Google Cloud Generative AI Leader Professional Certificate

1 - Set exercises - 10

Group Coursework

2 - Oral assessment and presentation - 30

Individual Coursework

3 - Written assignment (including essay) - 60

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The module explores enterprise AI strategy, functional applications in operations, marketing, finance, HR and corporate decision-making, followed by organisational readiness, capability building and operating model redesign. It then addresses responsible AI governance, regulatory considerations and performance measurement, culminating in frameworks for scaling AI initiatives to achieve sustainable cross-functional value creation.
Indicative list of topics:
<ul><li>Strategic Context and Value Creation</li><li>AI in Strategy and Corporate Decision-Making</li><li>AI in Operations and Supply Chains</li><li>AI in Marketing and Customer Management</li><li>AI in Finance and Risk Management</li><li>AI in Human Resource Management</li><li>From Pilot to Scale: Organisational Readiness and Capability Building</li><li>Operating Model Transformation and AI Integration</li><li>Responsible AI, Ethics, and Regulatory Compliance</li><li>Measuring AI Impact and Scaling for Sustainable Value</li></ul>

Feedback is provided in a number of ways throughout your module. This includes feedback you receive during teaching from both peers and lecturers and that provided for formative assessment. Following an assessment, you will be given your marks and feedback in line with the assessment regulations and policy. More information on the timing and type of feedback that will be provided for each assessment will be available from the module leader. <a href='https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations'>https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations</a>

This module will support the development of all the graduate attributes. Your module leader will provide you with information about how your learning, teaching and assessment activities support your development of these attributes. The graduate attributes are: - Always learning - Engaged in the world - Technical and digital - Connected Professional - Creating Impact

Directed Asynchronous - 

In-Person - 

Self-directed - 

Best Practices in Business Technology Management. 

All-in on AI: How Smart Companies Win Big with Artificial Intelligence.

Technology Management: Recognizing, Evaluating and Successfully Using Technologies

Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World

Human Compatible: Artificial Intelligence and the Problem of Control

BBM180 - Deploying and Scaling AI Across Business Functions

BBM180-PRD2-PER-ALV1

The module will be taught through a combination of lectures, group work and structured self-directed learning. Lectures are designed to be highly interactive and typically include group-based exercises, guided (case) discussions, or guest talks. During lectures, you are expected to actively contribute, respond to directed questions, and critically engage with the perspectives of peers. A variety of preparatory materials and self-study resources including video lectures, quizzes/exercises, and readings will be made available on the module Moodle page to support in-class participation and deeper exploration of the subject matter. You will be expected to review and engage with these materials, plus undertake learning activities and prepare for cases.

Contact hours are designed to be flexible and are delivered using a variety of methods to help you learn in the most effective way. A proportion of the core content may be delivered online and additional support materials and content will also be made available through Moodle.

Deploying and Scaling AI Across Business Functions

Demonstrate a responsible and ethical orientation toward AI deployment, recognising and addressing risks related to bias, transparency, accountability and governance.

Values and attitudes

Critically evaluate organisational enablers and barriers to AI adoption and scaling, including the role of data, talent and infrastructure capabilities in enterprise deployment.

Knowledge

Evaluate and prioritise functional AI use cases using strategic, operational and financial criteria, and justify recommendations using appropriate qualitative and quantitative evidence.

Skills

Analyse the relationship between organisational AI capability development, scaling choices, and competitive positioning in dynamic and uncertain business environments.

Develop and apply performance metrics to measure AI value realisation and ROI, and communicate AI deployment strategies effectively to technical and non-technical stakeholders.

Design structured AI adoption and scaling roadmaps that align with organisational strategy, including assessing readiness and sequencing initiatives for effective implementation.

Appreciate the importance of human–AI collaboration in organisational contexts, including the implications for decision-making, roles, and professional judgement in complex settings.

Value cross-functional integration and organisational learning in digital transformation and adopt a long-term, sustainability-oriented perspective on AI-driven change.

Apply relevant governance, regulatory and ethical frameworks to enterprise AI deployment, with critical awareness of current issues and emerging expectations.

Demonstrate systematic knowledge of AI applications across major business functions to analyse how these applications generate operational and strategic value within organisations.