{"id":5280,"date":"2021-12-13T06:30:19","date_gmt":"2021-12-13T06:30:19","guid":{"rendered":"https:\/\/www.aiproblog.com\/index.php\/2021\/12\/13\/state-of-ai-2021-ai-adoption-is-maturing-and-here-are-the-top-use-cases-for-2021\/"},"modified":"2021-12-13T06:30:19","modified_gmt":"2021-12-13T06:30:19","slug":"state-of-ai-2021-ai-adoption-is-maturing-and-here-are-the-top-use-cases-for-2021","status":"publish","type":"post","link":"https:\/\/www.aiproblog.com\/index.php\/2021\/12\/13\/state-of-ai-2021-ai-adoption-is-maturing-and-here-are-the-top-use-cases-for-2021\/","title":{"rendered":"State of AI 2021 \u2013 AI Adoption is maturing and here are the top use cases for 2021"},"content":{"rendered":"<p>Author: ajit jaokar<\/p>\n<div>\n<p><a href=\"https:\/\/storage.ning.com\/topology\/rest\/1.0\/file\/get\/9904004279?profile=original\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/storage.ning.com\/topology\/rest\/1.0\/file\/get\/9904004279?profile=RESIZE_710x\" width=\"720\" class=\"align-full\"><\/a><\/p>\n<p>It&#8217;s the end, of the year and its time to reflect back on the year. Mc kinsey has published a state of AI for 2021.<\/p>\n<p>Here are some insights from that report and my view on it<\/p>\n<ul>\n<li>AI adoption is maturing<\/li>\n<li>AI adoption is continuing its steady rise<\/li>\n<li>business functions where AI adoption is most common are service operations, product and service development, and marketing and sales, though the most popular use cases span a range of functions.<\/li>\n<li>The top three use cases are service-operations optimization, AI-based enhancement of products, and contact-center automation<\/li>\n<li>Companies are aware of risks and also threats<\/li>\n<li>Companies are deploying risk mitigation strategies<\/li>\n<li>Professional standards of development are being adopted such as design thinking, model performance tracking, data governance, data quality, AI governance framework, capabilities to develop individual talent<\/li>\n<\/ul>\n<p>Here are my top four insights from the state of AI 2021 survey<\/p>\n<\/p>\n<h2>\u00a01) The most popular AI use cases span a range of functional activities.<\/h2>\n<ul>\n<li>Service-operations optimization<\/li>\n<li>New AI-based enhancements of products<\/li>\n<li>Contact-center automation<\/li>\n<li>Product-feature optimization<\/li>\n<li>Predictive service and intervention<\/li>\n<li>Customer-service analytics<\/li>\n<li>Creation of new AI-based products<\/li>\n<li>Customer segmentation<\/li>\n<li>Risk modeling and analytics<\/li>\n<li>Fraud and debt analytics<\/li>\n<\/ul>\n<p>\u00a0<\/p>\n<p><span style=\"font-size: 14pt;\"><strong>2) Organizations seeing the highest returns from AI are more likely to follow both core and more advanced best practices<\/strong><\/span>.<\/p>\n<ul>\n<li>Use design thinking when developing AI tools<\/li>\n<li>Test the performance of our AI models internally before deployment<\/li>\n<li>Track the performance of AI models to ensure that process outcomes and\/or models improve over time<\/li>\n<li>Have well-defined processes for data governance<\/li>\n<li>Have protocols in place to ensure good data quality<\/li>\n<li>Have a clear framework for AI governance that covers the model-development process<\/li>\n<li>AI-development teams follow standard protocols for building and delivering AI tools<\/li>\n<li>Have well-defined capability-building programs to develop technology personnel\u2019s AI skills<\/li>\n<\/ul>\n<h2>\u00a03) Organizations see significant AI risks\u00a0<\/h2>\n<ul>\n<li>Cybersecurity<\/li>\n<li>Regulatory compliance<\/li>\n<li>Explainability\u00b2<\/li>\n<li>Personal\/individual privacy<\/li>\n<li>Organizational reputation<\/li>\n<li>Equity and fairness<\/li>\n<li>Workforce\/labor displacement<\/li>\n<li>Physical safety<\/li>\n<li>National security<\/li>\n<li>Political stability<\/li>\n<\/ul>\n<h2>4) Organizations are engaging in AI risk-mitigation practices\u00a0<\/h2>\n<ul>\n<li>Model documentation<\/li>\n<li>Training and testing data<\/li>\n<li>Measuring model bias and accuracy<\/li>\n<li>Training and testing data<\/li>\n<li>Scan training and testing data to detect the underrepresentation of protected characteristics and\/or attributes<\/li>\n<li>Data professionals actively check for skewed or biased data during data ingestion<\/li>\n<li>Increase the representation of protected characteristics and\/or attributes in our training and testing data as needed<\/li>\n<li>Data professionals actively check for skewed or biased data at several stages of model development<\/li>\n<li>Legal and risk professionals work with data-science teams to help them understand definitions of bias and protected classes<\/li>\n<li>Have a dedicated governance committee that includes risk and legal professionals<\/li>\n<\/ul>\n<p>Source \u2013 <a href=\"https:\/\/www.mckinsey.com\/business-functions\/mckinsey-analytics\/our-insights\/global-survey-the-state-of-ai-in-2021\">mc kinsey<\/a><\/p>\n<p>\u00a0<\/p>\n<\/div>\n<p><a href=\"https:\/\/www.datasciencecentral.com\/xn\/detail\/6448529:BlogPost:1082581\">Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Author: ajit jaokar It&#8217;s the end, of the year and its time to reflect back on the year. Mc kinsey has published a state of [&hellip;] <span class=\"read-more-link\"><a class=\"read-more\" href=\"https:\/\/www.aiproblog.com\/index.php\/2021\/12\/13\/state-of-ai-2021-ai-adoption-is-maturing-and-here-are-the-top-use-cases-for-2021\/\">Read More<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":470,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[26],"tags":[],"_links":{"self":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/5280"}],"collection":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/comments?post=5280"}],"version-history":[{"count":0,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/5280\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media\/472"}],"wp:attachment":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media?parent=5280"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/categories?post=5280"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/tags?post=5280"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}