--- title: "Can an AI agent buy from DAX companies? | Hyperize" description: "36 DAX companies in the AI agent test: only four pass the test with all four agent types, at two none gets any further. All numbers, CC BY 4.0." canonical: https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company lang: en last-updated: 2026-09-15 --- # Can an AI agent buy from a DAX company? [Home](/en) [Insights](/en/insights) Can an AI agent buy from a DAX company? Original Research 36 DAX companies, one task each, four types of AI agent. Only four companies pass the test with all four agent types. Hyperize 10 min read We will send agents on far more errands than we can imagine today: searching, comparing, requesting, buying, mostly in the background. Many of these errands lead to a company's website. A company that the agent cannot find there, or cannot use, loses the customer without noticing. We wanted to know how well prepared Germany's largest companies are for this, and sent AI agents to 36 DAX companies, each with one real customer task. [S1](#source-s1) The result surprised us. The insights at a glance 1. 01 [Only 11% of DAX companies pass the test with all four agent types.](#insight-1) 2. 02 [The plain text fetch reaches its goal on 39% of websites, the browser agent on 68%.](#insight-2) 3. 03 [Only 39% of DAX websites let the plain text fetch reach its goal.](#insight-3) 4. 04 [No test went as far as the purchase: a cart reached is not a purchase yet.](#insight-4) 5. 05 [97% of DAX companies score fewer than 50 of 100 points on AI visibility.](#insight-5) 6. 06 [AI visibility and usability are practically unrelated in this measurement.](#insight-6) 7. 07 [At 39% of DAX companies, AI points buyers to third parties.](#insight-7) 8. 08 [No company manages both: high AI visibility and the test with all four agent types.](#insight-8) Contents - [01 · Five errands for your agent](#section-01) - [02 · How we measured](#section-02) - [03 · Only four pass the test with all four agent types](#section-03) - [04 · The ranking ends with adidas, Allianz, Bayer, SAP, BMW](#section-04) - [05 · Visible and usable barely relate](#section-05) - [06 · At 14, the purchase goes through third parties](#section-06) - [07 · On the side: the job application](#section-07) - [08 · Three questions for your website](#section-08) - [09 · All 36 numbers to cite](#section-09) 01 ## Imagine your agent has to get five things done today. Send a parcel, book a mobile plan, get a car insurance quote, order a running shoe, request chemicals for the company. Five errands, five DAX brands, one day. The day is invented, the five results are really measured [S1](#source-s1). One day, five errands 07:40 [DHL](/en/dax40-index/brands/dhl) Get the price for a 5 kilo parcel Price on the first fetch: 7.69 euros. Three times through the franking assistant, three times the same price. Result: done 09:15 [Deutsche Telekom](/en/dax40-index/brands/deutsche-telekom) Put a SIM-only plan in the cart 29.95 euros read, cart reached. Without the brand name, though, the AI recommends discount providers first: the customer never sees Telekom at all. Result: done 12:30 [Allianz](/en/dax40-index/brands/allianz) Get a car insurance quote calculated The browser agent calculates all the way to the quote. The plain fetch gets a 403 error, so no access. Result: partly done 15:00 [adidas](/en/dax40-index/brands/adidas) Put a running shoe in the cart Error page right on the homepage, for every type of agent. The agent has to give up. Result: turned away 17:30 [Brenntag](/en/dax40-index/brands/brenntag) Request a 200 litre drum of isopropanol The page can be read, but the details needed to order are missing. The enquiry form stops at mandatory fields: the request never arrives. Result: partly done Cyan: the agent got as far as the goal of the task (cart, quote or order-ready price). Outlined: only partly. Dark: test not successful. Nothing was bought, that was never the task. The same agent, five websites, three different outcomes. At DHL the parcel price is there, machine-readable; at adidas an error page appears before the agent sees a shoe [S9](#source-s9) [S7](#source-s7). The agent has to give up. The customer who sent it gets the shoe somewhere else, or not at all. Whether an agent completes its errand is not decided by the agent alone. The website it lands on decides too. That is exactly what we measured at all 36 companies. How, is in the next chapter. What came out of it, in the four after that. > The same agent, five websites, three different outcomes. The website, too, decides whether the agent completes its errand. Insight 1 of 8 ### Only 11% of DAX companies pass the test with all four agent types. Four technical ways of accessing a website, one real customer task per company. Passing means: every agent type reaches the goal set for it (from a readable price to the cart). No purchase. 11% of DAX companies (4 of 36) pass the test with all four agent types 4 all four pass 32 at least one fails or only partly Why this matters At the other 89%, at least one agent type fails or gets only part of the way to its goal. [Save as image](/og/stat/insight-1.