Value
What does the problem currently cost in time, errors, lost revenue, slow delivery or constrained growth?
Free decision guide
Should this problem use AI?
Use six practical questions to compare AI, conventional software, a process change or no new system before you invest.
Start the assessmentA good AI project starts with a valuable problem, usable context and clear limits. “Use AI” is not yet a use case.
How to use this guide
Choose one specific activity—not an entire department. Answer the questions using what happens today. If the business value remains unclear, do not start with architecture or tools.
Six questions
Test the opportunity before choosing the technology.
Frequency
Does the work happen often enough for a better system to produce recurring value?
Clarity
Can you describe the responsibility, inputs, acceptable actions and desired result?
Variability
Does the work contain language, documents, context or changing situations that fixed rules handle poorly?
Access
Can the solution use the business systems, data or actions required to complete useful work?
Control
Can important actions be bounded, logged, reviewed and escalated to a person when needed?
Possible conclusions
The right answer may be AI, software or no new system.
- Keep it manual
- The work is rare, low-value, highly sensitive or changes too often to justify a system.
- Improve the process first
- The current work is inconsistent, unclear or owned by nobody. Software would only make the confusion faster.
- Use conventional software
- The steps are predictable and rules can handle them reliably and economically.
- Use an AI-assisted feature
- AI can classify, extract, summarize or draft while a person remains responsible for the decision or action.
- Build an AI agent
- The work needs context, multi-step decisions and tool use within clear permissions, controls and escalation paths.
- Build a connected system
- The problem spans people, records, permissions and several systems; an agent may be one component rather than the whole answer.
When an agent makes sense
Responsibility + context + tools + boundaries + measurement.
A useful agent can explain what job it owns, what information it may use, which actions it may take, when a person must intervene and how its performance will be evaluated after launch.
Warning signs
Pause before paying for a build when these are still unresolved.
- The proposed AI system has no defined responsibility or measurable outcome.
- The idea begins with a model or tool rather than a valuable problem.
- Success depends on the agent never making a mistake, but no review or recovery path exists.
- The underlying data is inaccessible, inconsistent or not permitted for the intended use.
- A reliable native feature or straightforward software change already solves the problem.
Need a deeper answer?
Turn one valuable problem into a build-ready decision.
The fixed-price AI & Systems Audit maps the current situation, evaluates the options and produces a practical implementation plan in 10 business days.