Course Introduction

Agentic AI is emerging as a powerful evolution of artificial intelligence, enabling systems to move beyond generating content and actively support complex project delivery and coordination activities. By interpreting objectives, accessing information, using approved tools, and completing multi-step tasks, AI agents can help project professionals improve responsiveness, consistency, collaboration, and operational efficiency.

The Agentic AI for Project Delivery and Coordination Course provides a practical and strategic understanding of how agentic AI can be applied throughout the project delivery lifecycle. Participants will explore how intelligent agents can support planning, task coordination, progress tracking, reporting, stakeholder engagement, issue management, risk monitoring, and other activities that traditionally require substantial manual effort.

The course examines the architecture and operating principles behind agentic AI, including goals, instructions, reasoning, context, memory, tools, workflows, orchestration, permissions, and human intervention. Participants will learn how these components work together to enable AI systems to perform structured sequences of activities while remaining aligned with project objectives, organizational policies, and defined operational boundaries.

Practical project delivery applications are a central focus of the course. Participants will learn how to identify suitable coordination processes, design agent-enabled workflows, automate recurring activities, manage information flows, monitor project conditions, and establish appropriate triggers and escalation mechanisms. The emphasis is on practical implementation and measurable improvements rather than AI experimentation without a clear business purpose.

The course also addresses the governance and operational challenges associated with agentic AI. Participants will examine issues involving data privacy, cybersecurity, access permissions, inaccurate outputs, autonomous actions, accountability, bias, auditability, human oversight, and organizational readiness. These considerations are essential for ensuring that AI agents enhance project performance without introducing unacceptable operational or governance risks.

By completing the course, participants will be better prepared to use agentic AI as a practical capability for modern project delivery and coordination. They will develop the knowledge required to identify high-value opportunities, design responsible agent-enabled workflows, improve team coordination, and establish an implementation roadmap that supports productivity, delivery quality, transparency, and sustainable organizational value.

Duration

5 days

Who Should Attend

• Project managers responsible for coordinating project teams, deliverables, schedules, resources, stakeholders, and project execution activities.

• Program managers managing interconnected projects that require sophisticated coordination, information sharing, and cross-project visibility.

• PMO directors and managers seeking to modernize project delivery processes through agentic AI and intelligent workflow capabilities.

• PMO analysts responsible for project reporting, governance, coordination, performance tracking, documentation, and management information.

• Project coordinators looking to reduce manual follow-ups and improve task management, communication, documentation, and delivery coordination.

• Project planners and schedulers interested in using AI agents to monitor activities, dependencies, milestones, constraints, and delivery progress.

• Project controls professionals seeking intelligent approaches to monitoring project performance, identifying exceptions, and coordinating corrective actions.

• Agile delivery managers, Scrum Masters, and product delivery professionals exploring agentic AI for iterative planning, coordination, and team support.

• Business analysts working on project requirements, process analysis, workflow improvement, stakeholder coordination, and digital transformation initiatives.

• Risk and issue managers seeking AI-enabled approaches for monitoring project conditions, escalating concerns, and coordinating risk responses.

• Transformation leaders responsible for implementing AI-enabled operating models and intelligent project delivery capabilities.

• Operations managers responsible for coordinating complex processes involving multiple teams, systems, activities, and organizational dependencies.

• Technology and innovation professionals evaluating agentic AI technologies for enterprise project delivery and operational coordination.

• Consultants and advisors supporting organizations with AI adoption, project transformation, automation, PMO modernization, and digital strategy.

• Senior business and project leaders seeking to understand the strategic implications, opportunities, and risks of agentic AI in project environments.

Course Objectives

• Understand the foundations of agentic AI and distinguish autonomous and semi-autonomous AI systems from conventional automation and generative AI tools.

• Identify project delivery and coordination activities where agentic AI can generate measurable improvements in productivity, responsiveness, quality, and collaboration.

• Analyze existing project workflows to identify bottlenecks, repetitive coordination tasks, manual handoffs, information gaps, and opportunities for agent-enabled improvement.

• Design effective AI-agent roles, objectives, instructions, constraints, permissions, escalation mechanisms, and decision boundaries for project delivery environments.

• Apply agentic AI to project planning, task coordination, progress monitoring, information management, reporting, issue tracking, and stakeholder communication.

• Design multi-step workflows that enable AI agents to gather information, analyze project conditions, initiate approved actions, monitor results, and escalate exceptions.

• Establish human-in-the-loop controls that ensure important project decisions, approvals, sensitive communications, and high-impact actions receive appropriate professional review.

• Evaluate AI-agent performance using practical measures such as accuracy, workflow completion, response time, productivity improvement, delivery consistency, and business value.

• Address governance, security, privacy, access control, accountability, auditability, and operational risks associated with deploying AI agents in project environments.

• Develop a practical roadmap for implementing, testing, governing, scaling, and continuously improving agentic AI capabilities across project delivery and coordination functions.

Comprehensive Course Outline

Module 1: Foundations of Agentic AI for Project Delivery

• Understanding agentic AI concepts, autonomous systems, AI agents, and their growing role in modern project delivery environments.

• Exploring how AI agents differ from generative AI assistants, chatbots, robotic process automation, and traditional workflow automation technologies.