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-1) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) 02 ## How we measured. A purchase is not a single click but a series of steps. The agent has to find the brand, get onto the website, read the offer, choose the right variant and get through to the cart or the quote. It can fail at any step. find arrive read choose complete The [DAX 40 Agent Success Index](/en/dax40-index) measures exactly where [S1](#source-s1). Each brand gets one task, set and published before the measurement so that nobody picks the easiest one afterwards [S3](#source-s3). Then four technical ways of accessing a website attempt the task; we call them agent types. The four differ a lot, and that decides a great deal later on: Agent type 1 Plain fetch Loads only the text of the page, without images, without clicks, without programs in the background. What is not written here does not exist for it. This is how AI search engines read most pages today when they cite a source. Agent type 2 Script A program that calls up pages, pulls out data and fills in forms. It can calculate, but it cannot see what happens on the screen. This is how price comparison sites, shopping bots and many home-built company tools work. Agent type 3 Browser agent Controls a real browser: clicks, scrolls, reads the page the way a human sees it. Slow, but closest to a human. This is how the agents in ChatGPT, Claude and Gemini work when they get something done for you. Agent type 4 Autonomous agent Plans by itself, tries out routes, switches to another one when blocked, calls other tools. Needs no step-by-step instructions. This is what the buying agents now emerging look like. So there is no such thing as the one AI agent. There are four types with four different sets of abilities, and they are developing fast. A website that lets the browser agent through may lock out the plain fetch, the one AI search engines use today to read and cite pages. These four types appear as columns in every chart in this article, in exactly this order. Insight 2 of 8 ### The more an AI agent works like a human, the more often it reaches its goal. Share of tested websites on which the agent type reached its goal. The agent types ran on different numbers of websites (36, 36, 22, 18); no direct comparison on the same websites. 39 → 68% success rate from the plain text fetch to the browser agent Plain fetch (reads text only)39% · 14 of 36 Script (pulls data)33% · 12 of 36 Browser agent (clicks like a human)68% · 15 of 22 Autonomous agent (plans by itself)67% · 12 of 18 Why this matters A website that only lets the clicking agent through is only partly usable, or not usable at all, for the programs that only read pages. [Save as image](/og/stat/insight-2.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-2) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) Two values per brand. First, visibility to AI, called [AI Visibility](https://www.hyperize.ai/en/methodology/agent-success-score) in the index. It is a score from 0 to 100: do AI assistants such as ChatGPT find and recommend the brand when nobody names it? It bundles several signals from the answers and is not a simple mention rate. Second, usability for agents, AI Usability in the index: can an agent that has arrived on the website take the task there to the defined endpoint? The endpoint is defined per task: a cart, a quote or an order-ready price. No task involves buying; a cart reached is not a completed purchase yet. Both values (0 to 100) are weighted, added up and divided by ten: one number from 0 to 10 [S2](#source-s2). Usability counts 0.70, visibility to AI 0.20, the quality of the evidence 0.10. 36 of the 40 DAX companies have both values in the measurement round of the second quarter of 2026 (the index calls it wave Q2 2026 Pilot). Scout24 is measured as a marketplace in its own lane, Hochtief joins in the next round. RWE and Deutsche Börse have no purchase on their website that could be measured [S1](#source-s1). This round is a pilot measurement: one task per company. The full methodology provides for several tasks per company [S3](#source-s3). The published results can be checked; how the individual runs feed into the two values stays internal [S2](#source-s2). Confidence Most brands carry confidence grade C. That means: one measured task, one measurement round. Qiagen carries B because the data are complete. adidas and Zalando carry D because no agent type got as far as a working page [S1](#source-s1). 03 ## Only four of 36 companies pass the test with all four agent types. Only at Telekom, Qiagen, DHL, Infineon did each of the four agent types reach its goal [S4](#source-s4) [S5](#source-s5) [S9](#source-s9) [S10](#source-s10). Goal means something different per type: the plain fetch has to be able to read the price, the browser agent has to get to the cart or the quote. At adidas and Zalando no agent type got any further. adidas shows an error page right on the homepage, at Zalando no agent gets as far as the cart [S7](#source-s7) [S11](#source-s11). For a customer who lets an agent do the shopping, these two shops do not exist at that moment. At the remaining 30, it depends on the type of agent. The one that fails most often is the simplest, which only reads the text of the page. On ten of 36 websites it gets nowhere, on 12 only part of the way [S1](#source-s1). That hits the kind of fetch many AI systems use to read pages before they cite a source. The browser agent gets furthest, reaching its goal on 15 of 22 tested websites. Failed does not always mean locked out. Some websites reject programs, some show them only an empty shell without content, on some the details that belong to the task are missing. In the