Business execs gear up for ‘next phase’ of GenAI
Product enhancements and productivity gains are among the top benefits that business leaders expect to achieve from their planned investments in generative artificial intelligence, according to the results of a recent survey by KPMG.
The vast majority (97%) of executives indicated plans for GenAI investments over the next 12 months, with 43% expecting an allocation of $100 million or more. When asked what they saw as the greatest value creation that might come from these investments, half of the respondents said improving products and services via customer data analysis, while 48% said “enhancing efficiency to generate greater productivity.”
“We’re entering the next phase of GenAI, moving from pilots to transformational programs,” Steve Chase, KPMG’s vice chair of AI & Digital Innovation, said in a press release. “Early experimentation has proven the potential of GenAI, sparking a readiness for greater investments that will deliver enterprise-wide productivity gains, reshape business models and create new revenue streams.”
Despite the growing frenzy around GenAI, many companies are taking a measured approach toward adoption, according to Sanjay Sehgal, head of markets at KPMG.
“They want to make sure they do this in a thoughtful way,” Sehgal said in an interview.
Given the size of the companies polled by KPMG, the dollars that are being invested into GenAI are “probably in line” with the types of outcomes that executives are hoping to achieve at this stage — if not low in some cases, he said. KPMG surveyed 220 U.S.-based business leaders representing organizations with an annual revenue of $1 billion or more.
The proportion of S&P 500 companies mentioning AI on earnings calls rose to 36% in the fourth quarter of last year, an all-time high, Goldman Sachs analysts wrote in a February research note shared with CFO Dive.
The report highlighted several companies, including Microsoft, Amazon, and IBM, that are expecting AI to produce results such as enhanced productivity, reduced costs, and improved product offerings.
In one example, IBM CFO James Kavanaugh told investors during a January earnings call that the company remains “laser-focused on our productivity initiatives as we digitally transform our business processes and scale AI within IBM.”
“This includes simplifying our application and infrastructure environments, streamlining our supply chain, aligning our teams by workflow, reducing our real estate footprint and enabling a higher value-added workforce through automation and AI-driven efficiencies,” Kavanaugh said.
KPMG predicts that GenAI performance indicators will continue to evolve over time, with early productivity boosts giving way to more transformative investments. However, enabling long-term business value first requires “meaningful investments” in areas such as data security, governance frameworks and workforce preparedness, the firm said in its release.
“When you put all of that together, that’s an investment that companies have to make to then ultimately be able to reap the value that’s going to be on the other side,” Sehgal said.
Top GenAI investment priorities currently include workforce training and capability building as well as developing governance programs to implement the technology in a responsible way, according to the release. Over half (58%) of organizations said they plan to provide mandatory GenAI skills training in the workplace.
The research comes on the heels of a Deloitte study showing mixed views from CFOs on the outlook for GenAI investments. That poll found that finance leaders are planning to spend modestly on GenAI next year as they navigate some of the risks and uncertainties surrounding the technology.
Thirty percent of the Deloitte survey respondents indicated either uncertainty about the appropriate metrics to use for gauging the value of their investment in GenAI or a lack of current measurements. Those responding to a question about top barriers to GenAI deployment within the finance function in particular cited technical skill gaps, adoption risks, and culture and trust issues, among other concerns.