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.”
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.
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 organizations can use IT to overcome business challenges and improve operational efficiency. Follow news and updates from the events on Twitter using #GartnerSYM.
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