chart, those are the dark cells. Cells with a light outline mean: no result has been published yet for this agent type. Finding 1 · Who reaches the goal Which type of agent reaches the goal of the task at which company? Four cells per company, one per agent type. Cyan: this agent reached its goal on the company's website (from a readable price to the cart or quote). Light cyan: partly. Dark: test not successful (block, empty shell or missing information). Outlined: no result published. Ordered by score. goal reachedpartlytest not successfulno result published Brand Plain fetch Script Browser agent Autonomous agent Score 1 [Deutsche Telekom](/en/dax40-index/brands/deutsche-telekom) 7.0 2 [Qiagen](/en/dax40-index/brands/qiagen) 6.8 3 [DHL Group](/en/dax40-index/brands/dhl) 6.5 4 [Infineon](/en/dax40-index/brands/infineon) 6.2 5 [Siemens](/en/dax40-index/brands/siemens) 5.6 6 [Merck](/en/dax40-index/brands/merck) 5.2 7 [Deutsche Bank](/en/dax40-index/brands/deutsche-bank) 4.9 8 [MTU Aero Engines](/en/dax40-index/brands/mtu-aero-engines) 4.8 9 [Commerzbank](/en/dax40-index/brands/commerzbank) 4.8 10 [Fresenius Medical Care](/en/dax40-index/brands/fresenius-medical-care) 4.7 11 [Siemens Energy](/en/dax40-index/brands/siemens-energy) 4.6 12 [Fresenius](/en/dax40-index/brands/fresenius) 4.6 13 [Symrise](/en/dax40-index/brands/symrise) 4.5 14 [Vonovia](/en/dax40-index/brands/vonovia) 4.4 15 [Hannover Rück](/en/dax40-index/brands/hannover-rueck) 4.4 16 [Munich Re](/en/dax40-index/brands/munich-re) 4.2 17 [GEA Group](/en/dax40-index/brands/gea-group) 4.1 18 [Henkel](/en/dax40-index/brands/henkel) 4.1 19 [BASF](/en/dax40-index/brands/basf) 4.1 20 [Volkswagen](/en/dax40-index/brands/volkswagen) 4.1 21 [Beiersdorf](/en/dax40-index/brands/beiersdorf) 4.1 22 [Siemens Healthineers](/en/dax40-index/brands/siemens-healthineers) 4.0 23 [Mercedes-Benz](/en/dax40-index/brands/mercedes-benz) 4.0 24 [Rheinmetall](/en/dax40-index/brands/rheinmetall) 3.7 25 [Daimler Truck](/en/dax40-index/brands/daimler-truck) 3.7 26 [E.ON](/en/dax40-index/brands/eon) 3.7 27 [Airbus](/en/dax40-index/brands/airbus) 3.6 28 [Continental](/en/dax40-index/brands/continental) 3.6 29 [Heidelberg Materials](/en/dax40-index/brands/heidelberg-materials) 3.6 30 [Zalando](/en/dax40-index/brands/zalando) 3.5 31 [adidas](/en/dax40-index/brands/adidas) 3.4 32 [Allianz](/en/dax40-index/brands/allianz) 3.2 33 [Bayer](/en/dax40-index/brands/bayer) 3.1 34 [SAP](/en/dax40-index/brands/sap) 3.1 35 [BMW](/en/dax40-index/brands/bmw) 3.0 36 [Brenntag](/en/dax40-index/brands/brenntag) 2.5 Source: Hyperize DAX 40 Agent Success Index, wave Q2 2026 Pilot, status per agent type and brand, as of 2026-09-14. Insight 3 of 8 ### Only 39% of DAX websites let the plain text fetch reach its goal, the agent that only reads pages. The plain text fetch loads only the text of a page, without clicks and without programs running in the background. Failing here means: an access block, an empty page shell or missing information, and all three occur. 39% of DAX websites (14 of 36) let the plain text fetch reach its goal 14 reached the goal 12 partly 10 failed Why this matters This is how many AI systems read pages before they cite a source. What this fetch cannot read, it cannot repeat. [Save as image](/og/stat/insight-3.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-3) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) > Whether an agent gets any further is usually decided on the first call to the website, before it sees an offer. 04 ## The ranking ends with adidas, Allianz, Bayer, SAP and BMW. At the top are a telecoms group, a lab supplier, a logistics company and a chipmaker: Deutsche Telekom with 7.0 of 10, then Qiagen, DHL and Infineon [S1](#source-s1). The last seven places go to Zalando (3.5), adidas (3.4), Allianz (3.2), Bayer (3.1), SAP (3.1), BMW (3.0), Brenntag (2.5). Six of them are names everyone knows. The reasons are different every time. SAP rejects simple agents, and in the answers examined the AI points to implementation partners such as Accenture, Deloitte or Capgemini [S13](#source-s13). At BMW a simple program cannot read a price in the configurator [S14](#source-s14). At Bayer the agent finds Aspirin Forte, but no product page and no buy button [S15](#source-s15). Six brands score 5.0 or more. Thirteen stay below 4.0. The median is 4.1: the typical DAX company reaches less than half of the possible points. By sector, Logistics (6.5, one brand), Tech & Telecom (5.0), Industrials (4.9) and Pharma (4.9) lead, Automotive (3.7) and Chemicals (3.7) trail [S1](#source-s1). Finding 2 · The ranking Agent Success Score, 36 brands, 0 to 10 Cyan: 5.0 points or more. The dashed line marks 5.0. Below it is the middle (median): the value that half of the companies reach. Each brand links to its reference page with task, measured values and sources. The full table with both values is below, for citing. 