{"id":28437,"date":"2024-01-18T17:04:22","date_gmt":"2024-01-18T22:04:22","guid":{"rendered":"https:\/\/www.crim.ca\/annoter-donnees-ia\/"},"modified":"2026-01-22T12:27:02","modified_gmt":"2026-01-22T17:27:02","slug":"annoter-donnees-ia","status":"publish","type":"post","link":"https:\/\/www.crim.ca\/en\/annoter-donnees-ia\/","title":{"rendered":"The success of an AI project depends on data quality"},"content":{"rendered":"<p>As artificial intelligence (AI) shapes the future of business, data quality is emerging as the essential pillar of success.<\/p>\n<p><strong>Michel Savard<\/strong>, Data Science Practice Leader at CRIM, rightly points out: &#8220;What&#8217;s unique to a company is its data. That&#8217;s where the return on investment lies.<\/p>\n<p>According to Varibase&#8217;s Digital Marketing Survey 2023, although 55% of Quebec companies have data management platforms, their maturity remains moderate, rated at 3.2 out of 10. The question is: How can you ensure the success of your shift to artificial intelligence while minimizing the potential risks?<\/p>\n<p>That&#8217;s when CRIM&#8217;s experts come into play for a successful digital transformation and guarantee the success of AI projects . The article published by <em>Les Affaires<\/em> highlights the main lines addressed by CRIM to ensure data quality:<\/p>\n<h3><strong>1. The challenge of misunderstood data :<\/strong><\/h3>\n<p>CRIM&#8217;s<a href=\"https:\/\/www.numeria.ai\/\" target=\"_blank\" rel=\"noopener\"> NUMERIA<\/a> program offers essential support to SMEs, helping them to <em>de-risk<\/em> their AI projects.<\/p>\n<h3><strong>2. Data quality for effective predictive models :<\/strong><\/h3>\n<p>Beyond quantity, CRIM insists on the importance of data quality for effective predictive models.<\/p>\n<h3><strong>3. Going beyond raw data :<\/strong><\/h3>\n<p>Data governance becomes essential to guarantee the reliability and relevance of the information used.<\/p>\n<h3><strong>4. In search of the &#8220;ground truth&#8221; : <\/strong><\/h3>\n<p>Information that is often overlooked can prove crucial to the success of an AI project.<\/p>\n<h3><strong>5. Invest in data quality : <\/strong><\/h3>\n<p>The key to success in AI lies in continuous investment in data quality.<\/p>\n<p>&nbsp;<\/p>\n<p>Read Michelle Savard&#8217;s full interview <a href=\"https:\/\/www.lesaffaires.com\/dossier\/ia-le-geant-est-parmi-nous\/l-art-d-annoter-ses-donnees\/645966?utm_medium=Social&amp;utm_campaign=echobox&amp;utm_source=LinkedIn\" target=\"_blank\" rel=\"noopener\">&#8220;The art of annotating your data&#8221;,<\/a> published in <em>Les Affaires<\/em>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>As artificial intelligence (AI) shapes the future of business, data quality is emerging as the essential pillar of success. Michel Savard, Data Science Practice Leader at CRIM, rightly points out: &#8220;What&#8217;s unique to a company is its data. That&#8217;s where the return on investment lies. According to Varibase&#8217;s Digital Marketing Survey 2023, although 55% of [&hellip;]<\/p>\n","protected":false},"author":38,"featured_media":24710,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[81],"tags":[],"class_list":["post-28437","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/28437","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/users\/38"}],"replies":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/comments?post=28437"}],"version-history":[{"count":1,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/28437\/revisions"}],"predecessor-version":[{"id":28763,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/28437\/revisions\/28763"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/media\/24710"}],"wp:attachment":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/media?parent=28437"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/categories?post=28437"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/tags?post=28437"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}