{"id":19,"date":"2026-09-11T06:01:48","date_gmt":"2026-09-11T06:01:48","guid":{"rendered":"https:\/\/bisconf.org\/2027\/?page_id=19"},"modified":"2026-10-20T14:36:17","modified_gmt":"2026-10-20T14:36:17","slug":"call-for-papers","status":"publish","type":"page","link":"https:\/\/bisconf.org\/2027\/call-for-papers\/","title":{"rendered":"Call for Papers"},"content":{"rendered":"<style>.cfp-section .cfp-topic-list{display:flex;flex-direction:column;gap:1.5rem;margin-top:1.5rem}.cfp-section .cfp-topic-card{background-color:#FCF8F8;border-left:3px solid var(--primary);border-radius:var(--radius-md,8px);padding:1.25rem 1.5rem}.cfp-section .cfp-topic-card:hover{background-color:var(--primary-light);color:#000000;}.cfp-section .cfp-topic-card h4{color:var(--text-main,inherit);margin:0 0 .6rem}.cfp-section .cfp-topic-card ul{line-height:1.65;margin:0;padding-left:1.5rem}<\/style>\n<section class=\"cfp-section\" id=\"scope\">\n<div style=\"float:left; margin-right: 10px;\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" width=\"48\" height=\"48\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"4\" cy=\"6\" r=\"2\"><\/circle><circle cx=\"4\" cy=\"18\" r=\"2\"><\/circle><circle cx=\"12\" cy=\"5\" r=\"2\"><\/circle><circle cx=\"12\" cy=\"12\" r=\"2\"><\/circle><circle cx=\"12\" cy=\"19\" r=\"2\"><\/circle><circle cx=\"20\" cy=\"12\" r=\"2\"><\/circle><path d=\"M6 6l4-1M5.5 7.3l4.8 3.5M5.5 16.7l4.8-3.5M6 18l4 1M14 5.8l4.5 4.8M14 12h4M14 18.2l4.5-4.8\"><\/path><\/svg><\/div>\n<h2 style=\"margin-bottom: 15px;\">Orchestrating Human and Artificial Intelligence in Business<\/h2>\n<div style=\"clear:both;\"><\/div>\n<p>Artificial Intelligence has swiftly entered enterprises, often faster than regulatory and organizational frameworks can adapt. Employees increasingly recognize the benefits of AI and integrate it into their daily work, sometimes without formal approval or governance mechanisms. This phenomenon, often referred to as shadow AI, creates both opportunities and risks. As the initial fascination with AI matures, organizations are beginning to ask a more fundamental question: what comes next?<\/p>\n<p>Public debate around AI remains polarized. Some voices warn about disruption, job displacement, and broader societal consequences, while others emphasize unprecedented opportunities for productivity and innovation. At the same time, many organizations are reevaluating earlier workforce reduction strategies and recognizing that the future is not a binary choice between people and AI. Instead, the challenge lies in establishing effective approaches for alignment, collaboration, and orchestration. Organizations need robust frameworks for the safe and responsible adoption of AI technologies. The theme \u201cOrchestrating Human and Artificial Intelligence in Business\u201d reflects these profound changes in organizations, work practices, and labor markets.<\/p>\n<p>Beyond the societal perspective, there is a pressing need for methods, tools, and technologies that support this transition. AI agents require coordination and governance. It is not enough to provide them with access to tools and knowledge; they must also be able to collaborate effectively with people. Determining which tasks should be performed by humans, which by AI agents, and which through hybrid collaboration has become a central research question. Business Process Management has long focused on coordinating activities across people and organizations. Today, a new participant enters this landscape: autonomous AI agents.<\/p>\n<\/section>\n<section class=\"cfp-section\" id=\"tracks\">\n<div style=\"float:left; margin-right: 10px;\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" width=\"48\" height=\"48\"><polygon points=\"12 2 2 7 12 12 22 7 12 2\"><\/polygon><polyline points=\"2 17 12 22 22 17\"><\/polyline><polyline points=\"2 12 12 17 22 12\"><\/polyline><\/svg><\/div>\n<h2 style=\"margin-bottom: 15px;\">Topics of Interest<\/h2>\n<div style=\"clear:both;\"><\/div>\n<div class=\"cfp-topic-list\">\n<div class=\"cfp-topic-card\">\n<h4>Artificial Intelligence<\/h4>\n<ul>\n<li>enterprise copilots<\/li>\n<li>foundation and large language models<\/li>\n<li>responsible AI and bias mitigation<\/li>\n<li>AI