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AI Adaptation Research Report — INFY (Infosys Ltd) · WhiteSwan constituent

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AI Adaptation Research Report — INFY (Infosys Ltd) · WhiteSwan constituent

EventTrader research desk · generated 2026-11-06 02:57 UTC · report ai-adapt-infy-20261106 · narrative: built from the evidence pack by the platform
Company INFY — Infosys Ltd · SIC 7371 Services-Computer Programming Services
Book AMF-WHITESWAN (long) — WhiteSwan
Composition algorithm Swan Composite v1.1.0 — 50% AI Adaptation Score + 25% AI Story Score + 25% market verdict, conviction-weighted
Anchor filing 20-F filed 2026-06-15 (period 2026-03-31)
Adoption level 3 — integrated · model-confirmed
AI Adaptation Score 62.9 / 100 · run 2026-11-06 · sector software percentile 96.6
Price 12.75 USD
Place in the book rank 10 of 10 · composite 64.2 · story 52.3 · market verdict 78.6 · weight 5.8%

1. Verdict

  • INFY (Infosys Ltd) is a WhiteSwan constituent: its own filings document AI inside the product or operations with investment behind it, and its AI Adaptation Score ranks at the top of the software companies (SIC 7370–7379) on the 2026-11-06 run [S5].
  • The score rests on the company's 20-F filed 2026-06-15, read in full by the platform's scorer [S1].
  • Adoption level 3 — integrated on the 0–4 rubric, confirmed by a model read with credibility 5.0/10 [S1].
  • AI Adaptation Score 62.9 / 100, percentile 99.5 of 6511 scored filers and 96.6 within its sector (software, 585 filers) [S5].
  • What would move it: a next report that withdraws the deployments, investment or outcomes it now states [S1].

2. The company

Infosys Ltd files with the SEC under CIK 1067491, SIC 7371 (Services-Computer Programming Services), listed on NYSE [S4]. The filing the score reads is the 20-F filed 2026-06-15 for the period ended 2026-03-31, effective for the books from 2026-06-16 [S2].

3. What the filing says about AI

The scorer found 313 AI-related sentences in the 20-F: 261 in the substantive sections (business, management's discussion) and 52 in the risk factors [S1]. Signals counted in the substantive text: proprietary-model language 2, deployments 14, measured outcomes 3, investment 9, third-party vendor tools 8, exploratory language 9 [S1].

Verbatim from the filing:

"Our approach integrates developer copilots, pre-built Software Development Life Cycle (“SDLC”) agents, AI native architecture, agentic workflows, and context aware data foundations to accelerate delivery, improve quality, and reduce operational friction." — Item 4. Information on the Company [S1] "Our offerings span AI native product and platform engineering, intelligent business process re-engineering, industry specific solutions and vertical package rollouts." — Item 4. Information on the Company [S1] "Microsoft Business Applications Services Practice The Microsoft Business Applications Practice at Infosys helps enterprises accelerate Digital and AI-enabled transformations by redefining the Customer Experience (“CX”), Employee Experience (“EX”) and Operational Excellence (“OX”) across enterprise functions using D365 ERP & CRM Suite, Business Central, Power Platform, Copilot Studio, Azure AI foundry, and Microsoft Fabric." — Item 4. Information on the Company [S1] "Our Application Development offerings are further strengthened by an integrated Domain Consulting Group (“DCG”) that embeds industry context directly into AI native solution design and delivery." — Item 4. Information on the Company [S1] "We leverage AI agents built on SAP Joule and the SAP Generative AI Hub, alongside AI‑native provider ecosystems such as OpenAI, Anthropic and GitHub, to deliver SAP S/4HANA Cloud transformations while maintaining a clean core and supporting long‑term agility." — Item 4. Information on the Company [S1] "With over four decades of experience in managing the systems and workings of global enterprises, Infosys accelerates business transformation through its AI-first value framework, deep domain expertise, and unique ability to orchestrate innovations from its AI-native partner ecosystem." — Item 4. Information on the Company [S1] "Physical AI The partnerships enable best in class AI solutions with the flexibility and resilience required for AI native, agent driven enterprises." — Item 4. Information on the Company [S1] "Application Development Capabilities Our Application Development offerings enable clients to build and evolve software that is AI native by design." — Item 4. Information on the Company [S1] "To enable faster and more responsible AI adoption, DCG has developed AI native blueprints across 23 industry segments, aligned to segment specific priorities, regulatory needs, and value drivers." — Item 4. Information on the Company [S1] "It is a foundational enabler for the new generation of AI native services." — Item 4. Information on the Company [S1]

