Two axes, one score, tasks frozen before the wave.
The score is one number from two measured axes and one confidence layer [S2]. AI Visibility asks whether an AI agent finds and recommends the brand when a buyer asks without naming it. AI Usability asks whether an agent that has arrived can complete a real task on the brand's own surface.
The weighting is public and fixed: AI Visibility × 0.20, AI Usability × 0.70, Evidence × 0.10, shown on a 0 to 10 scale [S2]. Evidence is a confidence note on the measurement, not a third axis to sell against.
Every task is frozen and published before the wave runs, under the Task Selection Doctrine [S3]. One task per brand in this wave, run across three AI providers. The measurement language is German, except for Qiagen, measured in English as the buyer language for expert diagnostics [S5].
Confidence is C for most brands: one measured task each, one wave. Qiagen carries B on full datapoint coverage [S5]. adidas and Zalando carry D, because every measured agent class was blocked before a working surface could be scored [S1].
Two axes, one number, and every task frozen before anyone ran it.
Thirty-six brands ranked, from 7.0 down to 2.5.
Six brands score 5.0 or higher, thirteen stay below 4.0, and the median sits at 4.1 [S1]. At the top, Deutsche Telekom at 7.0: every measured agent class reaches the cart [S4]. At the bottom, Brenntag at 2.5: the buy-critical specification is not on the page, so no agent could confirm the order [S8].
Rank, brand, ticker, sector, the two axes and the score. Each brand name links to the reference page that carries the task, the access profile and the sources.
| Rank | Brand | Ticker | Sector | AI Visibility | AI Usability | Score |
|---|---|---|---|---|---|---|
| 1 | Deutsche Telekom | DTE | Tech & Telecom | 33.8 | 80 | 7.0 |
| 2 | Qiagen | QIA | Pharma & Healthcare | 11.5 | 80 | 6.8 |
| 3 | DHL Group | DHL | Logistics | 46.0 | 68 | 6.5 |
| 4 | Infineon | IFX | Industrials | 39.1 | 68 | 6.2 |
| 5 | Siemens | SIE | Industrials | 44.0 | 57 | 5.6 |
| 6 | Merck | MRK | Pharma & Healthcare | 38.3 | 54 | 5.2 |
| 7 | Deutsche Bank | DBK | Insurance & Finance | 40.5 | 48 | 4.9 |
| 8 | MTU Aero Engines | MTX | Aerospace & Defense | 52.5 | 45 | 4.8 |
| 9 | Commerzbank | CBK | Insurance & Finance | 38.0 | 48 | 4.8 |
| 10 | Fresenius Medical Care | FME | Pharma & Healthcare | 45.0 | 44 | 4.7 |
| 11 | Siemens Energy | ENR | Industrials | 41.9 | 45 | 4.6 |
| 12 | Fresenius | FRE | Pharma & Healthcare | 40.6 | 44 | 4.6 |
| 13 | Symrise | SY1 | Chemicals & Materials | 36.3 | 44 | 4.5 |
| 14 | Vonovia | VNA | Real Estate | 42.8 | 41 | 4.4 |
| 15 | Hannover Rück | HNR1 | Insurance & Finance | 28.2 | 45 | 4.4 |
| 16 | Munich Re | MUV2 | Insurance & Finance | 44.2 | 38 | 4.2 |
| 17 | GEA Group | G1A | Industrials | 40.3 | 38 | 4.1 |
| 18 | Henkel | HEN3 | Consumer & Retail | 35.3 | 39 | 4.1 |
| 19 | BASF | BAS | Chemicals & Materials | 37.7 | 39 | 4.1 |
| 20 | Volkswagen | VOW3 | Automotive | 49.7 | 34 | 4.1 |
| 21 | Beiersdorf | BEI | Consumer & Retail | 34.4 | 39 | 4.1 |
| 22 | Siemens Healthineers | SHL | Industrials | 33.3 | 38 | 4.0 |
| 23 | Mercedes-Benz | MBG | Automotive | 43.6 | 34 | 4.0 |
| 24 | Rheinmetall | RHM | Aerospace & Defense | 49.4 | 30 | 3.7 |
| 25 | Daimler Truck | DTG | Automotive | 21.4 | 38 | 3.7 |
| 26 | E.ON | EOAN | Utilities | 26.3 | 35 | 3.7 |
| 27 | Airbus | AIR | Aerospace & Defense | 43.9 | 30 | 3.6 |
| 28 | Continental | CON | Automotive | 26.4 | 34 | 3.6 |
| 29 | Heidelberg Materials | HEI | Chemicals & Materials | 40.2 | 30 | 3.6 |
| 30 | Zalando | ZAL | Consumer & Retail | 43.3 | 28 | 3.5 |
| 31 | adidas | ADS | Consumer & Retail | 35.0 | 28 | 3.4 |
| 32 | Allianz | ALV | Insurance & Finance | 19.8 | 30 | 3.2 |
| 33 | Bayer | BAYN | Pharma & Healthcare | 22.1 | 30 | 3.1 |
| 34 | SAP | SAP | Tech & Telecom | 29.4 | 26 | 3.1 |
| 35 | BMW | BMW | Automotive | 37.6 | 23 | 3.0 |
| 36 | Brenntag | BNR | Chemicals & Materials | 24.2 | 19 | 2.5 |
36 of 40 member brands are scored on both axes. Scout24 is measured as a marketplace subject in its own lane and is not blended into this ranking. Hochtief is scheduled for Wave Q3 2026.
