experienced provider to navigate the complexities of AI and ML
development.
“In nearly every industry, we’re seeing IT decision-makers turn
to artificial intelligence and machine learning to improve
efficiency and customer satisfaction,” said Tolga Tarhan, Chief
Technology Officer at Rackspace Technology. “But before diving
headfirst into an AI/ML initiative, we advise customers to clean
their data and data processes — In other words, get the right data
into the right systems in a reliable and cost-effective manner. At
Rackspace Technology, we’re proud to provide the expertise and
strategy necessary to ensure AI/ML projects move beyond the R&D
stage and into initiatives with long-term impacts.”
To download the full report, please visit
www.rackspace.com/solve/succeeding-ai-ml.
Survey Methodology
Conducted by Coleman Parkes Research in December 2020 and
January 2021, the survey is based on the responses of 1,870 IT
decision-makers across manufacturing, digital native, financial
services, retail, government/public sector, and healthcare sectors
in the Americas, Europe, Asia and the Middle East. The survey
questions covered AI and ML adoption, usage, benefits, impact and
future plans.
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.
Media ContactNatalie SilvaRackspace Corporate
Communicationspublicrelations@rackspace.com
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