University of Warwick

What you'll study

This programme blends core management subjects with applied artificial intelligence and data-driven strategy. You will study the technical foundations of AI alongside modules on digital strategy, innovation and organisation to develop the ability to design, evaluate and implement AI-led business solutions.

• Core modules: digital strategy and transformation; foundations of machine learning and data analytics for managers; AI in business practice; managing innovation and change; ethics, governance and regulation of AI.
• Technical and applied modules: supervised and unsupervised learning methods, natural language processing basics, data visualisation and storytelling for leaders, experimentation and A/B testing, cloud deployment and MLOps concepts.
• Strategy and leadership: competitive strategy in digital markets, platform business models, metrics and KPIs for digital products, stakeholder management and organisational design for data-driven firms.
• Project work: a major applied team project or consultancy assignment with industry partners and an individual dissertation or applied research project that lets you tackle a real-world digital strategy or AI implementation challenge.
• Optional modules and electives: options typically allow deeper study in areas such as financial technology, marketing analytics, cybersecurity strategy, operations and supply-chain analytics, or entrepreneurship and new ventures.

Teaching methods combine lectures, hands-on computing labs, case studies, guest practitioner sessions and group projects. Assessment uses a mix of coursework, group deliverables, applied projects and a final dissertation.

Entry requirements

Applicants are normally expected to hold a good undergraduate degree (UK first-class or upper second-class honours, or the international equivalent) in a quantitative, business or related subject. Candidates with significant relevant work experience and demonstrable quantitative or programming skills may also be considered.

• Quantitative background: prior study or experience in statistics, economics, computer science, engineering or another quantitative discipline is advantageous.
• Work experience: applicants with professional experience in technology, consulting or analytics will be competitive, particularly for those whose experience shows the application of digital tools in business contexts.
• Admissions tests: GMAT or GRE may be requested in some cases but are not universally required; applicants should check the programme entry guidance.
• English language: applicants whose first language is not English must demonstrate proficiency; for example, typical requirements reflect internationally recognised tests (such as IELTS or equivalent).

Career prospects

Graduates move into roles that combine strategic thinking with technical understanding. Typical job titles include digital strategy consultant, AI product manager, data science manager, analytics consultant, digital transformation lead and technology strategy analyst.

• Employers range across consulting firms, large technology companies, financial services, healthcare, manufacturing and high-growth digital startups.
• Graduates are prepared to lead cross-functional teams, translate analytical insight into commercial value, and develop roadmaps for deploying AI responsibly at scale.
• The programme is also suitable preparation for those wishing to continue to research or pursue PhD study in areas intersecting management and data science.

Why study at University of Warwick

Warwick Business School offers a strong combination of rigorous academic teaching and practitioner-informed learning. The school has established links with industry, providing opportunities for live projects, guest lectures and networking with employers engaged in digital transformation.

• Interdisciplinary strengths: you can draw on expertise across the Business School and other parts of the university to combine strategy, operations and technical AI knowledge.
• Careers support: dedicated careers and employability services help with recruitment events, employer connections, CV and interview preparation, and internship opportunities.
• Practical learning environment: teaching emphasises applied projects, access to datasets and industry problems, and exposure to contemporary tools and deployment considerations for AI in business.