governance<\/li>\n<li>trust, acceptance and adoption of AI systems<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Agentic Information Systems<\/h4>\n<ul>\n<li>AI agents and multi-agent systems<\/li>\n<li>reasoning and planning<\/li>\n<li>tool use and function calling<\/li>\n<li>agent orchestration and coordination<\/li>\n<li>agent governance and control<\/li>\n<li>no-code, low-code, harness engineering<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Human-AI Collaboration and Augmented Work<\/h4>\n<ul>\n<li>human-AI teaming<\/li>\n<li>hybrid intelligence systems<\/li>\n<li>task allocation between humans and AI agents<\/li>\n<li>AI-assisted decision making<\/li>\n<li>measuring productivity and value of human-AI collaboration<\/li>\n<li>collaborative intelligence<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Knowledge Representation<\/h4>\n<ul>\n<li>AI in knowledge work<\/li>\n<li>knowledge graphs and LLM synergy<\/li>\n<li>GraphRAG<\/li>\n<li>neuro-symbolic AI<\/li>\n<li>knowledge-grounded agents<\/li>\n<li>quality of data and data curation<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>AI-ready Enterprise Data Platforms<\/h4>\n<ul>\n<li>data infrastructure for AI systems<\/li>\n<li>enterprise memory<\/li>\n<li>data science for business systems and applications<\/li>\n<li>data spaces<\/li>\n<li>standards, data models, and business models for smart data<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Intelligent Business Process Management<\/h4>\n<ul>\n<li>AI-enhanced BPM<\/li>\n<li>adaptive and autonomous business processes<\/li>\n<li>process knowledge representation<\/li>\n<li>process mining and generative AI<\/li>\n<li>workflow synthesis and optimization<\/li>\n<li>orchestration of AI services and tools<\/li>\n<li>process digital twins<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Enterprise Architecture and Governance<\/h4>\n<ul>\n<li>AI-enabled enterprise architecture<\/li>\n<li>enterprise transformation<\/li>\n<li>governance of intelligent information systems<\/li>\n<li>organizational capabilities for AI adoption<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Digital Twins and World Models<\/h4>\n<ul>\n<li>world models for business systems<\/li>\n<li>simulation-based decision support<\/li>\n<li>predictive enterprise modelling<\/li>\n<li>digital twins for process optimization<\/li>\n<li>cyber-physical business systems<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Multimodal Models<\/h4>\n<ul>\n<li>multimodal retrieval<\/li>\n<li>multimodal reasoning<\/li>\n<li>visual grounding<\/li>\n<li>multimodal enterprise assistants<\/li>\n<li>deepfake and asset management<\/li>\n<li>document understanding and enterprise content processing<\/li>\n<\/ul><\/div>\n<div class=\"cfp-topic-card\">\n<h4>Societal Implications of AI<\/h4>\n<ul>\n<li>green transformation and sustainability (ESG)<\/li>\n<li>corporate social responsibility (CSR)<\/li>\n<li>misinformation and disinformation<\/li>\n<li>media and information integrity<\/li>\n<li>privacy and digital rights<\/li>\n<li>digital cultures<\/li>\n<\/ul><\/div>\n<\/p><\/div>\n<\/section>\n<p><a name=\"guidelines\"><\/a><\/p>\n<div style=\"float:left; margin-right: 10px;\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" width=\"48\" height=\"48\"><path d=\"M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z\"><\/path><polyline points=\"14 2 14 8 20 8\"><\/polyline><line x1=\"16\" y1=\"13\" x2=\"8\" y2=\"13\"><\/line><line x1=\"16\" y1=\"17\" x2=\"8\" y2=\"17\"><\/line><polyline points=\"10 9 9 9 8 9\"><\/polyline><\/svg><\/div>\n<h2 style=\"margin-bottom: 15px;\">Submission guidelines<\/h2>\n<div style=\"clear:both;\"><\/div>\n<p><a href=\"https:\/\/bisconf.org\/2025\/wp-content\/uploads\/2025\/04\/LNBIP_logo.png\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/bisconf.org\/2025\/wp-content\/uploads\/2025\/04\/LNBIP_logo-300x109.png\" alt=\"\" width=\"300\" height=\"109\" class=\"alignright size-medium wp-image-2870\" style=\"float:right; margin:5px;\"\/><\/a>BIS 2027 proceedings will be published as a volume in <strong>Lecture Notes in Business Information Processing (LNBIP) series by Springer Nature<\/strong>.