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January 10, 2024

IBM Report Suggests Early Adopters Driving Enterprise AI Adoption But Barriers to Adoption Remain

(StudioFI/Shutterstock)

The fourth IBM Global AI Adoption Index was released today. The report was compiled by an annual poll of 8,500+ IT professionals by Morning Consult and highlights the key trends in enterprise AI adoption around the globe.  

The year 2023 has been a breakout year for generative AI. Organizations are looking at different ways to deploy GenAI tools in their operations and solutions, however, the latest IBM data suggests that the number of large-sized enterprises that have actively deployed AI has remained steady at 44 percent. 

The number of organizations considering deploying AI or experimenting with the technology also remains steady at around 40 percent. However, 59 percent of the companies already exploring or deploying AI say that they have accelerated their rollouts and investment in AI. This shows growing commitment to and confidence in AI technology. 

Rob Thomas, Senior Vice President at IBM Software, shared that early adopters who overcame barriers to deploy AI are making further investments, and are getting benefits from AI. “More accessible AI tools, the drive for automation of key processes, and increasing amounts of AI embedded into off-the-shelf business applications are top factors driving the expansion of AI at the enterprise level.”

According to Thomas, the deployment of AI technically can have a quick and profound impact on certain business functions such as customer care, IT automation, and digital labor. Thomas remains confident that as organizations overcome the challenges of skills gap and data complexity, there will be greater AI adoption across enterprises. 

Based on the results of the IBM study, Businesses in the UK, Australia, and Canada are least likely to increase their investment in AI or accelerate the rollout of AI initiatives. The countries leading enterprise AI adoption and investment include China, India, Singapore, and the United Arab Emirates. 

According to the IBM study, the biggest barriers to deploying AI have been the lack of AI skills and expertise (33 percent), high level of data complexity (25 percent), and ethical concerns about AI (23 percent). 

AI Skills Gap (Dooder/Shutterstock)

The lack of skill set required for AI adoption signals an opportunity for individuals who acquire and improve their skills in the development, deployment, and maintenance of AI solutions. There has also opportunities in the emergence of new AI-related roles, such as AI project managers and machine learning engineers.  

A recent report by Deloitte also showed that a major bottleneck to AI adoption is ethical concerns. While the perception of AI technologies’ potential for social good is increasing, the perception of its potential for harm is rising even faster.

The need for trustworthy and governed AI is understood by IT professionals surveyed by IBM, but organizations are finding it challenging to overcome the barriers to AI adoption. A high percentage of IBM survey respondents (85 percent) agreed that consumers are more likely to choose services from companies with transparent and ethical AI practices. 

As organizations continue to work toward deploying AI technology, the IBM study shows that less than half (47 percent) are developing ethical AI policies. For companies that have not been able to meet their AI deployment goals, 2024 will be a pivotal year. If the rate of enterprise AI adoption has to rise, then organizations will need to find ways to overcome the barriers to AI adoption. 

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