Augmenting Project Delivery with AI: Strategy to Hands On Implementation

Overview of AI and its Evolution

• This session will cover what AI is, key terminology (ML, NLP, LLMs, Agents, RPA, Generative AI), the evolution of AI from expert systems to ML, to LLMs, to autonomous agents, the current landscape and major capability shifts, where AI is heading including agentic workflows, automation and judgement, project management augmentation, and opportunities and limitations.

AI in Project Management + Tools Overview

• This session will cover how AI is transforming project management domains, including schedule creation and optimisation, risk modelling and forecasting, cost estimating and trending, stakeholder communications, contract, procurement, and scope management, and lessons learned automation (MS Project AI, Primavera AI plugins). It will also include an introduction to prompt engineering for project managers, covering precision prompting, role prompting, constraints and structured prompts, chain-of-thought prompting, and common patterns.

AI Strategy for Project Oriented Organisations

• This session will cover the AI maturity model for project delivery organisations, identifying the highest-value project management use cases, the operating model for AI in PMOs, skills uplift for project managers, planners, controllers, and commercial teams, and change management considerations.

HandsOn Agent Building Workshop

• This session will cover defining the objective, creating the agent’s role or persona, structuring instructions and knowledge, testing on project management documents (risk registers, scopes, schedules, etc.), evaluating output and refining prompts, and establishing guardrails for safe agent behaviour.

Understanding AI Risks, Data Governance & Security

• This session will cover categories of AI risks in project environments, including hallucinations, bias, overautomation, version drift and quality issues, and misaligned decision-making. It will also cover data governance essentials, such as identifying data sensitivity (project documents, commercial data, personal information), secure versus insecure use of AI tools, differences between enterprise and consumer AI, data classification for project management artefacts, and organisational policies and controls.

Responsible AI, Ethics & Best Practices

• This session will cover ethical considerations in AI for project managers, including transparency and auditability of AI-assisted project decisions, accountability frameworks, risk mitigation strategies, practical rules for responsible AI in project work, and case examples of ethical and unethical AI usage in project environments.

Wrap-Up, Key Takeaways & Next Steps

• Wrap-up will include key takeaways, next steps, tools and templates to take away, recommended learning pathways, and a Q&A.