The Next Economy will be driven by 10 key emerging technologies, underpinning them all is artificial intelligence. At this point, AI is blogged and reported about intensely on a day-to-day basis. Still, unless you’re in the trenches, we don’t know how companies are adopting the technology.
How are enterprises using AI? How much are they budgeting for AI? What tools are they using? How are they prioritizing their use cases? To answers these questions, O’Reilly launched three industry surveys to explore trends in AI, data, and cloud hosting adoption, with the research culminating in a new report: AI Adoption in the Enterprise—How Companies Are Planning and Prioritizing AI Projects in Practice.
As someone who is deep in the trenches of this space, specifically in emotion recognition technology, I can confirm many of the findings from the report. Here are 5 charts that caught my attention:
Most organizations are still evaluating AI
Though the report notes that 81% of respondents work for organizations that already use AI, most are in the evaluation stage.
The level of spending depends on the maturity of an organization
Those with a mature practice plan to spend on AI at a higher rate than less-mature companies.
Company culture and identifying use cases are common obstacles to AI adoption
“Lack of data” and a “lack of skilled people”remain key factors that slow down AI adoption within many organizations. Two other common obstacles pertain to organizational challenges: 23% cited “company culture” and 17% cited “difficulties identifying use cases.”
Machine learning experts and data scientists are in hot demand
More than half of all respondents signaled that their organizations were in need of machine learning experts and data scientists. Close to half (47%) cited the need for people who can identify use cases that lend themselves to AI solutions.
Organizations are mostly using AI for research and development
Half of all respondents belong to organizations that use AI for R&D projects, and one-third use it for customer service or IT. IT is an area that lends itself to (partial) automation; thus, many AI solutions already target IT systems.
From our experience at Netek, where we focus on emotion recognition, most of the companies we’ve had contact with are deep in evaluation mode, lack the skills and budget to really take any project forward. There’s also the “let’s wait until someone else has figured it out” before we do anything, which speaks to the cultural part of adoption.
Download and check out the full report, and let me know what you think about the findings. How is your organization adopting AI?