Version PE-2026.10-v5 · Source-corpus cutoff: 10 October 2026 · Publication and methodological challenge: 11 October 2026
What the current public edition does
Mayden studies how AI changes recurring work, decisions, responsibilities and organisational learning. Its working definition of an AI-native enterprise is one that repeatedly converts AI capability into useful, accountable work across a defined organisational scope. That definition and the nine-theme framework are research hypotheses, not a validated enterprise classification.
The current edition publishes sector research, corpus-level documentation statistics and attributed operating examples, without individual company scores, ranks or coded profiles. Its purpose is to improve executive questions and make research boundaries inspectable. It is not an enterprise audit, certification, clinical or investment rating, representative adoption survey, or a confidential company assessment. The confidential opt-in diagnostic is in development; it is not yet a validated or operating service.
Named facts can make an operating example useful. Each must retain its publisher, period or unknown date, locator, operating scope and relevant boundary. Selection is by an explicit research question, not score or standing. Public mention implies neither participation, endorsement, client relationship nor permission for confidential access. No company is portrayed as weak because qualifying public evidence was not located. These publication rules apply to the website, PDF, chart, downloadable data and client payload, not just the visible interface.
The selected research corpus
The retained corpus contains 80 entity records: ten in each of Banking; Telecommunications; Energy & Utilities; Aviation & Logistics; Manufacturing & Materials; Retail & Consumer; Healthcare; Real Estate & Construction. It contains 272 recorded claims, 224 retained as eligible under the historical evidence rules. These are collection quantities, not independent experimental observations.
Each sector has two headquarters records in Saudi Arabia, UAE, Qatar, Kuwait and Bahrain. Oman is outside this edition; coverage is not the full GCC. Selection was purposeful, influenced by sector relevance and identifiable corporate disclosures. There was no probability sample, market-share threshold or complete industry census. No country league table, regional prevalence estimate or population percentile follows from this design.
Units mix international groups, local operators and subsidiary practices. A headquarters country does not identify where all reported work takes place. Corporate scopes can overlap. Sector cohorts also contain different business models. Public aggregates describe the selected records; they do not remove those limitations. Country-by-sector cells contain only two records and are not published as a new comparative product. Suppressing names alone would not ensure anonymity, especially because earlier named releases and source links remain public.
Search, access and source truth
The desktop review used bounded corporate-domain searches and annual, sustainability, governance and implementation reports, mainly in English with limited Arabic discovery. Search was not exhaustive or a preregistered systematic review. Logs describe performed work; they do not establish equal search intensity or recall across firms, themes or languages.
The retained archive includes claims, URLs, source dates where known, access dates, locators, implementation descriptions, scope limits, search notes and review decisions. A readable corporate report establishes what its author reports. It is not independent assurance of the operation. Vendor descriptions and mirrored reports retain origin and access limits. Republishing an assertion does not create independent confirmation. A search snippet is a discovery lead, not proof that a full source was read.
The edition does not announce a new 80-company crawl or source re-verification. The source corpus remains frozen at 10 October. The 11 October work adds a methodological challenge, institutional comparison and publication redesign. Changed presentation is not changed company performance.
How aggregate figures are constructed
The historical research codes evidence across nine candidate themes: AI Core; Augmented Workforce; Ecosystem; Interfaces & Automation; Decision Lineage; Experimentation; Autonomy & Operating Model; Knowledge; Governance. For public coverage, a record contributes one to a theme only when at least one retained eligible claim supports that theme. Each sector-theme denominator is its ten selected records. A record can contribute to several themes, so theme counts must not be added as unique companies.
There are 720 possible entity-theme cells (80 × 9); 201 contain qualifying evidence and 519 remain unknown in this review. Unknown means the review has no qualifying evidence for that cell, not that a capability is absent. Chart ordering is editorial/alphabetical, not a sector performance rank. Coverage is documentation coverage, distinct from search completeness and operational coverage of employees, workflows or decisions.