4. The AI Adaptation Score

The AI Adaptation Score weighs the adoption level (0–4) at 45%, building with AI from the ground up (greenfield) at 20%, the credibility of the claims at 15%, the trajectory against the previous filing at 12% and the investment signal at 8%, with trajectory and investment measured against the company's own sector; the greenfield reward counts only from level 3 upward [S5]. INFY's score of 62.9 decomposes into level 33.8, greenfield 8.0, credibility 7.5, trajectory 5.9 and investment 7.8 points [S5]. Its cluster label for the run is builder with a margin of 32.4 points from the sector's other cluster [S5].

The model read of the filing returned level 3 (integrated) with confidence 0.74 and sub-scores product 8.0, operations 7.0, investment 5.0, data moat 3.0, credibility 5.0, greenfield 4.0 (each 0–10) [S1]. Its summary: "Infosys embeds proprietary AI platforms (Topaz, Topaz Fabric, Equinox) and a proprietary agentic framework into its services, with production agent deployments and measurable-outcome framing. But it relies heavily on partner models (OpenAI, Anthropic, SAP) rather than proprietary models, and hard spend figures are absent—integrated, not native. AI is retrofitted onto a 40-year services firm." [S1].

"We also saw significant traction in agentic AI, with several agent‑based solutions successfully deployed in production and generating tangible value for our customers." — Item 4. Information on the Company [S1] "We help clients build portfolios of AI initiatives anchored to measurable results revenue uplift, margin expansion, reduction in cost to serve, cycle time compression, and experience improvement" — Item 4. Information on the Company [S1] "We have established a comprehensive repository of pre-built, ready-to-deploy AI agents utilizing our proprietary agentic framework." — Item 4. Information on the Company [S1] "We are leveraging our purpose-built, composable and open agentic services suite Infosys Topaz Fabric and our collaboration with AI disruptors to deliver both AI augmented and AI First Services to clients." — Item 4. Information on the Company [S1] "Infosys Equinox is an AI-first, composable commerce platform built for the agentic era, enabling enterprises to deliver intelligent, autonomous, and personalized commerce experiences across channels, customers, and AI agents." — Item 4. Information on the Company [S1]

5. Trajectory

The previous periodic report, the 20-F filed 2025-07-01, scored level 1 (exploring) with 144 AI sentences [S3]. The level rose by 2 between the two reports [S1].

6. Recent developments

  • wire:prnewswire 2026-10-29T09:54+00:00: Winners of Qorus-Infosys Finacle Banking Innovation Awards 2026 Announced [S7]
  • wire:prnewswire 2026-10-28T12:14+00:00: Canada's UNI Financial Cooperation Advances Branch Modernization with Infosys Finacle Universal Banker [S8]
  • wire:prnewswire 2026-10-27T11:47+00:00: Infosys accompagne Syngenta dans sa transformation mondiale vers SAP S/4HANA [S9]
  • wire:prnewswire 2026-10-27T11:36+00:00: Infosys schließt die weltweite SAP-S/4HANA-Umstellung für den Pflanzenschutzbereich von Syngenta erfolgreich ab [S10]
  • wire:prnewswire 2026-10-27T11:28+00:00: Infosys Successfully Delivers Syngenta's Global SAP S/4HANA Transformation for Crop Protection Business [S11]
  • wire:gnews-commercial-mega 2026-10-27T05:36+00:00: Infosys’s $5.2 Billion Deal Wins Fail to Lift FY27 Outlook - Analytics India Magazine [S12]
  • wire:prnewswire 2026-10-26T23:20+00:00: Infosys Investigation Notice: SueWallSt Notifies Investors of Pending Investigation Into Infosys (INFY) [S13]
  • wire:gnews-commercial-mega 2026-10-26T01:00+00:00: Infosys’s huge deal wins fail to give it an edge over peers - Livemint [S14]

