AI creates value when it improves a real task: finding information, understanding content, preparing decisions, connecting workflows or checking results.
Many opportunities become visible by examining everyday work: where do people repeatedly search, transfer, compare, coordinate or check information? These six areas help identify and organise such opportunities.
The examples are not ready-made standard products. Data, permissions, process variants and accountability determine which solution is genuinely useful.
Each area explains common starting points, explores three use cases in detail and adds further ideas as a concise orientation.
Consolidate information, compare options and prepare decisions transparently.
Find approved knowledge, compare evidence and prepare expert decisions.
Understand incoming documents, validate data and route complete cases deliberately.
Provide context, prepare communication and support service workflows.
Connect systems, prepare operational decisions and support specialist workflows.
Clarify product work, support development and verify deliverables.
Not every task needs generative AI. Strong solutions often combine AI with clear rules, search, automation and existing systems.
Retrieve relevant information from approved sources and connect it to traceable evidence.
Interpret text, documents, images or conversations and turn them into usable data.
Assess content against defined criteria and surface meaningful differences.
Create drafts, options or next steps that people can review transparently.
Carry out approved actions across systems and route exceptions deliberately.
Surface changes, bottlenecks or quality issues early using suitable baselines.
The most spectacular idea is not automatically the best starting point. A bounded, testable workflow creates stronger evidence for the next decision.
We structure the task, data, systems and risks and propose a testable first scope.