1 [Deutsche Telekom](/en/dax40-index/brands/deutsche-telekom) 7.0 2 [Qiagen](/en/dax40-index/brands/qiagen) 6.8 3 [DHL Group](/en/dax40-index/brands/dhl) 6.5 4 [Infineon](/en/dax40-index/brands/infineon) 6.2 5 [Siemens](/en/dax40-index/brands/siemens) 5.6 6 [Merck](/en/dax40-index/brands/merck) 5.2 7 [Deutsche Bank](/en/dax40-index/brands/deutsche-bank) 4.9 8 [MTU Aero Engines](/en/dax40-index/brands/mtu-aero-engines) 4.8 9 [Commerzbank](/en/dax40-index/brands/commerzbank) 4.8 10 [Fresenius Medical Care](/en/dax40-index/brands/fresenius-medical-care) 4.7 11 [Siemens Energy](/en/dax40-index/brands/siemens-energy) 4.6 12 [Fresenius](/en/dax40-index/brands/fresenius) 4.6 13 [Symrise](/en/dax40-index/brands/symrise) 4.5 14 [Vonovia](/en/dax40-index/brands/vonovia) 4.4 15 [Hannover Rück](/en/dax40-index/brands/hannover-rueck) 4.4 16 [Munich Re](/en/dax40-index/brands/munich-re) 4.2 17 [GEA Group](/en/dax40-index/brands/gea-group) 4.1 18 [Henkel](/en/dax40-index/brands/henkel) 4.1 19 [BASF](/en/dax40-index/brands/basf) 4.1 20 [Volkswagen](/en/dax40-index/brands/volkswagen) 4.1 21 [Beiersdorf](/en/dax40-index/brands/beiersdorf) 4.1 22 [Siemens Healthineers](/en/dax40-index/brands/siemens-healthineers) 4.0 23 [Mercedes-Benz](/en/dax40-index/brands/mercedes-benz) 4.0 24 [Rheinmetall](/en/dax40-index/brands/rheinmetall) 3.7 25 [Daimler Truck](/en/dax40-index/brands/daimler-truck) 3.7 26 [E.ON](/en/dax40-index/brands/eon) 3.7 27 [Airbus](/en/dax40-index/brands/airbus) 3.6 28 [Continental](/en/dax40-index/brands/continental) 3.6 29 [Heidelberg Materials](/en/dax40-index/brands/heidelberg-materials) 3.6 30 [Zalando](/en/dax40-index/brands/zalando) 3.5 31 [adidas](/en/dax40-index/brands/adidas) 3.4 32 [Allianz](/en/dax40-index/brands/allianz) 3.2 33 [Bayer](/en/dax40-index/brands/bayer) 3.1 34 [SAP](/en/dax40-index/brands/sap) 3.1 35 [BMW](/en/dax40-index/brands/bmw) 3.0 36 [Brenntag](/en/dax40-index/brands/brenntag) 2.5 5.0 Median 4.1 Source: Hyperize DAX 40 Agent Success Index, wave Q2 2026 Pilot, as of 2026-09-14. Score = (AI Visibility × 0.20) + (AI Usability × 0.70) + (Evidence × 0.10), divided by 10. CC BY 4.0. > The typical DAX company reaches 4.1 of 10 points. No agent bought anything, not even at the very top, because no test went as far as the purchase. Measurement ends at the cart, the quote or the order-ready price. Beyond that, where the agents got furthest, a customer account, a login or an identity check begins, at DHL a login before payment, which no agent tested [S9](#source-s9) [S10](#source-s10) [S16](#source-s16) [S17](#source-s17) [S18](#source-s18). A cart reached is not a purchase yet. The last step still belongs to the human. Insight 4 of 8 ### A cart reached is not a purchase yet: the last step was tested nowhere. Purchases were not part of the tasks. Where agents got furthest, the next step sat behind an account, a login or an identity check; whether an agent can pass it was not examined. 0 tests went as far as the purchase, across 36 DAX companies find website offer cart end of measurement purchase not examined agent gets there not examined Why this matters The last step still belongs to the human. Anyone who wants agents to really buy has to build and measure it next. [Save as image](/og/stat/insight-4.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-4) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) 05 ## Visible to AI and usable for agents barely relate. Insight 5 of 8 ### 97% of DAX companies score fewer than 50 of 100 points on AI visibility. AI visibility: a score from 0 to 100 for whether AI assistants find and recommend the brand when nobody names it; it bundles several signals and is not a simple mention rate. Each column is one company, without names. 97% of DAX companies (35 of 36) score below 50 of 100 points on AI visibility half of the points 36 companies, one column each, sortedof 100 points Why this matters On average 37 of 100 points. Being well known and being found and recommended by AI are two different things. [Save as image](/og/stat/insight-5.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-5) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) Being well visible to AI does not give a company a better website for agents. Qiagen has the website every agent type can use, usability 80, but scores 11.5 of 100 points on visibility to AI. Its reference page names the brand about once in ten cases on broad questions [S5](#source-s5). Rheinmetall, Airbus and Volkswagen score between 44 and 50 points on visibility, and then the agent gets no further on the website: usability 30, 30 and 34 [S1](#source-s1). Across all 36, there is practically no linear relationship between the two values: the correlation coefficient is −0.02 (Pearson, 36 pairs of values) [S1](#source-s1). 10 companies sit above both median lines, none by much; DHL, with visibility 46 and usability 68, gets furthest towards the top right [S9](#source-s9). Anyone who only measures how visible their brand is to AI knows little, in these data, about how far an agent gets on their website. Both have to be right, otherwise the purchase stalls. Finding 3 · Visible and usable All 36 companies by visibility to AI and usability for agents To the right: visibility to AI, whether AI assistants find and recommend the brand when nobody names it (AI Visibility, 0 to 100 points). Upwards: how far an agent gets on the company's own website (AI Usability, 0 to 100). The dashed lines are the middle (median) of both values. Relationship: r = −0.02 (Pearson), practically no linear relationship in this sample. Source: Hyperize DAX 40 Agent Success Index, wave Q2 2026 Pilot, as of 2026-09-14. Insight 6 of 8 ### Whether AI finds and recommends a brand says little, in this measurement, about how far an agent gets on its website. Each dot is one company: AI visibility to the right, usability upwards. Statistically r = −0.02 in this sample, so practically no linear relationship; no proof of independence. No relationship between AI visibility and usability for agents, in this measurement Why this matters Measuring visibility is not enough. Your own website is a second lever, and in these data it does not depend on visibility. [Save as image](/og/stat/insight-6.