RWE and Deutsche Börse sit outside the commerce lane: no retail transaction takes place on their brand surface, so there is nothing to measure there [S1]. Universe as of 2026-07-01, reviewed after each Deutsche Börse index review.
Thirty-six scores, one rule. The median DAX brand sits at 4.1.
Three patterns recur across the 36.
Three patterns explain more of the table than the sector column does. Each comes from the published reference page of the brand that shows it most clearly.
Qiagen: a near-flawless surface that mass-market AI rarely finds.
Qiagen scores 6.8, rank 2 in the set, with AI Usability 80 and AI Visibility 11.5 [S5]. Ask about a specific diagnostic kit and Qiagen surfaces reliably. Ask a broad category question and it comes up about one time in ten.
Once an agent arrives, everything works: server-rendered pages, a working product finder, an add-to-cart that needs no login [S5]. The build is ahead of being found. Pattern one: a surface can be ready long before discovery is.
Allianz: comparison portals capture the category before the brand page.
Allianz scores 3.2 with AI Visibility 19.8 [S6]. Ask an agent for car insurance and it reaches allianz.de about one time in five. Comparison portals such as Check24 and Verivox capture the category first.
Once reached, the surface works: a full browser agent runs the calculator to a quote, while a plain fetch gets a 403 [S6]. The reference page classifies the interception as avoidable, because agents route directly when the prompt names the brand or when the brand's own answers rank above the portals. Pattern two: the channel decides before the surface does.
adidas: the door closes before product and cart.
adidas scores 3.4 with every measured agent class blocked [S7]. Ask an agent to add an Ultraboost 5 to a cart on adidas.de and the answer is an Akamai 403 page at homepage entry, before search or product detail.
The reference page records this as a documented hard-block finding, not a measurement of a working surface, at Confidence D [S7]. Pattern three: a bot wall that turns away crawlers also turns away the agent that came to buy.
Ready but not found. Found but intercepted. Not even through the door.
Talent is measured separately and never blended.
The Talent lane asks a different question: can a candidate's agent find one live software or IT posting on the brand's own career site and reach the application form [S9]? The task was frozen on 2 July 2026, one posting per brand, and no application was submitted anywhere.
AI Usability is measured for 36 of 40 member brands [S9]:
- 26 brands: the agent reached the application form.
- 9 brands: the posting was found and the specification matched, but the form was not reached.
- 1 brand: blocked before the posting could be read.
- 4 brands: no score this wave, because no single posting could be locked for a complete measurement.
AI Visibility for this lane is still pending, so there is no Talent composite. Talent rows never blend into the Commerce ranking above or into any index average. Two lanes, two tables, no mixing.
How to cite these numbers.
The index dataset is published under CC BY 4.0: quote the numbers, name the source, link the index [S1]. The suggested citation and the machine-readable records are below.
Hyperize (2026). DAX 40 Agent Success Index, Wave Q2 2026 Pilot. https://www.hyperize.ai/en/dax40-index
Numbers as published on 2026-09-14. The index is a living dataset and re-scores each wave; this page is the dated record of the Q2 2026 wave.
- DAX 40 Agent Success Index, HTML: https://www.hyperize.ai/en/dax40-index
- DAX 40 Agent Success Index, JSON sibling: https://www.hyperize.ai/en/dax40-index.json
- This article, HTML: https://www.hyperize.ai/en/insights/articles/dax-40-agent-success-2026-the-numbers
- This article, JSON sibling: https://www.hyperize.ai/en/insights/articles/dax-40-agent-success-2026-the-numbers.json
- Agent Success Score, methodology: https://www.hyperize.ai/en/methodology/agent-success-score
- Task Selection Doctrine: https://www.hyperize.ai/en/methodology/task-selection
The numbers move each wave. A brand that wants a different number next wave needs two things: a surface where an agent can finish the task, and an answer agents cite before the portal. The weighting rewards the first at 0.70 and the second at 0.20 [S2].
Questions about the data: hello@hyperize.ai.