As with other areas of the economy (chips, workforce), demand isn’t the problem in the AI market, it’s supply: supply of knowledge and skills, and supply of technology. IBM this morning released the results of its Global AI Adoption Index 2021 study, which the company said shows that business adoption of AI slowed over the last year even as “the need for AI has been accelerated by changing business needs due to the global pandemic.” The major barriers to AI adoption: Limited AI expertise or knowledge, data complexity and data silos and lack of tools and platforms for building AI models. Another issue: explainability.
In short: more companies want to do more AI, but they lack the skills and technology to do it.
“Business adoption of AI slowed, but significant investments in AI are planned,” IBM said. “Almost a third of companies reported using AI in their business, similar to 2020 findings. Adoption is being driven by multiple pressures and opportunities businesses are facing, from the COVID-19 pandemic to advances in the technology that make it more accessible. A third of global IT professionals report their company plans to invest in both skills and AI solutions over the next 12 months.”
On the pandemic front, IBM said COVID-19 has accelerated how businesses are using automation: 80 percent of companies use automation software or plan to over the next year, and more than a third of organizations grew their use of automation during the pandemic.
The most aggressively adopted AI use case: natural language processing. Almost half of businesses surveyed by IBM use applications powered by NLP, and a quarter of businesses plan to use the technology over the next year. Customer service is the top NLP use case with 52 percent of global IT professionals reporting that their companies use, or are considering using, NLP solutions. It also was the use AI case IT professionals were most likely to report that the COVID-19 pandemic has increased their focus on, IBM said.
But AI adoption faces major barriers, the top of which are: Limited AI expertise or knowledge (39 percent), increasing data complexity and data silos (32 percent), and lack of tools/platforms for developing AI models (28 percent).
Trustworthiness and explainability of AI also are major issues. IBM said more than 90 percent of businesses using AI say the ability to explain how it arrived at a decision is critical. “While global businesses are now acutely aware of the importance of trustworthy AI, more than half of companies cite significant barriers in getting there including lack of skills, inflexible governance tools, biased data and more,” IBM said.
Data management also is a perennial challenge. “The ability to access data anywhere is key for increasing AI adoption,” IBM said. “The proliferation of data across the enterprise has resulted in over two thirds of global IT professionals drawing from more than 20 different data sources to inform their AI. Almost 90 percent of IT pros say being able to run their AI projects wherever the data resides is key to the technology’s adoption.”
All of this is of critical importance to companies because AI, done right, can deliver major competitive advantage. This is reflected in AI market sizing estimates, which in turn makes it important to technology vendors like IBM. “AI is the largest economic opportunity of our lifetime, estimated to contribute $16 trillion to GDP by 2030 and a new forecast from IDC is predicting worldwide AI revenues will surpass $300 billion in 2024 (and 80 percent of this driven by software),” IBM reported.
The annual findings are based on a survey 5,501 business leaders in 15 major markets. China (500), France (500), Germany (500), India (500), Italy (500), Latin America (1000 across Brazil, Mexico, Colombia, Argentina, Chile, Peru), Singapore (500), Spain (500), the United Kingdom (500), and United States (501). The polling was conducted online through Morning Consult’s proprietary network of online providers in April 2021. IBM said respondents were required to have significant insight or input into their firm’s IT decision-making.
