Agentic AI opportunity discovery
Identify a business workflow worth investigating for agentic change
Teams have many AI ideas but no agreed problem or accountable sponsor. The decision is how to identify a business workflow worth investigating for agentic change. The work begins with your actual workflow and looks for the evidence that separates intended behaviour from a consequential exception. It is particularly relevant to business-unit leaders and transformation owners. A useful outcome is an explicit account of what was examined, what remains uncertain, and which decision the evidence can support.
The operating choices relationship
- Process observations
Establish the basis for process evidence.
- Simpler alternative
Compare process repair before adding agent behaviour.
- Opportunity shortlist
Retain the scoped finding and its unresolved dependencies.
Decision
Frame the decision around process evidence
Questions and the evidence they need
- Process evidence
- Inspect process observations for the relevant constraint or observation.
- Simpler alternative
- Inspect exception logs for the relevant constraint or observation.
- Disconfirming case
- Inspect staff interviews for the relevant constraint or observation.
The decision is how to identify a business workflow worth investigating for agentic change. This is relevant to business-unit leaders and transformation owners when teams have many AI ideas but no agreed problem or accountable sponsor. Name the affected workflow, the consequence of a wrong decision, and the owner who can act on the result. The initial discussion should establish which evidence is already available and which uncertainty is material enough to investigate.
The specific failure hypothesis is that an attractive demonstration is prioritised despite weak evidence of a material workflow problem. It remains a hypothesis until examined in the deployment. Existing internal tests or operating records may already resolve it; identify the uncovered question before commissioning additional work.
Mechanism
Opportunity discovery starts with observed work
Relationships within operating choices
- Process evidence
- Locate repeated tasks and consequential exceptions.
- Simpler alternative
- Compare process repair before adding agent behaviour.
- Disconfirming case
- Name the observation that would reject the opportunity.
What this specialty examines
Opportunity discovery should identify repeated work, decision friction and consequential exceptions before selecting technology. Observe the process and ask where time, quality or accountability breaks down. An agent is one possible response, alongside simpler automation or process correction.
The review should map repeated work, decision points, constraints and alternatives before selecting a bounded hypothesis. Identify the normal route, relevant exceptions and the authoritative record of the outcome. Inspect the relevant business-system record, enforcement event or process evidence alongside any reported status. Keep incomplete cases visible, with an explanation of what their absence prevents the owner from concluding.
The tradeoff to make explicit
For this decision, visible automation opportunities attract interest while root-cause evidence may favour a simpler process change. Compare the available design or operating choices against the same intended outcome. If one option removes a required control or changes the task boundary, describe that difference before treating its apparent simplicity, speed or lower effort as an improvement. The decision should expose the tradeoff instead of burying it in an aggregate score.
Preparation
Connect the working inputs to the boundary being examined
Evidence packet for process evidence
Illustrative working format
- Process observations
- Retain the observed conditions and distinguish gaps from contrary evidence.
- Exception logs
- Retain the observed conditions and distinguish gaps from contrary evidence.
- Staff interviews
- Identify the accountable role and verify its decision rights or availability.
- Existing performance measures
- Retain the observed conditions and distinguish gaps from contrary evidence.
Start with process observations, exception logs, staff interviews and existing performance measures. Identify the owner, revision and operating context of each source. Sanitised examples may support initial design, but differences from actual conditions should remain explicit. Where direct access is unsuitable, a customer-controlled evidence or execution route may be considered, with agreed handling and retention.
The scope also needs the business sponsor, agreed expectations for a representative business hypothesis, and the authority to inspect the relevant boundary. Specify what evidence would distinguish the failure in which an attractive demonstration is prioritised despite weak evidence of a material workflow problem from acceptable behaviour. If stakeholders disagree about intended behaviour, resolve the interpretation before classifying the observed difference as a defect.
How the work proceeds
Carry process evidence through to an accountable finding
From the scoped material to a decision record
- Process observations
Establish the existing process and its constraints.
