“The survey has shown that enterprises are shifting away from a purely tactical approach to AI and beginning to apply AI more strategically,” said Erick Brethenoux, distinguished VP analyst at Gartner. “For example, a third of organizations are applying AI across several business units, creating a stronger competitive differentiator by supporting decisions across business processes.”
Organizations Still Challenged to Move AI From Pilot to Production
The Gartner survey revealed that on average, 54% of AI projects make it from pilot to production. This is a slight increase from the Gartner 2019 AI in Organizations Survey, which reported an average of 53% of AI projects that make it to production.
“Scaling AI continues to be a significant challenge,” said Frances Karamouzis, distinguished VP analyst at Gartner. “Organizations still struggle to connect the algorithms they are building to a business value proposition, which makes it difficult for IT and business leadership to justify the investment it requires to operationalize models.”
Forty percent of organizations surveyed indicated that they have thousands of AI models deployed. This creates governance complexity for the organization, further challenging data and analytics leaders’ ability to demonstrate return on investment from each model.
Talent Not a Significant Barrier to AI Adoption
While talent shortages are often assumed to impact AI initiatives, the survey found it is not a significant barrier to AI adoption. Seventy-two percent of executives reported that they have or can source the AI talent they need.
“The most successful organizations use a combination of in-house development and external hiring for AI talent. This ensures that the team renews itself continuously by learning new AI skills and techniques and considering new ideas from outside the organization,” said Brethenoux.
AI Security and Privacy Concerns Misplaced
Security and privacy concerns were not ranked as a top barrier to AI adoption, cited by just 3% of executives surveyed. Yet, 41% of organizations reported they have previously had a known AI privacy breach or security incident.
When asked which parties the organization was most worried about when it comes to AI security, 50% of respondents cited concerns about competitors, partners or other third parties, and 49% were concerned about malicious hackers. However, among organizations who have faced an AI security or privacy incident, 60% reported data compromise by an internal party.
“Organizations’ AI security concerns are often misplaced, given that most AI breaches are caused by insiders,” said Brethenoux. “While attack detection and prevention are important, AI security efforts should equally focus on minimizing human risk.”
More insights from the survey are available in the complimentary Gartner webinar, “The Gartner AI Survey Top 4 Findings.”