{"id":22390,"date":"2026-08-03T18:16:57","date_gmt":"2026-08-03T16:16:57","guid":{"rendered":"https:\/\/pmdoc.ua\/?page_id=22390"},"modified":"2026-08-03T19:10:00","modified_gmt":"2026-08-03T17:10:00","slug":"ai-projects","status":"publish","type":"page","link":"https:\/\/pmdoc.ua\/en\/training\/ai\/ai-projects\/","title":{"rendered":"ai.Projects"},"content":{"rendered":"<h2 class=\"entry-title\">Leading AI Projects<\/h2>\n<p class=\"tagline\">Deliver AI that works in production \u2014 not demos that die in a pilot folder.<\/p>\n<p><strong>Leading AI Projects<\/strong>\u00a0is hands-on\u00a0<strong>AI project management<\/strong>\u00a0training for people who must\u00a0<strong>manage AI projects<\/strong>\u00a0from problem to outcome: scope, data reality, build \/ buy \/ integrate, evaluation,\u00a0<strong>human-in-the-loop<\/strong>, and how to\u00a0<strong>operationalize AI<\/strong>\u00a0inside the company\u2019s delivery method (agile, hybrid, or waterfall).<\/p>\n<p>This is\u00a0<strong>AI project manager training<\/strong>\u00a0for real\u00a0<strong>AI delivery<\/strong>\u00a0\u2014 including\u00a0<strong>generative AI projects<\/strong>,\u00a0<strong>AI agents<\/strong>, and\u00a0<strong>multi-step agentic workflows<\/strong>, with clear value and control points. You lead the project and equip PMs \/ delivery leads who execute under your guidance.<\/p>\n<p>Sometimes\u00a0<strong>project context<\/strong>\u00a0is enough. Sometimes the initiative needs a shared\u00a0<strong>ontology<\/strong>\u00a0so agents, data, and stakeholders share one meaning model. You will decide which path fits\u00a0<em>this<\/em>\u00a0project \u2014 and how that choice shapes the\u00a0<strong>AI project lifecycle<\/strong>.<\/p>\n<div class=\"meta-box\">\n<p><strong>Instructor:<\/strong>\u00a0<a href=\"https:\/\/pmdoc.ua\/en\/evgeniy_musienko\/\">Yevhen Musiienko (Eugene Musienko), PMP<\/a><br \/><strong>Duration:<\/strong>\u00a02 days<br \/><strong>Participants:<\/strong>\u00a08\u201316<br \/><strong>Language:<\/strong>\u00a0English, Ukrainian, or Russian<\/p>\n<\/div>\n<h3>Target Audience<\/h3>\n<ul>\n<li>Project managers and delivery leads who\u00a0<strong>manage AI projects<\/strong>\u00a0or AI-enabled work<\/li>\n<li>Product owners \/ product managers shipping AI features or workflows<\/li>\n<li>Scrum Masters and agile coaches supporting\u00a0<strong>AI delivery<\/strong>\u00a0on the ground<\/li>\n<li>Business analysts and domain experts framing AI problem statements<\/li>\n<li>Team leads in engineering, data, operations, or knowledge work<\/li>\n<li>Anyone accountable for taking an\u00a0<strong>AI pilot to production<\/strong>\u00a0under real constraints<\/li>\n<\/ul>\n<p>Project delivery experience expected. Deep ML engineering not required.<\/p>\n<h3>Knowledge and Skills Acquired<\/h3>\n<p><strong>Participants will understand:<\/strong><\/p>\n<ul>\n<li>Why AI initiatives fail for management reasons more often than model reasons<\/li>\n<li>How to separate hype from fit before building<\/li>\n<li>When\u00a0<strong>project context<\/strong>\u00a0is enough vs when you must build an\u00a0<strong>ontology<\/strong><\/li>\n<li><strong>AI agents<\/strong>\u00a0and\u00a0<strong>multi-step agentic workflows<\/strong>\u00a0\u2014 value and control points<\/li>\n<li>Ethics, HITL, and evaluation as part of\u00a0<strong>responsible AI delivery<\/strong><\/li>\n<li>How to plug AI work into agile, hybrid, or waterfall<\/li>\n<\/ul>\n<p><strong>Participants will be able to:<\/strong><\/p>\n<ul>\n<li>Write an outcome-based\u00a0<strong>AI project<\/strong>\u00a0charter (metric + baseline + target + date)<\/li>\n<li>Design a\u00a0<strong>core AI workflow<\/strong>\u00a0(not only personal AI per role)<\/li>\n<li>Define HITL points, data boundaries, and stop rules<\/li>\n<li>Plan evaluation: quality + business value +\u00a0<strong>AI risk management<\/strong><\/li>\n<li>Set metrics and a keep \/ pivot \/ stop rhythm across the\u00a0<strong>AI project lifecycle<\/strong><\/li>\n<li>Run a short pilot cycle and report evidence to sponsors<\/li>\n<li>Hand off to operations \u2014\u00a0<strong>operationalize AI<\/strong>\u00a0with ownership and monitoring basics<\/li>\n<\/ul>\n<h3>Main Topics<\/h3>\n<h4>Module 1: Framing the AI Project<\/h4>\n<ul>\n<li>Outcome sentence instead of tool names<\/li>\n<li>Feasibility: AI vs automation vs process