Automation with AI

Introduces ethical frameworks for autonomous agents. This unit focuses on ensuring that automation and AI are deployed safely and ethically. Explores key considerations around data protection, privacy and security, and develops skills in identifying and mitigating bias in AI systems. The unit also introduces the principles of responsible AI governance to support compliant and trustworthy implementation.

Data pipelines for agents and automation. This unit equips participants with the data fundamentals required to support automation and agentic AI. Covers data structures, data quality and validation, alongside core integration patterns and API concepts. Participants also gain experience in designing data pipelines that enable intelligent agents and scalable automated workflows.

Building foundation automation. This unit builds the capabilities to design effective automation workflows. Covers visual workflow design principles, the use of triggers, actions and connectors, and advanced logic techniques. By the end of the unit, participants are able to build production-ready automations that enhance efficiency and reduce manual workload.

Autonomous agents + multi-agent systems. This unit introduces the configuration of autonomous and intelligent AI systems. Explores conversational AI, document intelligence tools, and the development of autonomous agents capable of interacting with external systems. It also covers multi-agent orchestration, enabling the design of AI systems that collaborate and complete tasks independently.

Communicating agent capabilities and limitations. This unit strengthens individuals' ability to support stakeholders through automation and AI adoption. Covers communication strategies, training design and delivery, and change-management principles that encourage engagement. Participants also develop facilitation and requirements-gathering skills to ensure solutions align with stakeholder needs.

Redesigning processes with autonomous agents. This unit focuses on redesigning processes to harness the full potential of automation and agentic AI. Participants examine end-to-end process automation, human–AI collaboration models, and testing and quality assurance methods. They also explore techniques for evaluating process improvement and measuring return on investment.

Monitoring agent performance and optimisation. This unit introduces methods for monitoring and enhancing the performance of automated and agentic systems. Builds skills in tracking automation outcomes, analysing agent performance and identifying optimisation opportunities. It also prepares individuals to scale solutions effectively while maintaining reliability.

Ensuring ongoing compliance and reporting on automation performance. This unit focuses on the compliance requirements associated with automated systems. It explores regulatory considerations, monitoring and control mechanisms, and approaches to risk assessment and mitigation. Also develops the ability to produce clear, accurate compliance documentation to support organisational accountability.

Measuring automation value and identifying improvement opportunities. This unit equips individuals to maximise the long-term value of automation initiatives. Covers techniques for measuring impact, applying continuous-improvement methodologies and developing strategic automation roadmaps. Participants develop a forward-thinking approach to ensure that automation continues to evolve and deliver sustained organisational benefit.