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<!DOCTYPE html> <html lang="en"> <head><script type='text/javascript' src='//cdnjs.cloudflare.com/ajax/libs/yui/3.6.0/yui/yui-min.js'></script><script type='text/javascript' src='//ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js'></script><script type='text/javascript' src='https://assets.adobedtm.com/4a848ae9611a/d0e96722185b/launch-d525bb0064d8.min.js'></script><script type='text/javascript' src=/assets/nr_browser_production.js></script>  <meta charset="utf-8"> <meta name="viewport" content="width=device-width"> <title> "Enhancement, Not Elimination: AI’s Impact on Jobs in the Indirect Tax " by David Henkin and Chris Zangrilli </title>  <meta itemprop="name" content="Enhancement, Not Elimination: AI’s Impact on Jobs in the Indirect Tax Domain"> <meta property="og:title" content="Enhancement, Not Elimination: AI’s Impact on Jobs in the Indirect Tax Domain"> <meta name="twitter:title" content="Enhancement, Not Elimination: AI’s Impact on Jobs in the Indirect Tax Domain"> <meta property="article:author" content="David Henkin"> <meta name="author" content="David Henkin"> <meta property="article:author" content="Chris Zangrilli"> <meta name="author" content="Chris Zangrilli"> <meta name="robots" content="noodp, noydir"> <meta name="description" content="The article explores the transformative potential of artificial intelligence (AI) in the indirect tax domain in response to Stephen J. Andriole’s article “The Big Miss: AI Will Replace Just About Everything and its view that AI will lead to widespread job displacement. We argue that AI will not broadly eliminate jobs in indirect tax but rather empower tax professionals by automating repetitive tasks, enhancing data analysis, and facilitating compliance. AI-powered tools will enable tax professionals to focus on higher-value activities, such as strategic planning, risk management, and client communication. The future of AI in indirect tax is promising, with advancements in machine learning and generative AI expected to enhance its capabilities further. Organizations that embrace AI and invest in reskilling their workforce will be well-positioned to transform and thrive in the indirect tax domain. AI will enhance, not eliminate, jobs in indirect tax."> <meta itemprop="description" content="The article explores the transformative potential of artificial intelligence (AI) in the indirect tax domain in response to Stephen J. Andriole’s article “The Big Miss: AI Will Replace Just About Everything and its view that AI will lead to widespread job displacement. We argue that AI will not broadly eliminate jobs in indirect tax but rather empower tax professionals by automating repetitive tasks, enhancing data analysis, and facilitating compliance. AI-powered tools will enable tax professionals to focus on higher-value activities, such as strategic planning, risk management, and client communication. The future of AI in indirect tax is promising, with advancements in machine learning and generative AI expected to enhance its capabilities further. Organizations that embrace AI and invest in reskilling their workforce will be well-positioned to transform and thrive in the indirect tax domain. AI will enhance, not eliminate, jobs in indirect tax."> <meta name="twitter:description" content="The article explores the transformative potential of artificial intelligence (AI) in the indirect tax domain in response to Stephen J. Andriole’s article “The Big Miss: AI Will Replace Just About Everything and its view that AI will lead to widespread job displacement. We argue that AI will not broadly eliminate jobs in indirect tax but rather empower tax professionals by automating repetitive tasks, enhancing data analysis, and facilitating compliance. AI-powered tools will enable tax professionals to focus on higher-value activities, such as strategic planning, risk management, and client communication. The future of AI in indirect tax is promising, with advancements in machine learning and generative AI expected to enhance its capabilities further. Organizations that embrace AI and invest in reskilling their workforce will be well-positioned to transform and thrive in the indirect tax domain. AI will enhance, not eliminate, jobs in indirect tax."