02 / Applied AI Workflow Workshop

A practical method for structuring human+AI knowledge work.

Give a team a shared way to define the work, provide context, evaluate output and decide where human review belongs—without turning the session into an implementation project.

Fit & trigger

For teams already encountering inconsistent AI use.

Who this is for
A company sponsor or team/department lead with recurring knowledge work, people already using or preparing to use AI, authority to improve team methods and participants able to judge useful output.
When it becomes relevant
AI use varies substantially across the team and there is no shared method for structuring work, evaluating quality or defining human review.
The outcome
A reusable workflow method the team can apply to recurring knowledge work while keeping quality judgement and accountability with people.
What it is
Productised education with light tailoring—not generic AI transformation, automation consultancy or department workflow implementation.
Workshop & deliverables

Teach the method, then make it reusable.

01

2–3 hour workshop

A presentation-led session with a live demonstration, applied exercise and Q&A.

02

Reference materials

A reusable reference deck, workflow design template and evaluation/QA checklist.

03

Illustrative examples

One or two worked examples that teach the method without becoming department implementations.

04

Sponsor/scoping call

Align the audience, constraints, objectives and representative recurring work.

05

Light tailoring

Select and prepare teaching examples within the proposal-defined customization boundary.

06

Bounded follow-up

One first-use Q&A or review in the agreed format.

The method

From fit to accountable use.

Participants learn to treat AI use as workflow design, not ad hoc prompting.

  1. Fit & contextWhere AI fits, boundaries, objective and inputs.
  2. TransformationDefine the operation AI is being asked to perform.
  3. Output & evaluationSpecify the required result and how quality is judged.
  4. Human roleSet review, escalation, ownership and operating mode.
Inputs & readiness

Preparation stays light.

The sponsor provides a brief, representative recurring tasks or sanitized materials, relevant AI/tool/policy constraints and the participant group. Any required tool access or permissions need to be resolved before the session.

If safe examples or permissions are unavailable by the input deadline, the demonstration is narrowed or the session pauses.

Timeline

One focused live session.

The core session lasts 2–3 hours. The proposal fixes the session date, input deadline, participant count, selected examples and follow-up format after scoping.

Boundaries

Standard scope does not include.

  • Department-wide process mapping
  • Bespoke workflow redesign
  • Production automation, agents or integrations
  • Tool procurement
  • SOP implementation
  • Ongoing AI operations or support
  • Guaranteed productivity gains
Price

€2,500 fixed fee

One presentation-led workshop for one team or department.

Apex Arc teaches the method; it does not implement your department's workflows as part of the Workshop.

Sample workshop reference material

Workflow design and output review.

Illustrative teaching material only—not a bespoke department workflow or evidence of client results.

Illustrative teaching material / Not client results
02 / Workflow design & QA

Define the work.
Make quality reviewable.

  1. 01 Context & objective

    What must the model know, and what useful result is required?

    QA check Is the task bounded and appropriate for AI?

  2. 02 Input & transformation

    What source material is authoritative, and what operation is requested?

    QA check Can claims be traced to supplied evidence?

  3. 03 Output & evaluation

    What form should the result take, and what makes it acceptable?

    QA check Are accuracy, completeness and risk checked?

  4. 04 Human role & owner

    Who reviews, escalates and remains accountable?

    QA check Is a qualified human making the final judgement?

Accountability stays with people A reusable teaching reference, not a bespoke department workflow.

Build a shared method

Where does inconsistent AI use create the most friction?