Five factors to evaluate AI project ideas: Focused, Actionable, Scalable, Tangible, and Resilient.
Why This Matters
Generative AI is changing everything than any previous wave of technology.
Yet many companies face the same frustrating pattern: the technology looks exciting, but the results are slow. Leaders ask for transformation, but teams do not know where to begin.
This gap creates the three common traps in enterprise AI adoption:
- Expectations rise too high
- Investments become heavy
- Failure rates spike
Let's turn these into a simple question:
How do you choose an AI project that is small enough to succeed fast, valuable enough to prove impact, and safe enough to scale? The FASTR Framework is built for that decision.
What This Framework Is About
Invented by a famous Cybersecurity Consulting company, the FASTR framework contains 5 factors that help companies filter ideas, reduce risks, and select business opportunities that AI can support quickly and reliably.
Same as other business frameworks, FASTR brings structure to project evaluation and creates a common language across product, engineering, operations, and leadership.
With its help, you could launch AI pilot projects in weeks, not years, and deliver business value from day one.
Core Concepts of the FASTR Framework
Focused: One Scene, One User, One Goal
AI succeeds when the problem is small and clear.
A focused project is simple to describe, easy to test, and fast to validate. Avoid using vague ambitions like “build an AI platform” and choose a targeted scenario instead. Small scopes reduce cost, shorten cycles, and increase the chance of success.
Evaluation checklist:
- Can the goal be described in one sentence?
- Is the user group clear?
- Can the team deliver a working loop in two to four weeks?
Example: A policy question bot for HR is focused and useful. A company wide AI brain is not.
