Gartner Survey Reveals Leading Organisations Expect to Double the Number of AI Projects in Place Within the Next Year
Announcement posted by Gartner 16 Jul 2019
Improved Customer Experience and Task Automation Are Key Drivers of AI Use
Organisations 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 organisations.
“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 organisations 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 Centre 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). This means that in 2022, those organisations expect to have an average of 35 AI or ML projects in place.
Source: Gartner (July 2019)
Customer Experience (CX) and Task Automation Are Key Motivators
Forty percent of organisations 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 organisations (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 (see figure 2). 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.”
Figure 2. Types of AI and ML Projects Currently Deployed
Measuring the Success of AI Projects
The survey showed that many organisations 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 organisations 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.”
For Editors
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 organisations. Participant roles were either primarily IT or a mix of IT and business roles with a specific focus and knowledge of AI or ML. The results of this study are representative of the respondent base and not necessarily the market as a whole.
Additional analysis on AI will be presented during Gartner IT Symposium/Xpo 2019, the world's most important gathering of CIOs and other senior IT executives. IT executives rely on these events to gain insight into how their organisations can use IT to overcome business challenges and improve operational efficiency. Follow news and updates from the events on Twitter using #GartnerSYM.
Upcoming dates and locations for Gartner IT Symposium/Xpo include:
September 16-18: Cape Town, South Africa
October 20-24: Orlando
October 28-31: Gold Coast, Australia
October 28-31: Sao Paulo, Brazil
November 3-7: Barcelona
November 11-14: Goa
November 12-14: Tokyo
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 and build the successful organisations 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 organisations in more than 100 countries — across all major functions, in every industry and organisation size.
To learn more about how we help decision makers fuel the future of business, visit www.gartner.com.
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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 organisations.
“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 organisations 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 Centre 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). This means that in 2022, those organisations expect to have an average of 35 AI or ML projects in place.
Source: Gartner (July 2019)
Customer Experience (CX) and Task Automation Are Key Motivators
Forty percent of organisations 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 organisations (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 (see figure 2). 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.”
Figure 2. Types of AI and ML Projects Currently Deployed
Measuring the Success of AI Projects
The survey showed that many organisations 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 organisations 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.”
For Editors
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 organisations. Participant roles were either primarily IT or a mix of IT and business roles with a specific focus and knowledge of AI or ML. The results of this study are representative of the respondent base and not necessarily the market as a whole.
Additional analysis on AI will be presented during Gartner IT Symposium/Xpo 2019, the world's most important gathering of CIOs and other senior IT executives. IT executives rely on these events to gain insight into how their organisations can use IT to overcome business challenges and improve operational efficiency. Follow news and updates from the events on Twitter using #GartnerSYM.
Upcoming dates and locations for Gartner IT Symposium/Xpo include:
September 16-18: Cape Town, South Africa
October 20-24: Orlando
October 28-31: Gold Coast, Australia
October 28-31: Sao Paulo, Brazil
November 3-7: Barcelona
November 11-14: Goa
November 12-14: Tokyo
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 and build the successful organisations 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 organisations in more than 100 countries — across all major functions, in every industry and organisation size.
To learn more about how we help decision makers fuel the future of business, visit www.gartner.com.
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