Capgemini: 53% of AI initiatives in large organizations move past pilot stage
As COVID-19 widens the gap between AI-at-scale leaders and struggling organizations
As COVID-19 widens the gap between AI-at-scale leaders and struggling organizations
More than half of existing AI initiatives in large organizations have moved beyond pilots and proofs of concept, according to Capgemini Research Institute
Although growing, scaling AI deployments across the enterprise has been challenging.
While 47% of organizations have launched AI pilots or proofs of concept, they are not yet deployed in production and fewer than half (40%) have deployed multiple use cases in production, even on a limited scale.
The study is based on a survey of 950 businesses in 11 countries, all with at least $1 billion in annual revenue.
Early bird gets the worm
Of organizations with AI initiatives, just 13% have rolled out multiple AI applications across numerous teams.
The majority (70%) of respondents said the top challenge facing their organizations is the lack of senior talent, followed by the lack of change management process (65%), and the lack of strong governance models for achieving scale (63%), according to Capgemini.
COVID-19 has had an impact on AI efforts in the enterprise, primarily widening the gap between AI-at-scale leaders and struggling organizations.
For example, 78% of AI-at-scale leaders are moving their AI initiatives ahead at the same pace as before the pandemic, and 21% have increased the pace of deployment.
In contrast, 43% of struggling organizations have pulled investments form AI initiatives with low potential impact due to high business uncertainly, and 16% suspended all AI initiatives. Despite the recent economic challenges, 40% of organizations in this group are progressing with their AI initiatives as planned, and 2% are quickening the pace of deployments.
Life sciences has emerged as the leading sector for AI initiatives, most notably due to the significant AI bets made by pharma companies, including drug development, research and development, and diagnosis.
In diagnostics, life since companies are using image recognition software with remote monitoring of patients, as one example.
More than a quarter (27%) of life science companies have successfully deployed AI use cases in production and continue to scale throughout multiple business teams, according to the study.
Following life sciences, retail, consumer products, and automotive organizations have deployed the most use cases in production.
Amid the economic uncertainty, businesses are focusing their efforts on projects with the most potential for success. About half (51%) of survey respondents have suspended AI initiatives or pulled investments with low potential impact.
In companies leading in AI deployments, 83% said IT and business together are the main drivers of their AI initiatives.
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