{"id":22707,"date":"2021-03-25T07:23:00","date_gmt":"2021-03-25T07:23:00","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/professionalize-ai-to-maximize-investment\/"},"modified":"2023-08-29T10:43:28","modified_gmt":"2023-08-29T10:43:28","slug":"professionalize-ai-to-maximize-investment","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/professionalize-ai-to-maximize-investment\/","title":{"rendered":"Professionalize AI To Maximize Investment"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"22707\" class=\"elementor elementor-22707\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-fb66929 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fb66929\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-57af804\" data-id=\"57af804\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4732b3d elementor-widget elementor-widget-text-editor\" data-id=\"4732b3d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>AI continues to be a high-stakes business priority, perhaps even more so in the midst of the COVID-19 pandemic, as organizations turn to AI to cut costs and, ultimately, increase efficiencies. Organizations have spent $306 billion on AI applications alone over the past three years, and this number is expected to continue to increase in the year ahead. However, even as more organizations adopt these technologies, 76 percent of C-Suite executives report they struggle with how to scale AI effectively.<\/p>\n<p>Beyond the strategic implementation of the right AI tools for your business needs, treating AI like any other profession is the key to unlocking the value of these technologies. Organizations are increasingly bolstering their core data science teams with \u201ccitizen data scientists\u201d (or, people who create models using predictive analytics but whose roles are outside of the data science field), with no guardrails and standards to enable success. Through the&nbsp;<a href=\"https:\/\/www.accenture.com\/us-en\/insights\/applied-intelligence\/professionalization-ai?c=acn_glb_professionalizatwitter_11636251&amp;n=smc_1020\" target=\"_blank\" rel=\"noreferrer noopener\">professionalization of AI<\/a>, organizations can better position and scale their AI investments, while standardizing processes to drive consistent results and incremental returns on investment. Quality use of AI technologies comes from standards and regulations \u2013 like any other industry \u2013 allowing practitioners to innovate in a responsible way that is sustainable for the future.<\/p>\n<p>If AI is formalized within an organization as a trade, including proper training and standards, it can be strategically scaled to ensure it\u2019s maximizing the best results for an organization and, in turn, providing the best return on investment. The contrast between those who strategically scale vs. those who do not has become increasingly clear in the COVID-19 pandemic as few organizations prove to be more agile than their peers in a time of constant crisis and change. These strategic scalers are also 1.5-2.5 times more likely to establish dedicated multidisciplinary teams.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-81564a1 elementor-widget elementor-widget-heading\" data-id=\"81564a1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Organizations can successfully professionalize AI in four steps:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-30b8ea9 elementor-widget elementor-widget-text-editor\" data-id=\"30b8ea9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Create distinguished roles and responsibilities for AI practitioners: Formalizing teams for AI capabilities and setting clear standards and responsibilities for practitioners models other professions and builds trust between the practitioner and stakeholders, both internally and externally. It also creates internal organization and accountability on teams to know what the expectations are at each level. In fact, 72% of strategic scalers say their employees fully understand how AI applies to their roles.<\/li><li>Implement education and training: AI practitioners should be given a clear career path, which will also allow for skill standards to be set in roles, avoiding a skill gap and inconsistencies in ability.<\/li><li>Establish defined processes: AI products should be tested and implemented with specific benchmarks to ensure a standardized approach that can be repeated. It\u2019s also important to analyze the way people work with these technologies and how to optimize human-machine collaboration.<\/li><li>Democratize AI: AI is becoming increasingly important to different roles within an organization. Through training programs and AI literacy efforts focused on those outside of <a href=\"https:\/\/www.experfy.com\/blog\/health-tech\/what-is-the-impact-of-wearable-technology-in-the-healthcare-industry\/\" target=\"_blank\" rel=\"noreferrer noopener\">technology<\/a> roles across an organization, other employees can gain confidence in AI and see how it applies to their roles.<\/li><\/ul>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1a2fd00 elementor-widget elementor-widget-text-editor\" data-id=\"1a2fd00\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>As AI becomes increasingly prevalent in organizations\u2019 operations, why should it be treated differently than other roles? Proper training and guidelines will maximize your investments, create long-term growth opportunities for AI in your organization and power your business to outperform peers.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>As AI becomes increasingly prevalent in organizations\u2019 operations, why should it be treated differently than other roles? Proper training and guidelines will maximize your investments, create long-term growth opportunities for AI in your organization and power your business to outperform peers.<\/p>\n","protected":false},"author":1088,"featured_media":19029,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[183],"tags":[97,1455,1456],"ppma_author":[3903],"class_list":["post-22707","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-ml","tag-artificial-intelligence","tag-investment","tag-professionalize-ai"],"authors":[{"term_id":3903,"user_id":1088,"is_guest":0,"slug":"fernando-lucini","display_name":"Fernando Lucini","avatar_url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2021\/05\/Fernando-Lucini-Accenture-150x133.jpeg","user_url":"https:\/\/www.accenture.com\/in-en","last_name":"Lucini","first_name":"Fernando","job_title":"","description":"Fernando Lucini is Global Data Science &amp; Machine Learning Engineering Lead at Accenture Applied Intelligence."}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22707","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/users\/1088"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=22707"}],"version-history":[{"count":4,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22707\/revisions"}],"predecessor-version":[{"id":31797,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22707\/revisions\/31797"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/19029"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=22707"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=22707"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=22707"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=22707"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}