{"id":1233,"date":"2024-05-25T14:51:54","date_gmt":"2024-05-25T14:51:54","guid":{"rendered":"https:\/\/aifinancetoday.com\/?p=1233"},"modified":"2024-05-25T14:51:55","modified_gmt":"2024-05-25T14:51:55","slug":"how-to-handle-ai-stalls","status":"publish","type":"post","link":"https:\/\/aifinancetoday.com\/how-to-handle-ai-stalls\/","title":{"rendered":"How to Handle \u201cAI Stalls\u201d"},"content":{"rendered":"\n<p><em>These four speed bumps could derail a chief financial officer\u2019s best AI strategies.<br><\/em><br>Approximately 90% of U.S. CFOs say their <a href=\"https:\/\/aifinancetoday.com\/boosting-revenue-streams-with-ai\/\">AI budgets<\/a> are on the rise in 2024, with 71% saying they\u2019ll boost their AI budgets by more than 10% this year, according to a <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2024-02-07-gartner-cfo-survey-shows-nine-out-of-ten-cfos-project-higher-ai-budgets-in-2024\">recent Gartner survey<\/a>.<br><br>\u201cAs organizations venture further down the AI path, executives must agree on their ultimate goals for using this technology,\u201d said Alexander Bant, chief of research at Gartner Finance. \u201cCFOs should complement increased spending on AI with critical C-suite discussions about the organization\u2019s AI ambition.\u201d<br><br>A big part of that ambition should be avoiding potential landmines that could stop a company\u2019s <a href=\"https:\/\/aifinancetoday.com\/uncle-sam-wants-worker-input-in-ai\/\">artificial intelligence plans<\/a> in their tracks.<br><br>This week, Gartner pointed to several potential \u201cAI stalls\u201d that could curb or even cancel a firm\u2019s adoption of artificial intelligence.<br><br>\u201cGartner has been working with 80,000 executives around the globe to figure out the right use cases, to improve data, and to get teams ready for the new era of AI,\u201d said Clement Christensen, senior director analyst, research, in the Gartner Finance practice at the company\u2019s CFO &amp; Finance Executive Conference This week in National Harbor, Md. \u201cHowever, as enterprises continue to pursue AI<em>,<\/em> we see cracks emerging: four enterprise-level organizational challenges in particular that we call the \u2018AI Stalls\u2019.\u201d<br><br>At the keynote event, Christensen and Gartner vice president and senior analyst Nisha Bhandare said AI Stalls are process-oriented and not structural. \u201cThese are common problems with the ways organizations use AI rather than problems with the technology itself and can cause significant delays in the adoption and return on investment of AI,\u201d Christensen said.  <br><br><strong>Gartner\u2019s \u201cFour AI Stalls\u201d Explained<\/strong><br><br>The AI stalls cited at the event cover a quadrant of key areas: cost overruns, misuse in decision making, loss of trust, and a rigid mindset.<br><br>\u201cThese stalls will be pervasive across most organizations of all sizes and industries from now through 2030. The time to course correct these stalls is now, and CFOs have a vital role in the enterprise in identifying and counteracting these stalls before they become a reality,\u201d Bhandare said.<br><br><strong>Cost Overruns<\/strong>. \u201cThere\u2019s a uniqueness to AI costs. Given how new AI is, CFOs don\u2019t really know how much it costs: they are learning as they go, driving cost estimates off by 500-1000%,\u201d said Bhandare. \u201cInitial rollout costs, such as infrastructure, user licenses, hiring new talent and implementation costs, are something CFOs are aware of and are not different to other technologies.\u201d<br><br>Bhandare points to a pair of cost buckets that match up with company AI investments, and CFOs need to account for those costs.<br><br>&#8212; The cost of keeping AI running, compliant, and data-efficient. \u2018Gen AI comes with its own uniqueness and usage cost per query, per employee,\u201d Gartner noted. \u201cThis is where most of the volatility in cost projections arise &#8211; especially as organizations mature from basic to more advanced AI use cases.\u201d<br><br>&#8212; The cost of experimentation (i.e., \u201csunk costs\u201d). Unlike other technologies, AI follows an experimentation process: start small and keep training the AI model. \u201cWith experiments, there are failures due to low adoption or from choosing the wrong use case,\u201d Gartner stated.<br><br><strong>Misuse in Decision Making<\/strong>. Smart CFOs will \u201cpace\u201d their AI rollouts to ensure expectations are being met and that the company isn\u2019t getting ahead of itself with its artificial intelligence initiative.<br><br>\u201cMost of the CFO\u2019s enterprise colleagues \u2013 such as business decision-makers in marketing, sales, and supply chain are excited about the benefits of automation, and they will likely overestimate AI\u2019s intelligence,\u201d said Bhandare. \u201cThey\u2019ll want to go to an automation solution right away instead of a trial period using more of a decision support or augmentation approach.\u201d<br><br><strong>Loss of External Trust.<\/strong> Like any new technology, especially a groundbreaking one like AI, trust is a huge issue for senior executives, especially in finance, where the metrics are vital to a company\u2019s story.<br><br>That\u2019s why it\u2019s important for CFOs to ensure that their company&#8217;s investments don\u2019t \u201cbreak\u201d the trust built with external parties.<br><br>\u201cWhen the data that AI is using to interact with external parties is biased or insecure, when the model is not updated to reflect current regulations, or when employees are not skilled to explain AI results to their customers: these failure points can lead to AI providing information that is incorrect, biased, or simply contrary to the company\u2019s culture. This will erode the trust organizations have built with their stakeholders,\u201d Christensen noted.<br><br><strong>A \u201dRigid\u201d Mindset<\/strong>. There\u2019s little doubt that AI will perform some tasks better than humans. <br><br>Establishing those tasks as a \u201cset of lower value tasks\u201d that staffers will no longer handle is frightening for employees.<\/p>\n\n\n\n<p>\u201cThe mistake CFOs often make is that while they tell employees what they wanted them to stop doing, they don\u2019t properly identify what they wanted them to start doing or provide any support for new ways of working,\u201d said Christensen. \u201cRather than just asking \u2018Is the tool easy to use?\u2019 ask, \u2018How will staff react to the use of AI, and how are we planning for their response?\u2019\u201d<br><br><br><\/p>\n","protected":false},"excerpt":{"rendered":"<p>These four speed bumps could derail a chief financial officer\u2019s best AI strategies.Approximately 90% of U.S. CFOs say their AI&#8230;<\/p>\n","protected":false},"author":10,"featured_media":856,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1],"tags":[],"acf":[],"aioseo_notices":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.3 - 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