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. \u201cIt is less about replacing human workers and more about augmenting and enabling them to make better decisions faster,\u201d Mr. Hare said.<\/p>\n Automating tasks is the second most important project type \u2014 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.<\/p>\n 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%). \u201cFinding the right staff skills is a major concern whenever advanced technologies are involved,\u201d said Mr. Hare. \u201cSkill 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.\u201d<\/p>\n The survey showed that many organizations use efficiency as a target success measurement when they seek to measure a project\u2019s merit. \u201cUsing 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\u2019re aggressive in adoption strategies were much more likely instead to say they were seeking improvements in customer engagement,\u201d said Whit Andrews, distinguished vice president, analyst at Gartner.<\/p>\n Gartner clients can learn more in \u201cSurvey Analysis: AI and ML Development Strategies, Motivators and Adoption Challenges.\u201d<\/p>\n Gartner\u2019s AI and ML Development Strategies study was conducted via an online survey in December 2018 with 106 Gartner Research Circle Members \u2014 a Gartner-managed panel composed of IT and IT\/business professionals \u2014 in Europe, the U.S., Canada, Asia\/Pacific and Latin America.<\/p>\n 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.<\/p>\n About Gartner<\/b><\/p>\n Gartner, Inc. (NYSE: IT)<\/em>, is the world\u2019s 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.<\/p>\n 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 \u2014 across all major functions, in every industry and enterprise size.<\/p>\n To learn more about how we help decision-makers fuel the future of business, visit www.gartner.com<\/a>.<\/p>\n Gartner for Marketers<\/strong> 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<\/a>.<\/p>\n Source: Gartner<\/i><\/p>\n Tags: Artificial Intelligence (AI)<\/a>, automation<\/a>, customer experience (CX)<\/a>, Gartner<\/a>, Machine Learning (ML)<\/a>, trends<\/a> Read the original article at Insurance-Canada.ca <\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Improved customer experience (CX) and task automation are key drivers of AI use: Gartner Stamford, CT (July 15, 2019) \u2013 Organizations that are working with artificial intelligence (AI) or machine learning (ML) have, on...<\/p>\n","protected":false},"author":578,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/posts\/15994"}],"collection":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/users\/578"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/comments?post=15994"}],"version-history":[{"count":0,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/posts\/15994\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/media?parent=15994"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/categories?post=15994"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/tags?post=15994"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"Average](\"https:\/\/www.insurance-canada.ca\/wp-content\/uploads\/2019\/07\/AI-Press-release.png\")
<\/a><\/p>\nCustomer Experience (CX) and Task Automation Are Key Motivators<\/strong><\/h4>\n
Measuring the Success of AI Projects<\/strong><\/h4>\n
About the Survey<\/strong><\/h4>\n