AI-Enhanced Project Management (PROED 545)
University of Utah Professional Education
Monitor project performance, automate reporting, detect risks, manage quality, evaluate project close and consider data ethics, bias and transparency.
Browse / 270 listings
Compare 270 listings explicitly covering project management or delivering AI projects. Check the advertised planning, risk, reporting and adoption exercises before enrolling.
Alphabetical order · 61–80 of 270
University of Utah Professional Education
Monitor project performance, automate reporting, detect risks, manage quality, evaluate project close and consider data ethics, bias and transparency.
Packt
LinkedIn Learning
AI-assisted requirements, team construction/staffing, Agile delivery, retrospectives and organizational change.
Project Management Institute
2Impact Consultancy
Atton Institute
Covers AI-supported initiation, charters, scope, WBS/backlogs, estimation, scheduling and scenarios, RAID/risk management, capacity, stakeholder reporting, privacy and governance; ends with an implementation lab and capstone on configuring PM tools and measuring a pilot.
CyberTED
Named sections cover AI/PM foundations, planning and scheduling, risk/issues, team collaboration and communication, performance tracking/reporting, Agile and hybrid PM, AI PM tools, future trends and a capstone project.
Justin Bateh, PhD / Maven
Use an AI PM workspace for status, meetings and risks; select low-risk agent tasks, write delegation briefs, redesign a workflow with human ownership/QA and develop an agent-system blueprint.
Stanford University IT Technology Training
Amir Fazel
NAIT Continuing Education
Prompt frameworks, iterative output refinement and workflow-aligned prompt systems for project-management performance and communication using ChatGPT.
iLect / NABLAS
8 h AI project delivery: problem/data/goal, AI vs non-AI, requirements/specs, schedule/workload/team/vendor, costs/IP/contracts, PoC, acceptance, operations/effects.
HINSHITSU University
Online PM course on AI-era project design/decisions/risks, customer agreements, WBS, quality/done criteria, monitoring and process evaluation.
Microsoft Learn
Requirements and grounding-data assessment for enterprise AI-agent solutions, including measurable value, data quality and scenario selection.
Trainingcred
Ten modules cover mapping AI to project phases, predictive monitoring dashboards, AI evaluation models, coordination workflows, machine-learning/risk, compliance audit, project-plan optimization, stakeholder engagement, virtual meetings and strategic reporting dashboards.
Saudi GLOMACS
The five-day outline moves from AI/data and PM tool analysis to an AI-driven schedule scenario and resource-allocation model, predictive risk assessment/monitoring, responsible integration and team change, then a practical AI-PM tool exercise and personal implementation action plan.
Scandinavian Academy for Training and Development
Eight modules span AI-PM basics, scheduling/milestones, predictive risk, resources/cost, stakeholder sentiment, monitoring/reporting and ethics. Provider states lectures/visuals, pre/post evaluation, brainstorming and practical role-play; no graded project is stated.
Regewall Training Institute
The ten-module course spans AI fundamentals, AI-supported WBS/scheduling, project forecasting, risk, budget/cost control, communications/reporting, Agile/Waterfall/Hybrid methods, M&E, governance/privacy, and a team capstone. Specific tasks include generating a project schedule with MS Project AI/Asana Intelligence/ClickUp AI, building a simple risk or cost forecasting model, generating a project status report, and presenting an AI-enhanced plan/dashboard for a real or simulated project.
Project Management Institute
Cornelius Fichtner, PMP, CSM
AI literacy/ethics, ML/LLM foundations, prompting and integration with traditional PM planning, risk, reporting and automation.