Almost one-third of organizations are using some form of AI, with 43% reporting that their rollout accelerated as a result of the pandemic. That’s according to a new Morning Consult study commissioned by IBM, which revealed that while AI adoption was flat over the last year, momentum shifted with changing business needs.
IBM’s Global AI Adoption Index found that enterprise deployment of AI was flat compared with 2020, but that businesses plan “significant investments” in AI throughout the coming year. Adoption is being driven both by pressures and opportunities, from the pandemic to technological advances that make AI more accessible. Indeed, a third of companies told IBM that they plan to invest in AI skills and solutions over the next 12 months.
Of the categories of AI that organizations are adopting, natural language processing (NLP) is at the forefront. Almost half of businesses say that they’re using apps powered by NLP and one in four organizations plan to use the technology over the course of 2021. Customer service is the top use case, with 52% of companies deploying or considering deploying NLP for it, according to IBM.
Even before the pandemic, autonomous agents were on the way to becoming the rule rather than the exception — partly because consumers prefer it that way. According to research published last year by Vonage subsidiary NewVoiceMedia, 25% of people prefer to have their queries handled by a chatbot or other self-service alternative. And Salesforce says roughly 69% of consumers choose chatbots for quick communication with brands.
Respondents to the survey also said that the pandemic changed how they use automation. Eighty percent of companies said that they’re using automation software or plan to use it in the next 12 months, and for over 30% of organizations, the pandemic influenced their decision. Others told IBM that they’ve explored new applications of the technology to make themselves more resilient, like helping to automate the resolution of IT incidents.
Barriers to adoption
According to IBM, even companies adopting or planning to adopt AI face challenges, like limited AI expertise and a lack of tools for developing AI models. For example, while over 90% of businesses told IBM that their ability to explain how AI arrived at a decision is important, more than half cited problems in getting there, including biased data.
IBM’s findings agree with a recent Boston Consulting Group survey of 1,000 enterprises, which found that less than half that achieved AI at scale had fully mature, “responsible” AI implementations. The lagging adoption of responsible AI belies the value that these practices can bring to bear. A study by Capgemini found that customers and employees will reward organizations that practice ethical AI with greater loyalty, more business, and even a willingness to advocate for them — and in turn, punish those that don’t.
Laments over the AI talent shortage have also become a familiar refrain from enterprises. O’Reilly’s 2021 AI Adoption in the Enterprise paper found that a lack of skilled people and difficulty hiring topped the list of challenges in AI, with 19% of respondents citing it as a “significant” barrier. And in 2018, Element AI estimated that of the 22,000 Ph.D.-educated researchers globally working on AI development and research, only 25% are “well-versed enough in the technology to work with teams to take it from research to application.”
The ability to access data anywhere is increasingly key to responsible, successful AI deployments, IBM asserts. Over 60% of global IT professionals draw from more than 20 different data sources to inform their AI, according to the survey. And almost 90% of IT pros say that being able to run their AI projects wherever the data resides is critical.
“As organizations move to a post-pandemic world, data from IBM’s Global AI Adoption Index 2021 underscores a major uptick in AI investment,” IBM SVP Rob Thomas said in a press release. “A large majority of those investments continue to be focused on the three key capabilities that define AI for business – automating IT and processes, building trust in AI outcomes, and understanding the language of business. We believe these investments will continue to accelerate rapidly as customers look for new, innovative ways to drive their digital transformations by taking advantage of hybrid cloud and AI.”
Still, IDC predicts that worldwide spending on cognitive and AI systems will reach $77.6 billion in 2022, up from $24 billion in revenue last year. Gartner agrees: In a recent survey of executives from thousands of businesses worldwide, it found that AI implementation grew a whopping 270% in the past four years and 37% in the past year alone.
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