a study by Gartner reveals that large organizations intend to double the number of their AI projects in place

According to Gartner’s annual AI survey conducted online from October to December 2021 among 699 decision makers from organizations in the United States, Germany and the United Kingdom, published last August, large organizations expect to double the number of AI projects in place and 80% of decision makers believe automation can be applied to any business decision.

The business value of AI will reach $5.1 billion by 2025. Gartner’s annual survey provides insight into the keys to successful AI implementation and barriers to operationalizing AI the AI.

The four themes covered are:

  • The value of AI;
  • The operationalization of AI;
  • Talent recruitment;
  • Privacy, security and risk.

It was conducted with organizations that have deployed AI or intend to deploy AI within three years. It does not concern France, but a study, conducted online last February by Vanson Bourne for Mulesoft, revealed that 78% of French organizations will integrate hyperautomation into their roadmap in the next 24 months.

According to the Gartner study, for 80% of leaders, automation can be applied to any business decision. Erick Brethenoux, vice president and analyst at Gartner, comments on this high percentage:

“The survey showed that companies are moving away from a purely tactical approach to AI and are starting to apply AI more strategically. For example, a third of organizations are applying AI across multiple business units, creating a stronger competitive differentiator by supporting decisions across all business processes. »

The operationalization of AI

The operationalization of AI has only marginally increased over the past two years. the survey reveals that 54% of AI projects go from pilot to production, while the one conducted in 2019 reported an average of 53%.

Frances Karamouzis, vice president and analyst at Gartner, notes:

“Scaling AI continues to be a significant challenge. Organizations still struggle to connect the algorithms they build to a business value proposition, making it difficult for IT and business managers to justify the investment needed to operationalize the models. »

Forty percent of organizations surveyed indicated that they have deployed thousands of AI models, which creates governance complexity for the organization. Data and analytics managers, on the other hand, struggle to demonstrate the ROI of each model.

Talent recruitment

While talent shortages are often seen as a significant barrier to AI adoption, 72% of leaders said they had or could find the AI ​​talent they needed.

Erick Brethenoux explains:

“The most successful organizations use a combination of internal development and external hiring for AI talent. This ensures that the team continually renews itself by learning new AI skills and techniques and considering new ideas from outside the organization. »

Security and Privacy

Although 41% of organizations said they had already had a known privacy breach or security incident related to AI, only 3% of leaders surveyed said they were concerned about security and privacy issues, the rest were not. do not view them as a major barrier to AI adoption.

When asked to specify their AI security concerns, 50% of respondents said problems could come from competitors, partners or other third parties and 49% from cyber attackers. These percentages are astonishing because 60% of organizations that experienced an AI security or privacy incident reported that the data compromise originated from an internal actor.

Erick Brethenoux says:

“Organizational AI security concerns are often misplaced, given that most AI breaches are caused by insiders. While attack detection and prevention are important, AI security efforts should also focus on minimizing human risk. »

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