Leading organizations expect to double the number of A.I. projects within a year

Improved customer experience (CX) and task automation are key drivers of AI use: Gartner

Stamford, CT (July 15, 2019) – Organizations that are working with artificial intelligence (AI) or machine learning (ML) have, on average, four AI/ML projects in place, according to a recent survey by Gartner, Inc. Of all respondents, 59% said that they have AI deployed today.

The Gartner “AI and ML Development Strategies” study was conducted via an online survey in December 2018 with 106 Gartner Research Circle Members – a Gartner-managed panel composed of IT and IT/business professionals. Participants were required to be knowledgeable about the business and technology aspects of ML or AI either currently deployed or in planning at their organizations.

“We see a substantial acceleration in AI adoption this year,” said Jim Hare, research vice president at Gartner. “The rising number of AI projects means that organizations may need to reorganize internally to make sure that AI projects are properly staffed and funded. It is a best practice to establish an AI Center of Excellence to distribute skills, obtain funding, set priorities and share best practices in the best possible way.”

Today, the average number of AI projects in place is four, but respondents expect to add six more projects in the next 12 months, and another 15 within the next three years (see Figure 1 below). This means that in 2022, those organizations expect to have an average of 35 AI or ML projects in place.

Customer Experience (CX) and Task Automation Are Key Motivators

Forty percent of organizations named CX as their top motivator to use AI technology. While technologies such as chat bots or virtual personal assistants can be used to serve external clients, most organizations (56%) today use AI internally to support decision making and give recommendations to employees. “It is less about replacing human workers and more about augmenting and enabling them to make better decisions faster,” Mr. Hare said.

Automating tasks is the second most important project type — named by 20% of respondents as their top motivator. Examples of automation include tasks such as invoicing and contract validation in finance or automated screening and robotic interviews in HR.

The top challenges to adopting AI for respondents were a lack of skills (56%), understanding AI use cases (42%), and concerns with data scope or quality (34%). “Finding the right staff skills is a major concern whenever advanced technologies are involved,” said Mr. Hare. “Skill gaps can be addressed using service providers, partnering with universities, and establishing training programs for existing employees. However, establishing a solid data management foundation is not something that you can improvise. Reliable data quality is critical for delivering accurate insights, building trust and reducing bias. Data readiness must be a top concern for all AI projects.”

Measuring the Success of AI Projects

The survey showed that many organizations use efficiency as a target success measurement when they seek to measure a project’s merit. “Using efficiency targets as a way of showing value is more prevalent in organizations who say they are conservative or mainstream in their adoption profiles. Companies who say they’re aggressive in adoption strategies were much more likely instead to say they were seeking improvements in customer engagement,” said Whit Andrews, distinguished vice president, analyst at Gartner.

Gartner clients can learn more in “Survey Analysis: AI and ML Development Strategies, Motivators and Adoption Challenges.”

About the Survey

Gartner’s AI and ML Development Strategies study was conducted via an online survey in December 2018 with 106 Gartner Research Circle Members — a Gartner-managed panel composed of IT and IT/business professionals — in Europe, the U.S., Canada, Asia/Pacific and Latin America.

Participants were required to be knowledgeable about the business and technology aspects of ML or AI either currently deployed or in planning at their organizations. Participant roles were either primarily IT or a mix of IT and business roles with a specific focus and knowledge of AI or ML.

About Gartner

Gartner, Inc. (NYSE: IT), is the world’s leading research and advisory company and a member of the S&P 500. We equip business leaders with indispensable insights, advice and tools to achieve their mission-critical priorities today and build the successful organizations of tomorrow.

Our unmatched combination of expert-led, practitioner-sourced and data-driven research steers clients toward the right decisions on the issues that matter most. We are a trusted advisor and objective resource for more than 15,000 organizations in more than 100 countries — across all major functions, in every industry and enterprise size.

To learn more about how we help decision-makers fuel the future of business, visit www.gartner.com.

Gartner for Marketers provides the objective, expert advice and proven tools that CMOs and other marketing leaders need to seize the right opportunities with clarity and confidence, and to stay ahead of the trends that matter. With in-depth research and analysis, Gartner for Marketers helps you focus on the opportunities with the greatest potential to deliver results. More information on Gartner for Marketers is available online at www.gartner.com/marketing.

Source: Gartner

Tags: Artificial Intelligence (AI), automation, customer experience (CX), Gartner, Machine Learning (ML), trends Read the original article at Insurance-Canada.ca