Data, AI and Automation for Senior Finance Leaders (Intermediate)
Understand how AI enabled solutions, dynamic forecasts, pricing tools and automated workflows are designed, so you can lead adoption with clarity and confidence.
Shape Your Digital Decision Making
Once leaders understand how data and AI work at a foundational level, the next challenge is understanding how real solutions are created. Many organisations want dynamic forecasting, automated reporting and integrated pricing models, but leaders struggle to evaluate technical proposals or understand what is required for these tools to function. This course bridges that gap by showing how modern AI and automation solutions are designed in practice.
You will learn how data models, rules, assumptions and AI components come together to form complete workflows that operate in real time. Through clear demonstrations and practical examples, you will see how forecasting engines, pricing algorithms, insight pipelines and automated processes are structured, validated and refined. This gives you the ability to speak the same language as your technical teams and understand what drives complexity, cost and value.
By the end, you will be able to assess whether a proposed solution is robust, scalable and commercially sound. You will know how to identify high value opportunities, avoid common design mistakes and ensure AI and automation initiatives genuinely improve performance, accuracy and speed. This capability gives leaders far more control and enables you to direct digital progress with confidence.
Future-Proof Your Role
What to Expect
- How data models, rules, assumptions and logic are combined to design AI enabled solutions
- How integrations work between systems, including APIs, pipelines, connectors and real time feeds
- How automation works in practice, from basic triggers to low code tools such as Power Automate and VBA
- How AI is applied inside workflows, including:
– Machine learning models for predicting and trend detection
– Generative AI for reasoning and automated analysis
– RAG retrieval for accuracy and evidence based responses
– Agentic AI for multi-step decision making and complex tasks - How complete workflows are built for:
– Dynamic forecasting and automated commentary
– Pricing optimisation using internal and external data
– Competitor and market monitoring
– Automated reporting and dashboard refreshes
– Agentic processes that check, decide and act - Real examples of how design choices affect accuracy, reliability and outcome quality
- How to work with technical teams to evaluate proposals and shape solution design
Key Outcomes
- Clear understanding of how AI enabled forecasting, pricing and automation tools are designed
- Ability to spot risks, weaknesses or unrealistic assumptions in proposed solutions
- Confidence to guide technical teams and shape workflows to fit business needs
- Clearer identification of high value automation and AI opportunities
- Stronger capability to oversee and direct digital improvement projects
- A natural progression toward evaluating full AI system architecture in the Advanced course