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-6) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) 06 ## At 14 companies, according to AI answers, the purchase goes through third parties. At 14 of the 36 companies, third parties regularly come before the brand in the AI answers to the task. That means a comparison portal, a retailer, a broker or an IT service provider [S1](#source-s1). The index classifies this as structural, because in these industries the purchase usually happens there. What is measured are mentions in AI answers, not purchases. Henkel and Beiersdorf explain their product, dm, Rossmann and Amazon sell it. SAP describes the software, Accenture and Deloitte implement it. Munich Re and Hannover Rück are named, the contract is placed by Aon and Guy Carpenter, two large insurance brokers. A retailer, a broker and a competitor are not the same thing; each brand's reference page names exactly who comes before it. At two companies the third party is avoidable: Deutsche Telekom and Allianz. There the agent reaches the brand directly as soon as the question names the brand, or the brand itself gives the best answer to the general question [S4](#source-s4) [S6](#source-s6). At 13 companies nobody stands in between in the evaluated answers; there, the company's own website alone decides. At seven companies this evaluation is still open. Finding 4 · The purchase through third parties How often does AI name a third party instead of the brand? Share of AI answers that name a third party for the company's task (comparison portal, retailer, broker, IT service provider), as published on the brand's reference page. What is measured are mentions, not purchases. Structural: in this industry the purchase usually goes through third parties. Avoidable: the brand can win the answer back. Companies without evaluated answers are missing. [Vonovia](/en/dax40-index/brands/vonovia) structural 83% Immowelt · ImmoScout24 · wg-gesucht [Siemens Energy](/en/dax40-index/brands/siemens-energy) structural 70% Bechtel · Fluor · Hitachi Energy [Hannover Rück](/en/dax40-index/brands/hannover-rueck) structural 70% Aon · Guy Carpenter · Gallagher Re [Munich Re](/en/dax40-index/brands/munich-re) structural 70% Aon · Guy Carpenter · Gallagher Re [Henkel](/en/dax40-index/brands/henkel) structural 70% dm · Rossmann · Edeka [SAP](/en/dax40-index/brands/sap) structural 70% Accenture · Deloitte · Capgemini [GEA Group](/en/dax40-index/brands/gea-group) structural 65% Tetra Pak engineering · Andritz · Bühler [BASF](/en/dax40-index/brands/basf) structural 65% Amazon · Bauhaus · OBI [Beiersdorf](/en/dax40-index/brands/beiersdorf) structural 65% dm · Rossmann · Müller [Daimler Truck](/en/dax40-index/brands/daimler-truck) structural 65% Mercedes-Benz truck dealer network · fleet-leasing firms · TruckStore used-fleet channel [Continental](/en/dax40-index/brands/continental) structural 65% Reifen.de · Tirendo · Euromaster [Zalando](/en/dax40-index/brands/zalando) structural 61% Amazon · About You · Nike.de [Siemens Healthineers](/en/dax40-index/brands/siemens-healthineers) structural 60% University-hospital procurement · Hospital group purchasing organizations · Vizient-equivalent GPOs [E.ON](/en/dax40-index/brands/eon) structural 56% Verivox · Check24 · Stromauskunft [Deutsche Telekom](/en/dax40-index/brands/deutsche-telekom) avoidable 22% Check24 · Verivox [Allianz](/en/dax40-index/brands/allianz) avoidable 22% check24 · verivox · tarifcheck Source: Hyperize DAX 40 Agent Success Index, wave Q2 2026 Pilot, intermediary share per brand, as of 2026-09-14. Insight 7 of 8 ### At 39% of DAX companies, AI points buyers to retailers, portals, brokers or integrators. Counted are mentions in AI answers, not purchases. Structural means: in this industry the purchase usually goes through third parties. At 7 companies this evaluation is still open. 39% of DAX companies (14 of 36): according to AI answers, the purchase goes through third parties 14 2 13 7 14 companies: through third parties, structural2 companies: through third parties, avoidable13 companies: brand directly7 companies: not yet evaluated Why this matters The customer still comes, but through someone who has a say in the terms. At these 14, on average 67 of 100 answers name the third party. [Save as image](/og/stat/insight-7.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-7) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) 07 ## Measured on the side: 26 of 36 career sites let the agent get as far as the start of the application. The index also measures a second lane, separate and never combined with the first. Can an applicant's agent find an open IT job on the brand's career site and get as far as the start of the application? Start means: the application can begin, at some brands behind a login. Task frozen on 2 July 2026, one job per brand, no application was submitted [S12](#source-s12). On the side · The job application 40 DAX members → 36 measured → 26 to the start of the application 36 of the 40 members are measured [S12](#source-s12): - 26 times the agent reached the start of the application. - 9 times it found the job and compared the requirements, but did not get as far as the start. - 1 time the agent was turned away. - 4 times no complete measurement came about. There is no overall figure for this lane yet. Visibility to AI is missing, and without both values there is no score. 