- Simpler alternative
Apply the scoped check to disconfirming case.
- Opportunity shortlist
Record the evidence, open dependencies, and the owner’s next decision.
Establish the problem and comparison baseline
Bring process observations, exception logs, staff interviews and existing performance measures into a working session with business-unit leaders and transformation owners. Separate observed process conditions from stakeholder preferences and future estimates. Describe the current approach and at least one credible alternative, including simpler process improvement where relevant. The preparation output is a comparison brief with the unresolved assumptions, accountable owner and observations that would justify advancing or rejecting the proposed option.
Examine options and challenge assumptions
Compare candidate problems using evidence strength and a bounded learning question. Define what would disprove the opportunity, including a stable existing solution or an inaccessible dependency. Avoid treating enthusiasm for a demonstration as confirmed demand.
Choose the next bounded commitment
Develop an opportunity shortlist with evidence gaps and proposed disconfirming tests from the examined alternatives. Distinguish immediate dependencies from questions that a bounded experiment can answer, and name who owns the operating or benefit measure. Recommend an advance, hold, revise or stop decision with a specific next observation. Any later expansion should depend on the agreed learning result and available capacity, rather than the completion of planning activities alone.
Indicative artefact
Make the opportunity shortlist usable by its owner
Opportunity shortlist
Illustrative working format
- Opportunity shortlist
- Identify the assessed workflow, revision, and decision boundary.
- Evidence gaps
- Name the missing evidence, responsible owner, and condition for revisiting the decision.
- Disconfirming tests
- Name the unresolved condition, next action, and accountable owner.
A useful decision artefact is an opportunity shortlist with evidence gaps and proposed disconfirming tests. Supporting material may include selected cases, configuration or process records, evidence references, a disagreement log and prioritised actions. Retain the case selection rationale and material disagreements alongside the result; otherwise the result may be mistaken for complete coverage.
Illustrative scenario
Locate the ticket bottleneck before expanding the agent scope
Drafting time versus approval queues
Illustrative scenario
- Proposed ticket agent
A service team proposes ticket automation before locating the source of its delays.
- Drafting or approval
Compare drafting effort with time waiting in approval queues to identify the actual constraint.
- Next experiment
If approvals dominate, test that constraint before assuming faster drafting justifies more agent features.
Consider a fictional situation: a service team proposes an agent for ticket handling before checking whether delays actually come from approval queues. The scenario is illustrative, with no client engagement, executed test or measured improvement implied.
For ticket delays, inspect whether drafting or approval queues dominate the problem. If approvals are the bottleneck, an agent that writes faster may add little value. The next experiment should examine the actual constraint before expanding feature scope.
Scope and next action
Keep the conclusion within the stated business hypothesis
Confirm fit before the next commitment
- Process evidence
- This review is limited to the stated business hypothesis.
- Process observations
- The relevant owner must confirm access and the intended operating conditions.
- Opportunity shortlist
- Commitment depends on the sponsor’s evidence review.
A strategy or business-case model is decision support. It does not establish demand, guarantee financial returns, commit staffing or authorise organisational changes. Any engagement depends on an agreed scope, qualified team, authorised access and confirmed availability. Bring the affected workflow, its current configuration or process, the triggering change and the evidence already available. When ideas lack an agreed problem or accountable sponsor, confirm which missing observation would change the owner’s next action.
Ways to engage
Related engagement scopes
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AI Transformation Sprint
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Continue exploring
Related insights and resources
Choose the work before the agent
Compare agentic work with simpler alternatives, expose the dependencies behind a promising demonstration, and fund a bounded experiment with a clear decision at its end.
Measure the work that improves
Connect agent activity to accepted business outcomes, establish a credible comparison, and distinguish useful capacity from realized financial value before deciding whether to scale.
Before the pilot: five questions for agent readiness
A compelling demo leaves important questions open. Use a five-dimension rubric to examine the data, authority, evidence, ownership and people behind your next agent initiative.