Introductory description

This module introduces students to the strategic and practical integration of Artificial Intelligence (AI) within programme and project management, focusing on the use of AI-supported and data-informed methods to enhance decision-making across scheduling, risk management, cost control, workflow automation and predictive forecasting within Agile and hybrid delivery contexts. It emphasises the application of algorithmic reasoning and data analytics to improve project performance, governance and lifecycle control, while critically examining organisational and digital transformation challenges and ethical considerations, including regulatory compliance, algorithmic bias and accountability. The module foregrounds responsible, transparent and effective approaches to AI-enabled decision-making and digital transformation, and is delivered through a blended learning model to support flexible participation across overseas and part-time centres.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Students progress from applying AI-supported methods within Agile project environments to improve planning, governance and lifecycle decision-making, to designing adaptive project and programme strategies that integrate traditional and emerging frameworks with AI-enabled approaches in support of accountability and informed stakeholder decision-making. They then critically assess the ethical, strategic and regulatory implications of AI in project and organisational contexts, with particular attention to digital trust, transparency and responsible innovation, before interpreting, applying and communicating data-analytic insights to support project decision-making, optimisation and AI-enabled improvement.

Learning outcomes

By the end of the module, students should be able to:

• Apply and critically evaluate AI-supported methods within Agile project environments to enhance planning, governance and lifecycle decision-making.
• Design adaptive strategies that integrate traditional and emerging programme and project frameworks with AI-enabled approaches to support accountability and stakeholder decision-making.
• Critically assess the ethical, strategic and regulatory implications of AI in project and organisational settings, focusing on digital trust, transparency and responsible innovation.
• Interpret and apply data-analytic methods to visualise and communicate insights that support project decision-making and AI-enabled optimisation.

Indicative reading list

Reading lists can be found in Talis

Specific reading list for the module

Subject specific skills

Critical evaluation of AI-enabled approaches to project and programme management, applying analytical judgement rather than technical specialism.
Digital and data literacy in configuring, interpreting and communicating AI-supported insights for project decision-making.
Problem-solving and optimisation skills, using analytical tools and dashboards to improve planning, monitoring and delivery performance.
Governance-aware decision-making, aligning technical and analytical choices with organisational controls, regulatory requirements and stakeholder needs.
Ethical reasoning and professional judgement, applying principles of transparency, fairness, accountability and privacy in AI-supported project contexts.
Collaborative and adaptive working, using AI-supported tools within Agile and changing environments to support team-based delivery and continuous improvement.

Transferable skills

Critical thinking and problem-solving, enabling structured analysis and evidence-based judgement in complex and uncertain contexts.
Digital literacy, including confident and responsible use of data, analytics and AI-supported tools to support professional practice.
Leadership and collaboration, supporting effective teamwork, facilitation and shared decision-making across multidisciplinary project environments.
Strategic thinking, linking operational and analytical decisions to organisational objectives and long-term value creation.
Communication and stakeholder engagement, translating technical and analytical insights into clear, accessible and persuasive narratives.
Adaptability and resilience, responding effectively to change, uncertainty and evolving technological and organisational environments.
Continuous learning and reflective practice, supporting ongoing professional development in rapidly changing digital contexts.