IBM Report: Early Adopters Driving Enterprise AI Growth

Early adopters are leading the way when it comes to the use of enterprise AI, according to new research commissioned by IBM.

According to the Global AI Adoption Index, which polled 8,500+ IT professionals across 20 countries, 59% of enterprises are already working with AI, intending to accelerate and increase investment in the technology. 

But despite the extent of enterprise AI adoption – about 42% of enterprise-scale organisations have AI actively in use in their businesses – ongoing challenges for AI adoption in enterprises remain, from hiring employees with the right skillsets to data complexity and ethical concerns.  

“We’re seeing that the early adopters who overcame barriers to deploy AI are making further investments, proving to me that they are already experiencing the benefits from AI,” said Rob Thomas, Senior Vice President at IBM Software. “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.”

AI adoption has remained steady at large organisations  

According to the Global AI Adoption Index, conducted by Morning Consult on behalf of IBM, 42% of IT professionals at large organisations today have actively deployed AI, while an additional 40% are actively exploring using the technology.  Additionally, 38% of IT professionals at enterprises report that their company is actively implementing generative AI (Gen AI), with another 42% currently exploring the technology. 

When it comes to geography, organisations in India (59%), China (50%), Singapore (53%) and the UAE (58%) are leading the way in the active use of AI, compared with lagging markets like Spain (28%), Australia (29%), and France (26%). 

The majority of surveyed companies actively deploying or exploring AI have accelerated their rollout or investments in the past 24 months. China (85%), India (74%), and the UAE (72%) are the markets most likely to be accelerating AI rollout, while businesses in the UK (40%), Australia (38%) and Canada (35%) were the least likely to accelerate the rollout.

Barriers are keeping the next wave of surveyed companies from benefiting from AI 

But despite enthusiasm for adopting AI, the top barriers hindering successful AI adoption at enterprises both exploring or deploying AI are limited AI skills and expertise (33%), too much data complexity (25%), ethical concerns (23%), AI projects that are too difficult to integrate and scale (22%), high price (21%), and lack of tools for AI model development (21%).    

Generative AI, meanwhile, poses different barriers to entry from traditional AI models. Data privacy (57%) and trust and transparency (43%) concerns are the biggest inhibitors of Gene AI according to IT professionals at surveyed organisations not exploring or implementing generative AI. Around one-third (35%) also say that lack of skills for implementation is a major inhibitor.   

The need for trustworthy and governed AI is understood by IT professionals, but barriers are making it difficult for surveyed companies to put into practice. IT professionals are largely in agreement that consumers are more likely to choose services from companies with transparent and ethical AI practices (85% strongly or somewhat agree) and say being able to explain how their AI reached a decision is important to their business (83% among companies exploring or deploying AI). 

But, with many companies already deploying AI facing multiple barriers in the process, well under half report they are taking key steps towards trustworthy AI like reducing bias (27%), tracking data provenance (37%), making sure they can explain the decisions of their AI models (41%), or developing ethical AI policies (44%).  

“We see organisations leveraging AI for use cases where I believe the technology can most quickly have a profound impact like IT automation, digital labour and customer care,” Thomas explains. “For the 40% of companies surveyed stuck in the sandbox, I am confident 2024 will be the year of tackling and overcoming barriers to entry like the skills gap and data complexity.”

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