> <meta property="og:description" content="The article explores the transformative potential of artificial intelligence (AI) in the indirect tax domain in response to Stephen J. Andriole’s article “The Big Miss: AI Will Replace Just About Everything and its view that AI will lead to widespread job displacement. We argue that AI will not broadly eliminate jobs in indirect tax but rather empower tax professionals by automating repetitive tasks, enhancing data analysis, and facilitating compliance. AI-powered tools will enable tax professionals to focus on higher-value activities, such as strategic planning, risk management, and client communication. The future of AI in indirect tax is promising, with advancements in machine learning and generative AI expected to enhance its capabilities further. Organizations that embrace AI and invest in reskilling their workforce will be well-positioned to transform and thrive in the indirect tax domain. AI will enhance, not eliminate, jobs in indirect tax."> <meta name="bepress_citation_journal_title" content="Communications of the Association for Information Systems"> <meta name="bepress_citation_firstpage" content="846"> <meta name="bepress_citation_lastpage" content="853"> <meta name="bepress_citation_author" content="Henkin, David"> <meta name="bepress_citation_author" content="Zangrilli, Chris"> <meta name="bepress_citation_title" content="Enhancement, Not Elimination: AI’s Impact on Jobs in the Indirect Tax Domain"> <meta name="bepress_citation_date" content="2024"> <meta name="bepress_citation_volume" content="55"> <meta name="bepress_citation_issue" content="1">   <meta name="bepress_citation_pdf_url" content="https://aisel.aisnet.org/cgi/viewcontent.cgi?article=4613&context=cais"> <meta name="bepress_citation_abstract_html_url" content="https://aisel.aisnet.org/cais/vol55/iss1/31"> <meta name="bepress_citation_doi" content="10.17705/1CAIS.05532"> <meta 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Domain</a></h1> </div> <div class='clear'></div> <div id='authors' class='element'> <h2 class='visually-hidden'>Authors</h2> <p class="author"><a href='https://aisel.aisnet.org/do/search/?q=author%3A%22David%20Henkin%22&start=0&context=509156'><strong>David Henkin</strong></a><br /> <a href='https://aisel.aisnet.org/do/search/?q=author%3A%22Chris%20Zangrilli%22&start=0&context=509156'><strong>Chris Zangrilli</strong></a><br /> </p></div> <div class='clear'></div> <div id='abstract' class='element'> <h2 class='field-heading'>Abstract</h2> <p>The article explores the transformative potential of artificial intelligence (AI) in the indirect tax domain in response to Stephen J. Andriole’s article <em>“The Big Miss: AI Will Replace Just About Everything</em> and its view that AI will lead to widespread job displacement. We argue that AI will not broadly eliminate jobs in indirect tax but rather empower tax professionals by automating repetitive tasks, enhancing data analysis, and facilitating compliance. AI-powered tools will enable tax professionals to focus on higher-value activities, such as strategic planning, risk management, and client communication. The future of AI in indirect tax is promising, with advancements in machine learning and generative AI expected to enhance its capabilities further. Organizations that embrace AI and invest in reskilling their workforce will be well-positioned to transform and thrive in the indirect tax domain. AI will enhance, not eliminate, jobs in indirect tax.</p> </div> <div class='clear'></div> <div id='doi' class='element'> <h2 class='field-heading'>DOI</h2> <p>10.17705/1CAIS.05532</p> </div> <div class='clear'></div> <div id='recommended_citation' class='element'> <h2 class='field-heading'>Recommended Citation</h2>  <p> Henkin, D., & Zangrilli, C. (2024). Enhancement, Not Elimination: AI’s Impact on Jobs in the Indirect Tax Domain. Communications of the Association for Information Systems, 55, 846-853. <a href="https://doi.org/10.17705/1CAIS.05532" >https://doi.org/10.17705/1CAIS.05532</a> </p> </div> <div class='clear'></div> </div> </div> <div id='beta_7-3'>     <div class="aside download-button"> <a id="pdf" class="btn" href="https://aisel.aisnet.org/cgi/viewcontent.cgi?article=4613&context=cais" title="PDF (446 KB) opens in new window" target="_blank" > <i class="icon-download-alt" aria-hidden="true"></i> Download </a> </div>         <div id="article-stats" class="aside hidden"> <p class="article-downloads-wrapper hidden"><span id="article-downloads"></span> DOWNLOADS</p> <p class="article-stats-date hidden">Since October 30, 2024</p> <p class="article-plum-metrics"> <a href="https://plu.mx/plum/a/?repo_url=https://aisel.aisnet.org/cais/vol55/iss1/31" class="plumx-plum-print-popup plum-bigben-theme" data-badge="true" data-hide-when-empty="true" ></a> </p> </div> <script type="text/javascript" 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