• New study from KPMG focuses on the challenges and opportunities of artificial intelligence as enterprises enter a new decade
In the next decade, artificial intelligence (AI) is expected to broadly impact daily business operations and provide tangible benefits to employees and consumers, according to Living in an AI World: Achievements and Challenges in Artificial Intelligence across Five Industries, a new study from KPMG LLP. Nine out of 10 respondents anticipate AI will help their organizations run more efficiently, indicating rising expectations and optimism about AI.
But before realizing AI’s true potential, results also indicate that many industries and enterprises must navigate various challenges such as a lack of understanding of technology capabilities, and a lack of skills, training, and initial investment funding, all needed to increase adoption and deployment.
“Executives need to look at AI as a strategic enterprise-wide initiative, not simply a technology play,” Traci Gusher, Principal, Innovation and Enterprise Solutions, Artificial Intelligence at KPMG, said. “It’s not just about installing AI technologies. It’s about using AI as a strategic lever to transform the business. And that requires building deep AI capabilities across the organization – both from the bottom up and the top down.”
AI Is Functional Today Across Industries but Leaders Want More
The report, which encompasses feedback from 750 business decision-makers, highlights noticeable differences in the pace of AI adoption across five industries (healthcare, financial services, transportation, technology and retail). The technology industry is at the forefront of deployment with nearly two-thirds of respondents noting that AI is at least moderately functional in their companies, compared to just 37 percent of respondents in the healthcare industry. Transportation, retail and financial services land in the middle of the spectrum with 55 percent, 52 percent, and 47 percent of respondents respectively indicating at least moderately functional AI adoption.
The study found that most respondents in every industry are seeking more aggressive AI adoption by their organizations.
| Industry | Respondents seeking more aggressive AI adoption |
| Transportation | 79% |
| Technology | 73% |
| Healthcare | 69% |
| Financial Services | 68% |
| Retail | 68% |
The sense that companies could be more aggressive is also apparent in individual perceptions of AI. Of those surveyed, most industry insiders within technology (57 percent), transportation (69 percent), healthcare (52 percent) and retail (64 percent) reported feeling that AI is more hype than reality right now, with only financial services (42 percent) being the exception.
“There is a clear gap between high expectations and the reality of integrating AI into organizations,” said Gusher. “AI implementation must occur in alignment with business strategy – which can take time to do properly.”
Overcoming Challenges to AI Adoption
The findings indicate that most respondents are aware of AI adoption and deployment challenges. The number one challenge cited was a lack of understanding of technology capabilities (46 percent), followed by lack of training (36 percent), and lack of initial investment funding (32 percent).
Related to training, the report found a disconnect around the level of confidence in employee preparedness between senior and frontline leaders. Those at a senior leader/C-level had significantly higher levels of confidence in employee preparedness versus those at a manager level (79 percent vs. 38 percent), indicating further opportunity to build AI literacy across all levels of organizations.
“AI can’t be built in a silo. People across functions should be leveraged, so AI ends up being smarter and more widely utilized. That’s when the organization starts to appreciate what it takes to build AI and make it work,” said Gusher.
The report serves as a reminder that to meet these rising expectations, enterprises need to be more aggressive in supporting AI initiatives investing in R&D, training, the hiring of AI talent and addressing some of the challenges around data security/privacy and job security.
