{"id":28439,"date":"2024-01-18T17:04:22","date_gmt":"2024-01-18T22:04:22","guid":{"rendered":"https:\/\/www.crim.ca\/notions-cles-derisquer-projet\/"},"modified":"2026-01-22T12:28:01","modified_gmt":"2026-01-22T17:28:01","slug":"notions-cles-derisquer-projet","status":"publish","type":"post","link":"https:\/\/www.crim.ca\/en\/notions-cles-derisquer-projet\/","title":{"rendered":"Key concepts for derisking your artificial intelligence project"},"content":{"rendered":"

In the dynamic world of artificial intelligence (AI) and automation, Quebec is at a crucial crossroads. In 2018, the Canadian Advanced Technology Alliance (CATA) revealed that Quebec’s manufacturing sector was significantly less automated compared to its American and German counterparts. This underscores the importance of companies, in Quebec and elsewhere, taking proactive steps to integrate AI into their operations.<\/p>\n

The article ” D\u00e9risquer un projet d’intelligence artificielle : 5 notions cl\u00e9s<\/a> ” published by the CSciences<\/strong> media highlights recommendations from Mathieu Barreau<\/strong>, Director of Business, Communications and Partnerships at CRIM, for successfully navigating an AI innovation project, while minimizing risks.<\/p>\n

1. Know your strategy<\/h2>\n

For any company aspiring to AI innovation, the first step is to clearly define its strategy. Understanding the potential risks is crucial, especially for companies entering such a complex and rapidly evolving field. Indeed, Barreau points out that “a company’s size is not a determining factor in the degree of its risk”. A thorough assessment of the risks and rewards is essential from the outset.<\/p>\n

2. Identify use cases<\/h2>\n

AI projects present unique challenges, mainly due to the rapid evolution of the field. Companies need to explore various use cases to identify those that best fit their business model and objectives. This step helps to determine the types of data needed, whether synthetic, public, or to be collected, and to take regulations into account. <\/span><\/p>\n

3. Analyze data beforehand<\/h2>\n

Careful data analysis is essential. In addition to data quality, it is important to consider data security, storage and usage rights. As Mr. Barreau points out, “We will never take the risk of developing our project on the basis of data for which we have not guaranteed the release of usage rights”.<\/p>\n

4. The right resources<\/h2>\n

The success of an AI project depends largely on the skills and expertise of the team involved. Companies therefore need to ensure they have the right resources, and the right partners.<\/p>\n

5. Reassure your investors<\/h2>\n

Finally, it’s essential to reassure investors, especially if you’re relying on subsidies to finance your project. This involves demonstrating the technical and commercial viability of the project to reduce perceived risks.<\/p>\n

Conclusion<\/h2>\n

Integrating AI into Quebec companies is not only a growth opportunity, but also a strategic challenge. By following these steps, companies can navigate the complex AI landscape more safely, maximizing their chances of success while minimizing risk.<\/p>\n

References<\/h2>\n

Touma, Chlo\u00e9 Anne (2023). ” D\u00e9risquer un projet d’intelligence artificielle: 5 notions cl\u00e9s<\/a> ” <\/em>on the CScience <\/em> website . <\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

In the dynamic world of artificial intelligence (AI) and automation, Quebec is at a crucial crossroads. In 2018, the Canadian Advanced Technology Alliance (CATA) revealed that Quebec’s manufacturing sector was significantly less automated compared to its American and German counterparts. This underscores the importance of companies, in Quebec and elsewhere, taking proactive steps to integrate […]<\/p>\n","protected":false},"author":38,"featured_media":24576,"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-28439","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\/28439","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=28439"}],"version-history":[{"count":1,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/28439\/revisions"}],"predecessor-version":[{"id":28764,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/28439\/revisions\/28764"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/media\/24576"}],"wp:attachment":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/media?parent=28439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/categories?post=28439"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/tags?post=28439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}