• Examining core agent capabilities including goals, reasoning, context, memory, tool use, action execution, feedback, and adaptive workflow behavior.

• Identifying practical project delivery scenarios where agentic AI can improve coordination, responsiveness, visibility, consistency, and operational efficiency.

Module 2: Project Delivery Processes and Agentic Opportunities

• Mapping project delivery processes to identify manual activities, coordination bottlenecks, repetitive tasks, delays, dependencies, and information gaps.

• Evaluating potential agentic AI use cases according to business value, process complexity, data availability, risk exposure, and implementation readiness.

• Designing future-state delivery processes that combine human expertise, AI agents, conventional automation, and existing project management technologies.

• Establishing measurable success criteria for agentic workflows, including productivity improvements, response times, quality levels, and delivery performance.

Module 3: Designing AI Agents for Project Coordination

• Defining agent roles, objectives, responsibilities, operating instructions, constraints, decision criteria, and expected outputs for project environments.

• Creating effective agent instructions that provide sufficient project context while reducing ambiguity, unnecessary actions, and inconsistent workflow behavior.

• Designing triggers, conditions, decision points, escalation paths, and completion criteria for AI-enabled project coordination workflows.

• Testing and refining agent behavior to improve reliability, consistency, task completion, exception handling, and alignment with project delivery requirements.

Module 4: AI Agents for Planning and Delivery Execution

• Applying agentic AI to support project planning, activity coordination, milestone management, dependency tracking, and delivery readiness activities.

• Designing agents that monitor project plans and identify overdue activities, blocked work, approaching milestones, resource constraints, and potential delivery delays.

• Automating routine coordination activities such as reminders, status requests, task updates, follow-ups, and information collection across project teams.

• Establishing human review points for important planning changes, schedule adjustments, resource decisions, and delivery commitments requiring professional judgment.

Module 5: AI-Enabled Team Coordination and Collaboration

• Using AI agents to coordinate information requests, team updates, action items, decisions, dependencies, and responsibilities across distributed project teams.

• Designing intelligent meeting workflows that prepare agendas, gather relevant information, capture outcomes, assign actions, and monitor completion.

• Applying agentic AI to facilitate communication between project teams while maintaining consistency, appropriate context, confidentiality, and communication standards.

• Managing human-agent collaboration by defining responsibilities, escalation procedures, intervention points, and expectations for team members working with AI systems.

Module 6: Agentic AI for Progress, Risk, and Issue Management

• Designing agents that monitor project information to identify emerging delivery risks, unresolved issues, dependencies, exceptions, and potential performance concerns.

• Applying AI agents to collect risk information, maintain registers, prepare alerts, support escalation, and coordinate approved risk response activities.

• Using agentic workflows to monitor project progress, detect deviations, summarize exceptions, and provide timely information for management intervention.

• Establishing controls that prevent agents from making unauthorized project decisions or executing high-impact corrective actions without appropriate human approval.

Module 7: Intelligent Reporting and Stakeholder Coordination

• Using AI agents to collect project updates, consolidate information, identify key developments, and prepare recurring project and management reports.

• Designing agent workflows that monitor reporting deadlines, identify missing information, follow up with contributors, and escalate unresolved reporting requirements.

• Developing stakeholder coordination workflows that generate appropriate updates, reminders, notifications, and escalation messages based on approved project conditions.

• Establishing validation and approval processes that ensure AI-generated reports and communications remain accurate, relevant, secure, and professionally appropriate.

Module 8: Agent Integration, Orchestration, and Multi-Agent Collaboration

• Understanding how AI agents interact with project platforms, enterprise applications, documents, databases, knowledge repositories, and approved organizational tools.

• Designing secure permissions that determine which project information agents can access and which actions they can perform within connected systems.

• Exploring multi-agent architectures in which specialized agents coordinate planning, reporting, risk monitoring, communication, analysis, and other project delivery responsibilities.

• Managing orchestration, information exchange, dependencies, error handling, workflow recovery, agent handoffs, and escalation across complex delivery environments.

Module 9: Governance, Security, and Emerging Agentic AI Issues

• Addressing agentic AI risks involving hallucinations, incorrect actions, unauthorized access, prompt manipulation, excessive permissions, and unpredictable behavior.

• Establishing governance frameworks covering privacy, cybersecurity, accountability, audit trails, access management, monitoring, human oversight, and responsible AI adoption.

• Examining emerging issues involving autonomous agents, multi-agent ecosystems, persistent memory, agent-to-agent communication, AI identity, and autonomous decision-making.

• Developing testing, monitoring, incident management, quality assurance, and continuous evaluation practices for safe and reliable agentic project operations.

Module 10: Implementation Strategy and the Future of Project Delivery

• Developing an actionable roadmap for piloting, evaluating, implementing, governing, scaling, and continuously improving agentic AI capabilities.

• Building business cases that demonstrate measurable benefits through reduced administrative effort, faster coordination, improved visibility, better responsiveness, and enhanced delivery performance.

• Exploring emerging developments such as autonomous project managers, AI delivery coordinators, multi-agent project ecosystems, intelligent PMOs, and agentic enterprise workflows.

• Creating a practical organizational action plan that aligns agentic AI adoption with project strategy, workforce capabilities, governance requirements, technology readiness, and business outcomes.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.