Programme overview
This programme focuses on selecting and designing AI use cases for automation, patent search, analysis, and R&D workflows.
Participants assess data, reliability, human oversight, intellectual-property risk, and performance measures before piloting.
Who this is for
Innovation, R&D, and digital-transformation leaders
Patent-intelligence, data, and technology teams
Process owners and AI implementation teams
Core content
Defining the problem and criteria for selecting AI use cases
Assessing input data, quality, usage rights, and confidentiality needs
Designing workflows with human review, approval, and traceability
Setting KPIs, risks, pilot scope, and scaling conditions
Learning outcomes
Build a prioritized AI use-case portfolio
Describe data and control requirements for each use case
Design a human-in-the-loop pilot workflow
Recommend KPIs and scale-up decision criteria
Delivery options & scope
Level
Intermediate
Duration
6-hours
Delivery channel
Online