WSQ - Project Management with Generative AI (GenAI)

Dr. Siva (Prof. Dr. S. Sivanesan) is a Singapore-based governance, risk and compliance specialist with more than 30 years of experience helping organisations strengthen the way they are directed, controlled and held to account. His work spans governance and board advisory, enterprise risk management (ERM), internal controls and audit, investigations into irregularities and financial fraud, and sustainability and ESG governance and reporting. He has worked with boards, regulators, financial institutions, the public sector and charities across Asia, and is a keynote speaker on AI and governance, risk culture and the future of internal audit. He holds a Doctorate in Governance, Risks and Sustainability from EIMT, a Masters in Business Systems and a Bachelor of Economics (Accountancy) from Monash University, and a Specialist Diploma in Sustainability Reporting from Temasek Polytechnic. His professional credentials include CIA, CISA and CRISC, and he is ACLP-certified in Singapore and an HRDC-accredited trainer in Malaysia.

In this WSQ course on Project Management with Generative AI, Dr. Siva brings a governance and risk perspective to every stage of the project lifecycle. As learners use GenAI to draft project charters, identify stakeholders and build scope, schedule, cost, quality and resource management plans, he challenges them to test those outputs against sound controls and clear accountability. His experience as a curator of ERM frameworks gives particular depth to the risk management plan, risk responses and the monitoring and control activities in Topic 3, from integrated change control to monitoring risks and closing a project or phase. His keynote work on AI and governance also informs practical discussion on using generative AI responsibly, checking its outputs and protecting sensitive project data. Drawing on long experience of working with boards and regulators, he helps learners engage senior stakeholders, communicate project risk clearly and anticipate problems before they disrupt delivery, so they leave able to combine GenAI productivity with disciplined project governance.

Dr. Alfred Ang is a certified Project Management Professional (PMP), a Certified ScrumMaster (CSM) and ITIL certified, and he also builds AI systems, a combination that suits a course on applying generative AI to project management. As Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd, he leads multidisciplinary teams in both software delivery and workforce upskilling, and he leads agentic AI adoption and digital transformation initiatives that help enterprises move from experimentation to operational AI. He is a full-stack AI developer and Agentic AI solution architect, holds a PhD in Electrical Engineering from NUS and an MSc in Electrical and Electronic Engineering from NTU, and is a Microsoft Certified Power BI Data Analyst (PL-300) and AWS Certified Solutions Architect. He has also worked in the defence, electronics and semiconductor industries. Among his 300+ public GitHub repositories are several project management tools: single-file IT PMO Kanban boards with drag-and-drop, filters, overdue tracking, KPI tiles and project status charts, including a portfolio dashboard and project timeline for a fictitious bank, and a guided SIPOC and process map builder for Lean Six Sigma that generates swimlanes and handoff tables. He has also built a Kacific ERP prototype in which purchase orders pass through human-in-the-loop approvals by email, Asana and Telegram, a useful example of AI agents operating within proper governance. He has published more than 20 peer-reviewed papers and co-invented more than 20 US patents.

Project Management with Generative AI follows the life of a project from initiation to closure, and Dr. Ang shows learners where generative AI can save time at each stage without weakening professional judgement. In the first topic on initiation and planning, learners use GenAI to draft a project charter, identify stakeholders and develop the full set of subsidiary plans, covering scope, schedule, cost, quality, resources, communications, risk, risk responses and procurement. The second topic covers execution and delivery, including directing project work, managing project knowledge, stakeholder engagement, quality, team and communications, where AI helps with status reports, meeting summaries and stakeholder messages. The third topic addresses risk and control: implementing risk responses, conducting procurements, monitoring and controlling work, integrated change control, validating and controlling scope, schedule and costs, and closing the project or phase. His PMP grounding means the framework is applied faithfully, while his AI engineering experience helps learners write prompts that produce usable registers, plans and reports rather than generic text. He also highlights the limits of AI in projects, particularly around confidential information, accountability and decisions that must remain with the project manager. As an ACTA-certified trainer and DACE-certified curriculum developer, he runs the course as a series of practical exercises on a realistic project, aligned to the WSQ assessment, so learners leave with templates and prompts they can reuse. Explore his project management tools on his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/

Wayne Lim is an ACTA-certified trainer, Agile practitioner and Scrum Master with 11 years of project management experience in the construction and marine sectors. He graduated from RMIT University with a bachelor's degree in construction management and has lectured in tertiary institutions on management, marketing, engineering, mathematics and customer service. Today he is part of a start-up in the maritime sector, and his current interests in R and Python programming, DevOps and Agile methodologies keep him close to the data and technology side of modern project work.

In WSQ - Project Management with Generative AI (GenAI), Wayne brings the discipline of running real construction and marine projects to the use of generative AI across the project lifecycle. Learners use GenAI to initiate and plan a project, from the project charter and stakeholder register to scope, schedule, cost, quality, resource, communications, risk and procurement plans. They then apply it to directing project work, managing stakeholder engagement and quality, and finally to monitoring and controlling scope, schedule, costs and risks through to closing the project or phase. His practitioner background helps participants judge where AI output genuinely saves effort and where the project manager's own experience must decide, so they leave ready to use GenAI with confidence on live projects.

Agus Salim is an ACLP-certified trainer and ICT consultant with over a decade of experience in systems integration, software development and IT security across enterprise and consulting environments. He has led teams delivering cybersecurity, cloud and enterprise IT projects using both agile and waterfall methodologies, and has worked with organisations such as Citi and Check Point Software Technologies. His credentials include PMP, CompTIA Security+, CEH and AWS Certified Cloud Practitioner, together with Microsoft Azure AZ-104 and AZ-305, giving him a balanced grounding in governance, risk management and cloud operations.

In WSQ - Project Management with Generative AI (GenAI), Agus pairs his PMP foundation with hands-on delivery experience to show how generative AI can support project scheduling, task automation and progress tracking. Learners use GenAI to develop the project charter, identify stakeholders and build a full project management plan, then apply it to directing project work, managing the team and communications, and resolving delivery challenges by optimising resources and budgets. The final topic focuses on risk responses, integrated change control and monitoring scope, schedule and cost. His security and governance background encourages careful handling of project data in AI tools, so participants leave able to adopt GenAI in real organisational projects while staying accountable for every decision.