Data, AI and Automation for Senior Finance Leaders (Foundation)
Build the knowledge senior finance leaders need to guide AI adoption, understand system design and improve data-driven decisions.
Shape Your Digital Decision Making
Businesses are under pressure to make faster, smarter decisions, yet most finance leaders have not been given the tools to understand how modern data, automation and AI actually work. Without this knowledge, digital projects stall, systems fail to connect properly and organisations become dependent on external providers. Our programme gives leaders the clarity, confidence and capability they need to direct AI driven transformation rather than be carried by it.
You will learn how data flows through your systems, how AI enabled tools are designed and how forecasting, pricing, commercial insight and operational workflows are built in practice. Each course shows you what happens behind the scenes so you understand how models think, how decisions are automated and how to structure your data so AI and automation deliver real commercial impact. This understanding empowers you to challenge assumptions, make informed decisions and guide development with authority.
By the end, your leadership team will be able to set better goals, identify high value opportunities, reduce risk and create a digital roadmap that drives competitive advantage. You gain the ability to oversee AI, automation and data architecture with confidence, ensuring every investment strengthens your systems, improves visibility and supports your long term strategy for growth.
Future-Proof Your Role
What to Expect
- How modern databases store, structure and connect information, and how integrations (APIs, data pipelines and real time feeds) move data across systems.
- How automation works, from simple workflow triggers to more advanced tools such as VBA, Power Automate and low-code integrations.
- How AI tools use data, including:
– Machine learning models for predicting and pattern recognition
– Generative AI for reasoning, drafting and summarisation
– RAG (Retrieval Augmented Generation) for accuracy and context
– Agentic AI for decision-making sequences and multi-step tasks. - How these components fit together into end-to-end workflows, such as:
– Automated data collection and validation
– AI-driven forecasting and commentary
– Dynamic pricing with market lookups
– Automated reporting and dashboard updates
– Agentic workflows that review, decide and act - Practical examples showing the impact of good vs poor data design on automation, forecasting, pricing, reporting and AI reliability
- How to work effectively with technical teams to improve data quality and design scalable workflows
Key Outcomes
- A clear understanding of how data integration, automation and AI combine to improve performance and reduce manual effort.
- Confidence to engage in AI, automation and analytics projects with the right expectations and vocabulary.
- Understanding of how AI tools can be safely and effectively applied in your business.
- The ability to identify high-value use cases and translate them into structured workflows your teams can deliver.
- A strong foundation for building dashboards, dynamic forecasts, pricing engines and automated reporting systems.