Growing AI Adoption Fuels Infrastructure Upgrades
A majority of companies participating in an annual industry survey report they are either using or “experimenting” with machine learning technology for enterprise applications ranging from cloud-based AI services to online shopping.
The AI adoption survey, "The Current and Future State of AI and Machine Learning 2020," released Tuesday (Nov. 3) by 451 Research also found that more than half of respondents said their current IT infrastructure must be upgraded in order to scale AI workloads. That finding portends a renewed wave of enterprise migration to public cloud services, the survey concludes.*
Text and natural language processing along with computer vision are seen by early adopters as general-purpose AI technologies. In the running also despite growing privacy concerns is facial recognition technology. (IBM announced this summer it would no longer sell facial recognition tools.)
Compared with last year, the percentage of corporate AI workloads and pilot projects jumped this year by roughly one-third, 451 Research reported. Twenty-nine percent of respondents moved machine learning applications to production while 28 percent reached the proof-of-concept stage.
“AI, though still a young technology in terms of enterprise adoption, is maturing rapidly and becoming an integral part of everyday experiences,” noted the adoption survey. AI “is already being implemented to improve and automate many business processes from data security to customer experience, and with millions of people now working remote, AI is being recognized by enterprises as a capable tool for workforce optimization and management.”
Machine learning adoption strategies vary. Nearly half of those companies polled favored application development using cloud-based AI services while 25 percent said they purchased applications with machine learning built in.
Indeed, software services and hosted applications were the most frequently cited environments supporting AI and machine workloads, followed by on-premise and hosted private clouds. Those trends are expected to continue over the next two years as prototype efforts move to production.
About one-third of respondents expect “moderate increases” in data volumes used for AI training and inference, with volumes for training more complex models running in the range 50 to 499 terabytes. (A small percentage said data volumes for training and inference exceeded 1 exabyte.)
Respondents were divided on the pandemic’s impact on their AI initiatives: Some said it would slow or halt development while a larger percentage said it would accelerate efforts to automate business processes or add intelligence to enterprise applications.
The financial services, energy, manufacturing and retail sectors (in that order) are expected to record the highest AI technology adoption rates in 2021. The survey found that 82 percent of financial services firms expect to increase new AI initiatives in response to the pandemic.
The survey also poses an intriguing question: Given growing enterprise adoption, why has no pure-play AI company emerged? The market analyst notes that AI services, applications and IT infrastructure generates substantial revenues for public cloud vendors, “but AI is nowhere near being the largest contributor to revenues in any of those divisions.”
Instead, the first pure-play AI enterprises might be Chinese. For example, 451 Research notes that Chinese computer vision specialist SenseTime has so far raised at least $1.6 billion in venture funding. Add to that China’s long-term investment strategy designed to lead the world in AI technology development by 2030.
The market analyst said its most recent AI adoption report updates earlier versions released in February and August of this year.
* The report, written by Nick Patience, an AI applications and platforms analyst, and Rachel Dunning, a research associate, is an annual overview of the market for AI and machine learning, according to 451 Research. The latest survey uses research conducted by its authors over the last year, and includes data from two previous 451 reports – the Voice of the Enterprise: AI & Machine Learning, Use Cases and AI Infrastructure surveys published in February 2020 and August 2020, according to the research firm. The survey data used in the February 2020 report was gathered from 1,000 online respondents from November to December of 2019. Fifty-two percent of the respondents were from the US, 17% from UK, 16% from France, and 15% from Germany. Fifty-one percent were in IT, while 49% were from other parts of the business. Twelve percent were in manufacturing, 11% in financial services, 11%, in healthcare, 11%, in tech, 8% in retail, 6% in energy and 5% in government. Thirty-one percent have 999 to 10,000 employees. Twenty-nine percent have revenue between $100 million to $999 million, while 18% have revenue from $1 billion to $10 billion. The survey data gathered from the May 2020 report included information from 704 online respondents, 71% from the US and 21% from the UK. Forty-nine percent of those respondents were in IT, while 51% were in other parts of the businesses. Sixteen percent of the respondents were in manufacturing, 15% were in software and IT services 15% in healthcare, 10% in education and training, 8% in financial services, 7% in construction, 6% in retail, 4% in business services, 4% in government, 4% in transportation and 3% in telecommunications. Thirty percent of the respondents are from businesses with 250-999 employees. Twenty-nine percent have revenue of $10 million to $99 million, while 27% have revenue from $100 million to $999 million.