- Talent shortages are not an impediment to AI adoption, a Gartner survey of almost 700 business leaders found. More than seven in ten executives reported they currently have or can source the necessary AI talent.
- Companies are deploying AI strategically, to support decision-making and automation across a broad array of business functions, rather than just tactically within tech units. Four in five respondents believe that AI-powered automation can be applied to “any business decision.”
- Demonstrating the effectiveness and the value of AI remains a challenge, despite widespread adoption. Two in five organizations surveyed have thousands of AI models deployed. However, only a little more than half of AI projects make it past the testing phase and into full production, according to the report.
AI has evolved, from cool novelty to narrowly focused tactical tool to a strategic asset with a broad range of enterprise applications.
The technology has now reached a tipping point, Gartner says.
Rather than restricting AI only to specific operations, companies are considering potential applications for AI across the enterprise, whether or not it’s actually going to be used, said Erick Brethenoux, distinguished analyst and VP at Gartner.
The survey was conducted online from October through December 2021 but reflects current headlines:
- Panera will begin testing AI-enabled voice technology for drive-thru customers at two locations in Rochester, New York on Monday.
- University of Florida Health is launching at $3.7 million project to build an AI model for detection new coronavirus variants.
- Samsung Electronics is rolling out a new line of AI-equipped home appliances.
Cardinal Health is using AI for inventory management, pricing, logistic and supply chain management, Ray Bajaj, the healthcare giant’s CTO and SVP, said as part of a Reuters virtual symposium on August 25.
AI has also been deployed to assist in population health risk management, to provide physicians with clinical decision support, and to help pharmacists more efficiently count pills, according to Bajaj.
“Every process is going to be AI and machine learning enabled,” he said.
Wins with automation — ML-based operations that reduce the need for workers — are fueling enthusiasm for AI. Successfully upskilling in-house talent has smoothed the way for AI deployments, according to Brethenoux.
Brethenoux said companies are finding employees with backgrounds in operational research, statistics, HR, finance, and engineering who can learn AI.
“One of my clients told me it's a lot easier to teach data science to subject matter experts than to teach subject matter expertise to data scientists,” said Brethenoux.