May 17, 2022

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Technology Forever

New International Rackspace Engineering Study Uncovers Common Synthetic Intelligence and Machine Learning Information Gap

SAN ANTONIO, Jan. 28, 2021 (Globe NEWSWIRE) — Rackspace Technology™ (NASDAQ: RXT), a major close-to-conclude, multicloud engineering methods company these days announced the final results of a worldwide survey that reveals that the vast majority of companies globally absence the inner methods to support crucial artificial intelligence (AI) and device learning (ML) initiatives.

The study, “Are Organizations Succeeding at AI and ML?” was done in the Americas, APJ and EMEA locations of the earth, and indicates that whilst numerous corporations are eager to include AI and ML tactics into operations, they ordinarily absence the expertise and current infrastructure essential to carry out experienced and productive AI/ML applications.

This analyze shines a gentle on the battle to balance the prospective gains of AI and ML from the ongoing difficulties of getting AI/ML initiatives off the floor. Although some early adopters are by now viewing the advantages of these technologies, other individuals are nonetheless making an attempt to navigate common soreness details such as absence of interior expertise, outdated technological innovation stacks, inadequate details high quality or the inability to evaluate ROI.

Added essential findings of the report incorporate the next:

  • Businesses are continue to checking out how to employ mature AI/ML capabilities — A mere 17% of respondents report mature AI and ML capabilities with a product manufacturing facility framework in location. In addition, the the vast majority of respondents (82%) stated they are nevertheless discovering how to apply AI or battling to operationalize AI and ML styles.
  • AI/ML implementation fails often because of to absence of interior means — Far more than a person-3rd (34%) of respondents report artificial intelligence R&D initiatives that have been tested and deserted or failed. The failures underscore the complexities of building and functioning a productive AI and ML application. The major causes for failure contain absence of information excellent (34%), absence of experience inside of the organization (34%), absence of output prepared facts (31%), and improperly conceived strategy (31%).
  • Prosperous AI/ML implementation has clear added benefits for early adopters — As businesses look to the upcoming, IT and operations are the main places in which they plan on incorporating AI and ML capabilities. The facts reveals that corporations see AI and ML potential in a range of small business models, which includes IT (43%), operations (33%), customer support (32%), and finance (32%). More, companies that have properly implemented AI and ML plans report increased efficiency (33%) and improved client pleasure (32%) as the best added benefits.
  • Defining KPIs is critical to measuring AI/ML return on investment  Together with the issue of deploying AI and ML tasks arrives the issues of measurement. The major essential functionality indicators utilized to measure AI/ML achievements include financial gain margins (52%), revenue expansion (51%), data examination (46%), and client fulfillment/web promoter scores (46%).
  • Corporations transform to reliable associates — Many corporations are continue to figuring out no matter if they will construct inside AI/ML assistance or outsource it to a trusted spouse. But offered the superior risk of implementation failure, the vast majority of corporations (62%) are, to some diploma, doing work with an knowledgeable company to navigate the complexities of AI and ML enhancement.

“In nearly each sector, we’re seeing IT final decision-makers transform to synthetic intelligence and device discovering to improve effectiveness and client satisfaction,” said Tolga Tarhan, Main Know-how Officer at Rackspace Technology. “But right before diving headfirst into an AI/ML initiative, we recommend shoppers to clear their details and info processes — In other text, get the appropriate data into the right systems in a trusted and cost-efficient fashion. At Rackspace Technologies, we’re proud to supply the know-how and technique important to guarantee AI/ML initiatives shift further than the R&D stage and into initiatives with long-time period impacts.”&#13

To download the full report, please take a look at www.rackspace.com/address/succeeding-ai-ml.

Survey Methodology

Performed by Coleman Parkes Analysis in December 2020 and January 2021, the study is dependent on the responses of 1,870 IT selection-makers across producing, electronic native, economic expert services, retail, authorities/general public sector, and health care sectors in the Americas, Europe, Asia and the Middle East. The survey issues covered AI and ML adoption, usage, advantages, affect and upcoming options.

About Rackspace Engineering

Rackspace Technological know-how is a top conclude-to-conclude multicloud technological know-how companies business. We can style, create and run our customers’ cloud environments throughout all major technological know-how platforms, irrespective of engineering stack or deployment product. We partner with our shoppers at each individual stage of their cloud journey, enabling them to modernize applications, make new products and undertake ground breaking systems.&#13

Media Call
Natalie Silva
Rackspace Corporate Communications
[email protected]