08 ## Three questions for your own website. Insight 8 of 8 ### Not a single DAX company manages both: high AI visibility and the test with all four agent types. High visibility: at least 50 of 100 points. Test passed: all four agent types reach their goal. Both thresholds are choices made by this article. 0 DAX companies manage both: 50 visibility points and the test with all four agent types test passed with all four not passed visibility 50 and above 0 1 visibility below 50 4 31 36 companies, the count per cell. Visibility: points from 0 to 100. Why this matters Every company has at least one of the two problems open, 31 have both. [Save as image](/og/stat/insight-8.png) [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.hyperize.ai%2Fen%2Finsights%2Farticles%2Fcan-an-ai-agent-buy-from-a-dax-company%23insight-8) Source: Hyperize, DAX 40 Agent Success Index, Q2 2026 (36 of 40 companies measured, pilot round with one task per company) · CC BY 4.0 · As of 14 September 2026 [How we measure →](#section-02) This is only the beginning: which tasks agents will take on in future is open, and their number is growing. A company that turns every agent away today can look completely different in the next measurement round. Three questions decide that, and all three are in these numbers. - Does AI find and recommend your brand when nobody names it? - Does every agent type reach its goal on your website, including the simplest one, which only reads? - Who does AI send buyers to, you or a third party? The index weights usability (0.70) higher than visibility to AI (0.20) [S2](#source-s2); which bottleneck comes first for a company is shown by its result on each value. We measure again in measurement round Q3 2026, with Hochtief and the next round of sectors. The numbers stay public. Hyperize does not only measure this, it builds the pages through which AI agents can understand an offer and take the next step. The free [Agent Success Snapshot](/en#snapshot) shows, for one brand, where agents get further today and where they give up. 09 ## All 36 numbers to cite. The eight insights are above, each in its place, each with a sentence and an image. What follows here are the licence, the data and the full table. To cite Hyperize (2026). DAX 40 Agent Success Index, Wave Q2 2026 Pilot. https://www.hyperize.ai/en/dax40-index Data licence [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/): cite the numbers, name the source, link to the index. Numbers as of 2026-09-14. This page is the dated record of measurement round Q2 2026; the index itself keeps measuring. - DAX 40 Agent Success Index, HTML: [https://www.hyperize.ai/en/dax40-index](https://www.hyperize.ai/en/dax40-index) - DAX 40 Agent Success Index, JSON twin (the same data in a format for programs): [https://www.hyperize.ai/en/dax40-index.json](https://www.hyperize.ai/en/dax40-index.json) - This page, HTML: [https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company](https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company) - This page, JSON twin: [https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company.json](https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company.json) - All 36 values as CSV: [https://www.hyperize.ai/data/dax40-agent-success-q2-2026.csv](https://www.hyperize.ai/data/dax40-agent-success-q2-2026.csv) - Agent Success Score, methodology: [https://www.hyperize.ai/en/methodology/agent-success-score](https://www.hyperize.ai/en/methodology/agent-success-score) - Task selection (Task Selection Doctrine): [https://www.hyperize.ai/en/methodology/task-selection](https://www.hyperize.ai/en/methodology/task-selection) For humans, the ranking is above. For machines and for citing, the same table with both values follows. To cite · 36 brands · wave Q2 2026 Pilot | Rank | Brand | Ticker | Sector | AI Visibility | AI Usability | Evidence | Score | | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | [Deutsche Telekom](/en/dax40-index/brands/deutsche-telekom) | DTE | Tech & Telecom | 33.8 | 80 | 70 | 7.0 | | 2 | [Qiagen](/en/dax40-index/brands/qiagen) | QIA | Pharma & Healthcare | 11.5 | 80 | 98 | 6.8 | | 3 | [DHL Group](/en/dax40-index/brands/dhl) | DHL | Logistics | 46.0 | 68 | 85 | 6.5 | | 4 | [Infineon](/en/dax40-index/brands/infineon) | IFX | Industrials | 39.1 | 68 | 70 | 6.2 | | 5 | [Siemens](/en/dax40-index/brands/siemens) | SIE | Industrials | 44.0 | 57 | 70 | 5.6 | | 6 | [Merck](/en/dax40-index/brands/merck) | MRK | Pharma & Healthcare | 38.3 | 54 | 68 | 5.2 | | 7 | [Deutsche Bank](/en/dax40-index/brands/deutsche-bank) | DBK | Insurance & Finance | 40.5 | 48 | 70 | 4.9 | | 8 | [MTU Aero Engines](/en/dax40-index/brands/mtu-aero-engines) | MTX | Aerospace & Defense | 52.5 | 45 | 65 | 4.8 | | 9 | [Commerzbank](/en/dax40-index/brands/commerzbank) | CBK | Insurance & Finance | 38.0 | 48 | 70 | 4.8 | | 10 | [Fresenius Medical Care](/en/dax40-index/brands/fresenius-medical-care) | FME | Pharma & Healthcare | 45.0 | 44 | 70 | 4.7 | | 11 | [Siemens Energy](/en/dax40-index/brands/siemens-energy) | ENR | Industrials | 41.9 | 45 | 65 | 4.6 | | 12 | [Fresenius](/en/dax40-index/brands/fresenius) | FRE | Pharma & Healthcare | 40.6 | 44 | 70 | 4.6 | | 13 | [Symrise](/en/dax40-index/brands/symrise) | SY1 | Chemicals & Materials | 