80% Of Executives Say Any Business Decision Can Be Automated
A third of organisations are applying AI across several business units, creating a stronger competitive differentiator by supporting decisions across business processes A recent survey by Gartner, Inc. revealed that over 80 per cent of respondents favoured automation for any business decision. As automation becomes embedded in digital business, the survey showed how organisations are […]
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A third of organisations are applying AI across several business units, creating a stronger competitive differentiator by supporting decisions across business processes
A recent survey by Gartner, Inc. revealed that over 80 per cent of respondents favoured automation for any business decision. As automation becomes embedded in digital business, the survey showed how organisations are evolving their use of artificial intelligence (AI) as part of their automation strategies.
The other survey findings revealed that One-third of organisations apply AI across several business units. On average, 54 per cent of AI projects make it from pilot to production. Talent is not a significant barrier to AI adoption, with 72 per cent of executives reporting that they have or can source the AI talent they need.
“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 organisations are applying AI across several business units, creating a stronger competitive differentiator by supporting decisions across business processes.”
The survey was conducted online from October through December 2021 among 699 respondents in the U.S., Germany and the UK at organisations who have deployed AI or intend to deploy AI within three years.
Organisations Still Challenged to Move AI From Pilot to Production
The Gartner survey revealed that, on average, 54 per cent of AI projects make it from pilot to production. It is slightly increasing from the Gartner 2019 AI in Organisations Survey, which reported an average of 53 per cent of AI projects that make it to production.
“Scaling AI continues to be a significant challenge,” said Frances Karamouzis, distinguished VP analyst at Gartner. “Organisations still struggle to connect the algorithms they are building to a business value proposition, making it difficult for IT and business leadership to justify the investment required to operationalise models.”
Forty per cent of organisations surveyed indicated that they have thousands of AI models deployed. It creates governance complexity for the organisation, further challenging data and analytics leaders’ ability to demonstrate ROI from each model.
Talent Not a Significant Barrier to AI Adoption
While talent shortages are often assumed to impact AI initiatives, the survey found that it is not a significant barrier to AI adoption. Seventy-two per cent of executives reported that they have or can source the AI talent they need.
“The most successful organisations 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 organisation,” said Brethenoux.
AI Security and Privacy Concerns Misplaced
Respondents did not rank security and privacy concerns as a top barrier to AI adoption; only 3 per cent of executives cited it as a barrier. Yet, 41 per cent of organisations reported they have previously had a known AI privacy breach or security incident.
When asked which parties the organisation was most worried about regarding AI security, 50 per cent of respondents cited concerns about competitors, partners or other third parties, and 49 per cent were concerned about malicious hackers. However, among organisations that have faced an AI security or privacy incident, 60 per cent reported data compromise by an internal party.
“Organisations’ AI security concerns are often misplaced, given that insiders cause most AI breaches,” said Brethenoux. “While attack detection and prevention are important, AI security efforts should equally focus on minimising human risk.”
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