<\/p>\n<p>Information for LNBIP authors may be found at link: <a href=\"https:\/\/www.springer.com\/gp\/computer-science\/lncs\/conference-proceedings-guidelines\" rel=\"noopener\" target=\"_blank\">www.springer.com\/gp\/computer-science\/lncs\/conference-proceedings-guidelines<\/a><\/p>\n<ul>\n<li>All papers must be typeset using template: <a href=\"https:\/\/resource-cms.springernature.com\/springer-cms\/rest\/v1\/content\/19238648\/data\/v8\" target=\"_blank\" rel=\"noopener\">LaTeX<\/a> or <a href=\"https:\/\/resource-cms.springernature.com\/springer-cms\/rest\/v1\/content\/19238706\/data\/v6\" target=\"_blank\" rel=\"noopener\">MS Word<\/a> (templates are also available at the <a href=\"https:\/\/www.springer.com\/gp\/computer-science\/lncs\/conference-proceedings-guidelines\" rel=\"noopener\" target=\"_blank\">Springer website<\/a>)<\/li>\n<li>Paper must not exceed 12 pages (including abstract and references)<\/li>\n<li>Submissions must represent work that has not been previously published or presented elsewhere. Please ensure that your paper is free from any form of plagiarism.<\/li>\n<li>Submissions do not need to be blinded. <\/li>\n<li>Submissions need to follow <a href=\"https:\/\/link.springer.com\/brands\/springer\/journal-policies#Artificial%20intelligence%20(AI)\" rel=\"noopener\" target=\"_blank\">AI policies<\/a> (especially on AI authorship and Generative AI Images).<\/li>\n<li><span style=\"border: 1px solid #333333; padding: 5px; box-shadow: 2px 2px 2px #999999; background: #fffce8;\"><strong>Submission system<\/strong>: TBA<\/span><\/li>\n<\/ul>\n<p><a name=\"venue\"><\/a><\/p>\n<div style=\"float:left; margin-right: 10px;\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" width=\"48\" height=\"48\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M2 22V9h6V4h8v5h6v13\"><\/path><path d=\"M2 22h20M8 22V9h8v13\"><\/path><path d=\"M11 22v-5h2v5\"><\/path><path d=\"M4 12h2M4 16h2M4 20h2M18 12h2M18 16h2M18 20h2\"><\/path><path d=\"M10 7h4M10 12h4\"><\/path><\/svg><\/div>\n<h2 style=\"margin-bottom: 15px;\">Conference venue<\/h2>\n<div style=\"clear:both;\"><\/div>\n<p>The conference will be held at Pozna\u0144 University of Economics and Business: <a href=\"https:\/\/ue.poznan.pl\/en\" target=\"_blank\" rel=\"noopener\">ue.poznan.pl\/en<\/a><\/p>\n<p>The BIS 2027 will run as <strong>an in-person conference only<\/strong>. Remote attendance is not supported. <\/p>\n<p><a name=\"dates\"><\/a><\/p>\n<div style=\"float:left; margin-right: 10px;\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" width=\"48\" height=\"48\"><circle cx=\"12\" cy=\"12\" r=\"10\"><\/circle><polyline points=\"12 6 12 12 16 14\"><\/polyline><\/svg><\/div>\n<h2 style=\"margin-bottom: 15px;\">Important dates<\/h2>\n<div style=\"clear:both;\"><\/div>\n<ul>\n<li>Submission deadline for conference papers: <strong>January 10, 2027<\/strong><\/li>\n<li>Notification of acceptance\/rejection: <strong>March 5, 2027<\/strong><\/li>\n<li>Submission of final papers (camera ready): <strong>March 24, 2027<\/strong><\/li>\n<li>The conference: <strong>June 23 \u2013 25, 2027<\/strong><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Orchestrating Human and Artificial Intelligence in Business Artificial Intelligence has swiftly entered enterprises, often faster than regulatory and organizational frameworks can adapt. Employees increasingly recognize the benefits of AI and integrate it into their daily work, sometimes without formal approval or governance mechanisms. This phenomenon, often referred to as shadow AI, creates both opportunities and [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"tags":[],"class_list":["post-19","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/pages\/19","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/comments?post=19"}],"version-history":[{"count":46,"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/pages\/19\/revisions"}],"predecessor-version":[{"id":116,"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/pages\/19\/revisions\/116"}],"wp:attachment":[{"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/media?parent=19"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bisconf.org\/2027\/wp-json\/wp\/v2\/tags?post=19"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}