36.3 | 44 | 65 | 4.5 | | 14 | [Vonovia](/en/dax40-index/brands/vonovia) | VNA | Real Estate | 42.8 | 41 | 70 | 4.4 | | 15 | [Hannover Rück](/en/dax40-index/brands/hannover-rueck) | HNR1 | Insurance & Finance | 28.2 | 45 | 65 | 4.4 | | 16 | [Munich Re](/en/dax40-index/brands/munich-re) | MUV2 | Insurance & Finance | 44.2 | 38 | 65 | 4.2 | | 17 | [GEA Group](/en/dax40-index/brands/gea-group) | G1A | Industrials | 40.3 | 38 | 65 | 4.1 | | 18 | [Henkel](/en/dax40-index/brands/henkel) | HEN3 | Consumer & Retail | 35.3 | 39 | 65 | 4.1 | | 19 | [BASF](/en/dax40-index/brands/basf) | BAS | Chemicals & Materials | 37.7 | 39 | 60 | 4.1 | | 20 | [Volkswagen](/en/dax40-index/brands/volkswagen) | VOW3 | Automotive | 49.7 | 34 | 70 | 4.1 | | 21 | [Beiersdorf](/en/dax40-index/brands/beiersdorf) | BEI | Consumer & Retail | 34.4 | 39 | 65 | 4.1 | | 22 | [Siemens Healthineers](/en/dax40-index/brands/siemens-healthineers) | SHL | Industrials | 33.3 | 38 | 65 | 4.0 | | 23 | [Mercedes-Benz](/en/dax40-index/brands/mercedes-benz) | MBG | Automotive | 43.6 | 34 | 70 | 4.0 | | 24 | [Rheinmetall](/en/dax40-index/brands/rheinmetall) | RHM | Aerospace & Defense | 49.4 | 30 | 65 | 3.7 | | 25 | [Daimler Truck](/en/dax40-index/brands/daimler-truck) | DTG | Automotive | 21.4 | 38 | 65 | 3.7 | | 26 | [E.ON](/en/dax40-index/brands/eon) | EOAN | Utilities | 26.3 | 35 | 70 | 3.7 | | 27 | [Airbus](/en/dax40-index/brands/airbus) | AIR | Aerospace & Defense | 43.9 | 30 | 65 | 3.6 | | 28 | [Continental](/en/dax40-index/brands/continental) | CON | Automotive | 26.4 | 34 | 65 | 3.6 | | 29 | [Heidelberg Materials](/en/dax40-index/brands/heidelberg-materials) | HEI | Chemicals & Materials | 40.2 | 30 | 65 | 3.6 | | 30 | [Zalando](/en/dax40-index/brands/zalando) | ZAL | Consumer & Retail | 43.3 | 28 | 70 | 3.5 | | 31 | [adidas](/en/dax40-index/brands/adidas) | ADS | Consumer & Retail | 35.0 | 28 | 70 | 3.4 | | 32 | [Allianz](/en/dax40-index/brands/allianz) | ALV | Insurance & Finance | 19.8 | 30 | 70 | 3.2 | | 33 | [Bayer](/en/dax40-index/brands/bayer) | BAYN | Pharma & Healthcare | 22.1 | 30 | 53 | 3.1 | | 34 | [SAP](/en/dax40-index/brands/sap) | SAP | Tech & Telecom | 29.4 | 26 | 65 | 3.1 | | 35 | [BMW](/en/dax40-index/brands/bmw) | BMW | Automotive | 37.6 | 23 | 65 | 3.0 | | 36 | [Brenntag](/en/dax40-index/brands/brenntag) | BNR | Chemicals & Materials | 24.2 | 19 | 70 | 2.5 | Source: Hyperize DAX 40 Agent Success Index, wave Q2 2026 Pilot, published on 2026-09-14. Score = (AI Visibility × 0.20) + (AI Usability × 0.70) + (Evidence × 0.10), divided by 10. All values are Hyperize's own measurements. CC BY 4.0. Questions about the data: [hello@hyperize.ai](mailto:hello@hyperize.ai). Sources ## Evidence and provenance. All sources are Hyperize's own measurements, published on the index and on the brands' reference pages. Hyperize does not only measure, it also builds the solutions that improve these values; the methodology is public, the values can be checked under CC BY 4.0. \[S1\] DAX 40 Agent Success Index, wave Q2 2026 Pilot (HTML page and JSON twin) Hyperize, own measurement · 2026-09-14 All 36 scores on both axes, AI Visibility and AI Usability per brand, status per agent type, intermediary classification and shares, coverage (36 of 40, marketplace lane, one brand in the next wave, two exclusions), confidence grades, licence CC BY 4.0. Retrieved on 2026-09-14, index last modified 2026-07-21. https://www.hyperize.ai/en/dax40-index \[S2\] Agent Success Score: methodology Hyperize, own measurement · 2026-09-14 The two measured axes, the quality of the evidence, the public weighting 0.20 / 0.70 / 0.10 and the 0 to 10 scale. https://www.hyperize.ai/en/methodology/agent-success-score \[S3\] Task Selection Doctrine Hyperize, own measurement · 2026-09-14 Tasks are frozen and published before the wave, one task per brand, fairness rules across brands. https://www.hyperize.ai/en/methodology/task-selection \[S4\] Deutsche Telekom, reference page Hyperize, own measurement · 2026-09-14 Score 7.0. Every agent type reads the plan price of 29.95 euros, the browser agent reaches the cart in the live shop; without the brand name, discount providers answer first (Lebara, sim.de). Third party avoidable. https://www.hyperize.ai/en/dax40-index/brands/deutsche-telekom \[S5\] Qiagen, reference page Hyperize, own measurement · 2026-09-14 Score 6.8, confidence grade B, AI Visibility 11.5, AI Usability 80. Server-rendered pages, product finder, cart without login; broad category questions name the brand about once in ten cases; measured in English. https://www.hyperize.ai/en/dax40-index/brands/qiagen \[S6\] Allianz, reference page Hyperize, own measurement · 2026-09-14 Score 3.2, AI Visibility 19.8. On the car insurance task, the AI names allianz.de about once in five cases; Check24 and Verivox come before it; the browser agent runs the premium calculator all the way to the quote, a plain fetch gets 403. Third party avoidable. https://www.hyperize.ai/en/dax40-index/brands/allianz \[S7\] adidas, reference page Hyperize, own measurement · 2026-09-14 Score 3.4, confidence grade D. Akamai 403 page at the homepage entry for every measured agent type on the cart task; documented hard block, no measurement of a working page. https://www.hyperize.ai/en/dax40-index/brands/adidas \[S8\] Brenntag, reference page Hyperize, own measurement · 2026-09-14 Score 2.5. The frozen specification (technical isopropanol, 200 litre drum, delivery in North Rhine-Westphalia) cannot