7. What would change the verdict

INFY leaves the long book if a later report drops the deployments, investment or outcomes it now states, if the model read judges the claims uncredible, or if higher-scoring filers displace it on a later run [S5]. The book is recomposed on every scoring run from the ten highest scores that pass the liquidity screen [S5].

8. Risks and caveats

The score reads what the company discloses, not what it does: a company can adopt AI without describing it in a periodic report, and can describe it without adopting it [S5]. Risk-factor language is counted separately from substantive text and never credited as adoption; boilerplate that resembles generic risk disclosure is excluded [S5]. Only the sections the scorer parses are read (business, risk factors, management's discussion for a 10-K or 10-Q; the earnings release of an 8-K is scored but never anchors a level) [S5].

9. Watch list

  • The next periodic report of INFY (expected around 2027-06-15) and its AI sentences [S4].
  • The model read of the current filing (done) [S5].
  • The next scoring run's AI Adaptation Score and the book's recomposition [S5].

Place in the book

  • Rank 10 of 10 in AMF-WHITESWAN (Swan Composite v1.1.0, scoring run 2026-11-06): the book holds the highest composites [S5].
  • Composite: 0.50 × 62.9 (AAS) + 0.25 × 52.3 (story) + 0.25 × 78.6 (market) = 64.2 [S5].
  • Market verdict 78.6: over the last 90 days INFY rose more and fell less than the software universe's median daily return (down-capture 1.16, up-capture 2.30, L = 1.14; 33 down / 19 up days) — the Failure-To-Adapt fund's selection signal, 50 = moves with the software universe's median daily return [S5].
  • AI Story Score 52.3: a beneficiary narrative in the AI stories written about the company [S5].
  • Weight: rank factor 1.00 (rank 10 of 10) × story factor 1.02 × market factor 1.29, normalised across the book and clamped to 5–20% → 5.8% [S5].

Sources

Method and disclaimer

The AI Adaptation Score reads each company's own periodic SEC reports (10-K, 10-Q, 20-F, 40-F): deterministic features (AI sentences by section, proprietary-model, deployment, outcome, investment and vendor language, boilerplate and negation excluded) set an adoption level on a 0–4 rubric; a model read of the filing's AI sentences confirms the level and scores credibility and greenfield (the business built with AI from the ground up rather than retrofitted); the score combines level, greenfield, credibility, trajectory against the previous report and investment, measured against the company's sector, with greenfield carrying the highest reward. The books are composed by Swan Composite v1.1.0: each company's composite is 50% AI Adaptation Score + 25% AI Story Score + 25% market verdict — the AI Story Score is the sentiment of the AI stories written about it, the belief network of companies named in the same stories and the price reaction to those stories (no story scores neutral); the market verdict is the Failure-To-Adapt fund's selection signal, the signed down/up capture ratio of the stock against the software universe's median return over 90 days (a stock that falls more and rises less than its peers scores below 50). AMF-BLACKSWAN holds the ten lowest composites that pass the liquidity screen and the new-listing gate and AMF-WHITESWAN the ten highest, weighted by conviction (rank, story agreement and market agreement, each leg 5–20%), recomposed on every scoring run. Every quote in this report is the filing's text verbatim; every factual sentence names its source; a source the platform could not reach is reported as missing, never filled in.

This report is information, not investment advice. Figures come from the cited sources as of their dates. Nothing here is a recommendation to buy, sell or hold any asset.

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