AIAF Index + AI Progress Watch

Our view of global AI progress.
The numbers and the reasons.

The AIAF Index is our AI-assisted editorial assessment of selected evidence about AI progress worldwide. We look across models, agents and practical applications—not just one company or country.

Global scope, selective evidence. We cannot observe every AI system. The Index expresses AIAF’s judgment; it is not an official global benchmark, a safety rating or a percentage of the way to AGI.

Two ways to understand the same subject

The Index gives a compact editorial assessment across five dimensions. Progress Watch explains what AI can do now, what still fails and what changed. Read them together: the number invites a question; the evidence helps answer it.

What do the five elements mean?

• Capability: the breadth and difficulty of tasks AI demonstrates it can perform.
• Autonomy: how much of a defined workflow AI completes, with intervention and failure rates disclosed.
• Reasoning / reliability: consistency in solving unfamiliar problems, including failed attempts.
• Real-world impact: measured changes to time, cost, quality and people's work in actual deployments.
• WTF factor / surprise: an explicitly subjective editorial view of how unexpected a development is relative to cited, dated expectations. Surprise does not establish competence or safety.

How to interpret the numbers

The intended scale is 0–100, with higher scores expressing a stronger editorial assessment within a dimension. A score of 81 does not mean 81% of all tasks can be done, and 75.4 does not mean 75.4% of the journey to AGI. The historical snapshot lacks published anchors sufficient to explain why each exact number was chosen; it should not be used for precise comparisons.

Before the next scored edition

The composite formula is now the equal-weight mean of all five elements, displayed to one decimal place. If any element is not assessed, no composite is published. Before changing component scores, we will publish the assessment scope, evidence cutoff and dimension-specific scoring anchors. Each dimension must include linked sources, conditions, failures, confidence and a written scoring rationale. Missing evidence will be marked “not assessed”, never replaced with an invented value.

Updates must show what changed and why. Method changes will be versioned; the historical launch score will not be silently recalculated or presented as a comparable baseline. No new scored-release date is confirmed.

Review and update policy

Reviewed weekly. Changed only with evidence.

Scheduled review: every Monday, Malaysia time. The first scheduled evidence review is 21 September 2026. Our daily editorial checks may identify significant developments for an additional review between weekly reviews.

A review does not automatically change a score. Each completed review will publish its date, sources examined, outcome and next review due. The score's assessment date remains separate from the date of the latest review.

Current score edition: 14 September 2026. The overall was corrected to 75.4/100 on 15 September using the unchanged historical components and a published equal-weight formula. This fixes the arithmetic but does not validate the component judgments. New component scores require scoring anchors and traceable evidence. Until those are ready, review notes will disclose the remaining gaps and keep the historical figures clearly labelled.

Review record

15 September 2026 — calculation correction: replaced 72 with 75.4 using (81 + 68 + 76 + 64 + 88) ÷ 5. Components unchanged; no new progress assessment. The original 72 had no documented formula.

15 September 2026 — review policy established. Schedule configured; first weekly evidence review pending. This is a policy update, not a completed score assessment. If a review is delayed, the actual completion date and reason will be disclosed here.

AI Progress Watch

What AI can do now.
What still fails.
What changed.

We follow selected, verifiable developments worldwide. Coverage includes models, agents and applications across organisations and countries; public evidence is uneven and coverage is not exhaustive.

1. What changed: the development, date and task involved.
2. What the evidence shows: source links, test conditions and results.
3. What still fails: limitations, failed attempts and missing evidence.
4. Why it matters: AIAF's labelled interpretation for life and work.
5. Index relevance: which dimension it informs. A score changes only after the scoring review, not automatically with a headline.

Start with a published evidence explainer

An agent’s score is not permission to act →

The 15 September briefing helps explain autonomy and reliability: what did an evaluation establish, what were its limits, and when should a person take over? It is an evidence explainer, not a new scored assessment or breaking-news claim.

AGI Watch: the evaluation lenses →

Our evidence and correction standards →