Research group · CIn — UFPE

Find out where your company really stands on AI adoption.

In ~3 minutes. The FAROL — AI Index for SMEs v1.0 is a (semi-automated) synthesis of 8 global frameworks consolidated by the FAROL group (CIn-UFPE), calibrated for the reality of Brazilian small and medium-sized businesses.

Research in progress · CIn — UFPE
Preview · fictional company
Current fluency
The problem

"AI maturity" is a broken concept.

Most existing frameworks inherit from CMMI — a 1990s model for stable software. AI is not stable. The state of the art changes every few months.

01

False sense of arrival

A company at "level 5 — optimized" feels it has arrived. Precisely for that reason, it is the most vulnerable to being overtaken by the next wave.

02

Penalizes those who experiment

Traditional frameworks reward standardization. In AI, experimenting and discarding quickly is more valuable. 42% of companies abandon AI projects — and that's not failure.

03

Ignores movement

Maturity measures position. What matters in AI is speed of adaptation. Someone who adopted LLMs yesterday may be more fluent than someone who has been doing ML for 5 years.

The solution

Fluency is not maturity. It's movement.

Just as TOEFL measures fluency in English, the FAROL scale measures fluency in AI — from N0 to N5. A living scale that recognizes that stopping means going backwards.

  • Continuous — those who stop practicing lose ground.
  • Distributed — companies can be A in data and D in people.
  • Ecosystem-dependent — it's easier to be fluent in a fluent environment.
A
Vanguard
Native fluency; state of the art.
B
Advanced
Sophisticated and structured use.
C
Intermediate
Consistent initiatives.
D
Initial
Focused experiments.
E
Absent
No significant use.
6
Axes
5
Levels (A → E)
8
Frameworks synthesized
7
Result classes
The 6 axes

Fluency is multidimensional.

FAROL measures each axis separately — and shows where the opportunities are.

01 · Axis

Strategy & Leadership

Clear vision of why AI matters — and leadership that acts coherently, allocating resources and prioritizing projects.

02 · Axis

Data & Infrastructure

Accessible and quality data, in infrastructure that allows training, inference, and continuous experimentation.

03 · Axis

People & Culture

Talent, experimentation culture, and AI literacy distributed across the organization — not concentrated in one person.

04 · Axis

Processes & Governance

How AI projects are selected and evaluated. Governance that doesn't paralyze — but doesn't let chaos reign either.

05 · Axis

Products & Customer

AI that reaches the end customer: products and experiences that solve real problems — not just internal optimization.

06 · Axis

Ethics & Risk

How the company identifies and mitigates AI risks — bias, privacy, transparency — without paralyzing innovation.

Foundations

Built on the shoulders of giants.

FAROL critically synthesizes the 8 most respected frameworks in the world — and calibrates for the Brazilian context in each index of the series (starting with SME Index v1.0).

Differentiator

Other frameworks measure maturity — a position. FAROL measures fluency — a movement. That's why it engages with all of them but reaches different answers.

MIT CISR
Digital capacity · governance
Gartner
Technology maturity · adoption
Deloitte
Transformation · execution
Cisco
AI Readiness Index
Forrester / IBM
Use cases · ROI
Microsoft
AI Maturity Model
Salesforce
Customer-facing AI
NIST
Risk and governance
First index in the series · v1.0

FAROL — AI Index for SMEs v1.0

(Semi-automated) synthesis of the world's 8 most respected global frameworks for AI maturity, consolidated by the FAROL group and calibrated for the reality of Brazilian SMEs. Six axes, three minutes. You leave with your radar, comparison against the 8 frameworks, and concrete next steps to move up a level.

It's the first index in a series — not the definitive version. Other indices will come for other contexts (education, health, public sector...) and new versions will refine this one.