International Business Machines Inc. (NYSE: IBM) just released the results of its annual survey in a report titled Global AI Adoption Index 2021 that revealed how the COVID-19 pandemic has accelerated the adoption of Artificial Intelligence (AI).
Major findings
Amongst the major findings of the report, the survey revealed that 43% of the companies are accelerating investments in AI coming out of the pandemic. And 90% of those companies are deploying resources to figure out how they are going to manage data across multiple cloud environments.
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Even though companies have been showing increased interest in AI, there still remain hurdles to adoption as 32% of the companies reported to struggle with figuring out how to make their data ready for AI.
The survey also revealed that 80 percent of the companies are already using automation software or plan to use this AI in the next 12 months. More than one in three organizations reported that the pandemic had an impact on their decision to deploy the technology.
Applications powered by natural language processing (NLP) have been at the forefront of AI adoption with almost half of businesses using NLP technology.
Top Use Cases
Rob Thomas, senior vice president of IBM’s Cloud and Data Platform, in an interview with CNBC said that the top five use cases for the adoption of AI have been AI operations, Customer Service, Employee Experience, regulatory compliance and financial planning & budgeting.
He also said that these use cases have applications across industries and AI adoption leads to quick deployment and hence, faster benefits. As an example, he shared that 100 companies were able to deploy AI tools for customer service applications within 30 days.
“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 businessâ€, said Rob Thomas.
Top barriers to AI Adoption
The survey determined that the top three barriers to AI adoption are limited AI expertise or knowledge, increasing data complexity and data silos, and lack of tools/platforms for developing AI models with 39%, 32% and 28% of the survey participants, respectively, citing those as barriers.