be confirmed on the public page; the enquiry form stops at a validation wall. https://www.hyperize.ai/en/dax40-index/brands/brenntag \[S9\] DHL Group, reference page Hyperize, own measurement · 2026-09-14 Score 6.5, AI Visibility 46.0, AI Usability 68. Price of 7.69 euros machine-readable on the first fetch; three browser runs through the franking assistant without login, zero deviation; the final checkout sits behind a login. https://www.hyperize.ai/en/dax40-index/brands/dhl \[S10\] Infineon, reference page Hyperize, own measurement · 2026-09-14 Score 6.2. Every agent type holds the specification from the part finder to the distributor cart; cart and checkout require a registered account. https://www.hyperize.ai/en/dax40-index/brands/infineon \[S11\] Zalando, reference page Hyperize, own measurement · 2026-09-14 Score 3.5, confidence grade D. Findable, not completable: a plain fetch hits an Akamai block, three browser runs do not reach the size 43 variant, the checkout hangs on a session. https://www.hyperize.ai/en/dax40-index/brands/zalando \[S12\] DAX 40 Agent Success Index, Talent lane (Talent view of the hub and talentLane block of the JSON twin) Hyperize, own measurement · 2026-09-14 Task frozen on 2026-07-02; AI Usability measured for 36 of 40 members: 26 to the application form, 9 to the requirements match, 1 blocked, 4 without measurement; AI Visibility open, no overall figure; Talent rows are never combined with the Commerce ranking. https://www.hyperize.ai/en/dax40-index.json \[S13\] SAP, reference page Hyperize, own measurement · 2026-09-14 Score 3.1. sap.com rejects plain fetches and scripts at the network edge (403 on every page), a browser agent gets through and reaches the demo request form. Systems integrators such as Accenture, Deloitte, Capgemini and PwC handle the close. Structurally through third parties, 70 percent of answers. https://www.hyperize.ai/en/dax40-index/brands/sap \[S14\] BMW, reference page Hyperize, own measurement · 2026-09-14 Score 3.0. Plain fetch and script read no price, because the configurator renders its content in shadow DOM components; the browser agent configures the 318i in one of three runs. https://www.hyperize.ai/en/dax40-index/brands/bmw \[S16\] Siemens, reference page Hyperize, own measurement · 2026-09-14 The browser agent configures the controller and reaches the order list in three of three runs; the order itself sits behind a Siemens ID login, which no agent passed. https://www.hyperize.ai/en/dax40-index/brands/siemens \[S17\] Deutsche Bank, reference page Hyperize, own measurement · 2026-09-14 Every agent type finds the account and the price, the browser agent reaches the account opening flow without login; the application stops at the identity and KYC check. https://www.hyperize.ai/en/dax40-index/brands/deutsche-bank \[S18\] Commerzbank, reference page Hyperize, own measurement · 2026-09-14 Found and form-ready across every agent type; the account opening stops at the identity and KYC check. https://www.hyperize.ai/en/dax40-index/brands/commerzbank \[S15\] Bayer, reference page Hyperize, own measurement · 2026-09-14 Score 3.1. Plain fetch and script get an Akamai 403 page. The browser agent reaches aspirin.de and confirms Aspirin Forte 1000 mg, but the product has no product page of its own and no buy button. The pharmacy route only works for the 500 mg variant. https://www.hyperize.ai/en/dax40-index/brands/bayer Next ## Three ways forward. Into the methodology. Into the index. [ Methodology · Agent Success Score ### Two values, one number. How visibility to AI (AI Visibility) and usability for agents (AI Usability) are measured, how the 0.20 / 0.70 / 0.10 weighting comes about and why the quality of the evidence is not a third value. Read the methodology](/en/methodology/agent-success-score)[ Index · DAX 40 Agent Success ### The living dataset behind this story. 36 brands with one reference page each: the task, both values, the status per agent type, the sources and a JSON twin for agents. Open the index](/en/dax40-index)[ Snapshot · your brand ### The same measurement, out of turn. A free Agent Success Snapshot for one brand, on the same two values, result in about 48 hours. The form is on the homepage. Get a free snapshot](/en#snapshot) Last checked · 2026-09-15 Next check · 2026-11-14 Tier · B (from measurement) Confidence · C (one task per brand; Qiagen B, adidas and Zalando D) Measurement round · Q2 2026 Pilot · as of 2026-09-14 [Machine-readable](https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company.json) Editorial coverage The DAX 40 Agent Success Index is a point-in-time snapshot of the agent-success of public digital touchpoints. Results are not statements about product quality, company performance, service quality, or the legal obligations of the brands named. Brand names and logos remain the property of their respective owners and are used solely for identification and reporting purposes in the context of editorial coverage (§ 23 MarkenG, Art. 5 GG). Brands wishing to respond, engage, or correct a factual error may contact [hello@hyperize.ai](mailto:hello@hyperize.ai). Responses received are published in full alongside the findings. Full methodology and editorial-coverage notice: [coverage statement](/en/imprint#dax40-disclaimer). --- Canonical: https://www.hyperize.ai/en/insights/articles/can-an-ai-agent-buy-from-a-dax-company Machine-readable index: https://www.hyperize.ai/llms.txt