New survey research indicates long-term AI strategy is the top priority for enterprise AI decision-makers, according to global technology research and advisory firm Information Services Group (ISG).
The survey of more than 200 global AI decision-makers finds enterprises plan to double the number of AI-enabled applications by the end of 2024, the tech company said.
Forty-two percent of respondents to the “ISG Market Lens Artificial Intelligence Study” said creating a long-term AI strategy or road map is one of their organization’s top three priorities, followed by 37 percent who said identifying AI use cases that build new revenue streams and 34 percent who prioritize AI use cases that improve customer experience.
“Enterprises currently have an average of 251 AI-enabled applications, including those in pilot or beta mode, a number they expect to nearly double to 488 by the end of 2024. This is a shift in AI spending from 2 percent of the IT budget in 2023 to 3.7 percent in 2024,” said Alex Bakker, ISG distinguished analyst and co-author of the ISG study.
“These AI-enabled applications are wide-ranging, covering analytics, customer experience, HR, supply chain, procurement and more,” Bakker said. “A long-term strategy is critical for guiding this rapid growth and ensuring AI investments are in line with business, revenue and customer experience goals.”
Measuring organizational performance against top AI priorities, respondents rated their progress toward a long-term strategy positively.
Forty-eight percent of survey respondents said their business is doing better than peer companies at formulating a long-term AI strategy, while 42 percent said their AI-supported customer experience is better than peers, the study noted.
A little more than a quarter (27 percent) said they are trailing their peers when it comes to using AI to generate new revenue streams.
Respondents indicated the most valuable AI use cases over the next two years will be cost and value optimization (rated most valuable by 26 percent of respondents), predictive operations such as supply chain (15 percent), and customer-facing recommendation engines (14 percent).
Cost optimization ranks highest across all industries, but other use cases vary by industry, researchers said.
Recommendation engines rank second in banking, financial services and insurance (BFSI) and retail, while predictive operations rank second in the energy and manufacturing sectors.
In healthcare, quality assurance ranks second as the most important use case, the data showed.
“Enterprises expect AI to come at greater cost and are willing to pay 7 percent to 8 percent more for applications with AI functionality,” said Michael Dornan, principal analyst and co-author of the study. “Though the highest proportion (30 percent) of respondents said efficiency is their organization’s primary motivation for enabling AI technologies, AI is currently driving up costs across the business more than it is saving through efficiencies.”
“Twice as many enterprises say their spending on security, cloud, CX and other IT initiatives is increasing compared with those who say it is falling, with AI considered the cause of the increase in around three-quarters of these cases,” Dornan added. “Even still, enterprises are placing the most value on achieving AI’s promise of cost and labor efficiencies over the coming two years.”
Recent ISG Market Lens buyer behavior studies have explored application development and maintenance , cost optimization, cybersecurity, global capability centers, network modernization, banking and the future workplace.