fix<\/li>\n<li>Scope, MVP, non-goals<\/li>\n<li>Stakeholder map and decision rights<\/li>\n<\/ul>\n<h4>Module 2: Designing the Workflow (Core AI)<\/h4>\n<ul>\n<li>Personal AI on the team vs shared AI workflow<\/li>\n<li><strong>AI agents<\/strong>\u00a0and\u00a0<strong>multi-step agentic workflows<\/strong>\u00a0(e.g. role-based document review loops)<\/li>\n<li>Value points vs control points (logging, permissions, human gates)<\/li>\n<li>Build \/ buy \/ integrate<\/li>\n<li>Fitting into agile, hybrid, or waterfall gates<\/li>\n<\/ul>\n<h4>Module 3: Context, Ontology, Data, and Risk<\/h4>\n<ul>\n<li>When\u00a0<strong>project context<\/strong>\u00a0is enough for delivery<\/li>\n<li>When to build a domain\u00a0<strong>ontology<\/strong>\u00a0for agents, knowledge, and evaluation<\/li>\n<li>Data readiness without becoming a data scientist<\/li>\n<li>Privacy, IP, approved data classes<\/li>\n<li>Bias, hallucinations, override rates<\/li>\n<li><strong>AI risk management<\/strong>\u00a0register for the project<\/li>\n<\/ul>\n<h4>Module 4: Tools, Agents, and Governance on the Project<\/h4>\n<ul>\n<li>Choosing tools for\u00a0<em>this<\/em>\u00a0project\u2019s context<\/li>\n<li>Governing\u00a0<strong>agentic AI<\/strong>: permissions, logging, human approval<\/li>\n<li>Ethical principles applied to delivery tasks<\/li>\n<li>Definition of Done for AI outputs<\/li>\n<\/ul>\n<h4>Module 5: Delivery, Metrics, Operationalize AI<\/h4>\n<ul>\n<li>Learning cycles (4\u20138 weeks) and evidence reviews<\/li>\n<li>Project metrics templates (documentation, code assist, agentic workflow)<\/li>\n<li>From\u00a0<strong>AI pilot to production<\/strong>\u00a0ownership<\/li>\n<li>Workshop: one-page\u00a0<strong>AI project management<\/strong>\u00a0plan + metric pack<\/li>\n<\/ul>\n<h3>Deliverables<\/h3>\n<ol>\n<li>AI Project Charter Template<\/li>\n<li>Workflow Design Canvas (actors, agents, handoffs, human gates)<\/li>\n<li>Metrics Pack (baseline \/ target \/ how to measure)<\/li>\n<li>Evaluation &amp; Go-Live Checklist<\/li>\n<li>Certificate of Completion<\/li>\n<\/ol>\n<p>Optional post-training consultation on a live project.<\/p>\n<h3>Related Trainings<\/h3>\n<table>\n<thead>\n<tr>\n<th>Training<\/th>\n<th>Focus<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><a href=\"https:\/\/pmdoc.ua\/en\/training\/ai\/ai-leadership\/\">Generative AI for Leaders &amp; Executives<\/a><\/td>\n<td>Executive GenAI literacy and tools<\/td>\n<\/tr>\n<tr>\n<td><a href=\"https:\/\/pmdoc.ua\/en\/training\/ai\/ai-adoption\/\">Leading AI Adoption<\/a><\/td>\n<td>Enterprise AI adoption system<\/td>\n<\/tr>\n<tr>\n<td><strong>Leading AI Projects<\/strong>\u00a0<em>(this course)<\/em><\/td>\n<td><strong>AI project management<\/strong>\u00a0\u2014 one initiative to measurable result<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3>Booking<\/h3>\n<p><a href=\"https:\/\/pmdoc.ua\/Contacts\">PMDoc.ua\/Contacts<\/a>\u00a0\u00b7 Instructor\u00a0<strong>Yevhen Musiienko<\/strong>: +380 (67) 980-2577 \u00b7 nitoiti@gmail.com \u00b7\u00a0<a href=\"https:\/\/www.linkedin.com\/in\/Evgeniy-Musienko-gkb1b981\">LinkedIn<\/a><\/p>\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Leading AI Projects Deliver AI that works in production \u2014 not demos that die in a pilot folder. Leading AI Projects\u00a0is hands-on\u00a0AI project management\u00a0training for people who must\u00a0manage AI projects\u00a0from problem to outcome: scope, data reality, build \/ buy \/ integrate, evaluation,\u00a0human-in-the-loop, and how to\u00a0operationalize AI\u00a0inside the company\u2019s delivery method (agile, hybrid, or waterfall). This [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":19497,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"content-type":"","footnotes":""},"class_list":["post-22390","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/pages\/22390","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/comments?post=22390"}],"version-history":[{"count":3,"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/pages\/22390\/revisions"}],"predecessor-version":[{"id":22415,"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/pages\/22390\/revisions\/22415"}],"up":[{"embeddable":true,"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/pages\/19497"}],"wp:attachment":[{"href":"https:\/\/pmdoc.ua\/en\/wp-json\/wp\/v2\/media?parent=22390"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}