Source-date figures use the 224 eligible claim records as denominator: 79 have no recorded publication date; 28 are dated before 2025; 117 are dated in 2025 or later. A claim is not a company or independent project. Publication date, reporting period, retrieval date and confirmation of continuing use answer different questions. An undated source may describe a dated period; a recent publication may describe an older deployment. No source-date category proves continuing or discontinued use.
Every exhibit specifies basis, unit, denominator where applicable, cutoff and interpretation boundary. Conceptual diagrams are proposed analytical tools, not measured distributions or maturity stages. Attributed accounts remain separate cases; connecting them visually must not imply an undisclosed system architecture. Reported benefits stay outside practice indicators and require their own baseline, period, comparison and cost boundary.
Historical arithmetic and why publication changed
Frozen v1–v4 editions retain the original public-disclosure method and artifacts. Each theme used the maximum qualifying anchor: a specific commitment/pilot, an implemented practice, or an implemented practice with operating detail. Unknown contributed no documented points while remaining unknown in the profile. Historical normalisation was 100 × sum of nine theme anchors / 27, with equal nominal weights and within-sector tied positions. It did not estimate percentage AI nativeness.
That arithmetic can be replayed, but maximum anchors can reward one narrow example, ordinal distances were uncalibrated, source availability differs and organisational scopes are not homogeneous. A fixed denominator does not solve these problems. The public-policy change reflects construct, intended-use and engagement considerations; it does not claim that historical companies changed or that every earlier calculation was arithmetically wrong.
The 11 October challenge tested 512 joint weight-corner choices and 36 ordinal-spacing choices on frozen v4, plus a separately labelled baseline reference. Independent replay checked 43,840 specification-record results (548 × 80). In the 512 weight choices, 53 of 59 historically ranked records changed position in at least one tested specification. The specifications are analyst-selected deterministic tests. They are not a probability distribution, error rate, confidence interval, exhaustive plausible model space or validation study. Full individual diagnostics remain internal; this aggregate account retains its historical basis and limits.
Earlier files must remain explicitly historical, with their exact data, method/code provenance and correction context. They are not current enterprise ratings. Previously public information cannot become confidential or anonymous retroactively. A material correction or lawful removal, if ever required, needs its own recorded decision rather than an unannounced overwrite.
Review, reproducibility and its limits
Source extraction, coding challenge and publication review were AI-assisted. Separate AI passes can share errors. No completed independent human assurance, blinded human reliability study or empirical validation is claimed. Legacy decisions that lack exact-claim binding remain identified as legacy; a new queue must not relabel them as completed review.
Current public exports contain aggregate figure inputs, their definitions, selected attributed facts and method information. They exclude individual company scoring records and sensitivity outputs. Readers can reproduce published chart arithmetic from its aggregate inputs and inspect cited sources. They cannot independently reconstruct every microdata decision from the current aggregate export alone. Mayden retains the detailed research records and private replay. Historical public bundles retain their own reproducibility contracts and limits. Hashes bind bytes or structured records, not factual truth.
A source, claim and operating case are different units. A two-claim provenance pilot in earlier research does not establish a reconciled source-family graph across all 80 records. Required dependencies, mirrors, common assertion origins and case overlap need further review. Public-source checking can flag a changed page; it cannot automatically decide what claim changed or whether a practice continues.
Research synthesis and institutional comparison
The eleven reports draw on 34 selected research and methodological references in the retained corpus. Designs range from experiments and observational studies to benchmarks, normative frameworks and guidance. They are not 34 comparable experiments, a complete literature census or a new statistical meta-analysis. A writing-task estimate, contact-centre result and repository experiment cannot establish one enterprise-wide productivity effect. Each study retains design, setting, population, access depth and transfer limits.
The additional 11 October institutional review inspected 21 primary sources for eight benchmark analogues and six consultancy-publication examples. This was a purposive comparative review, not a causal study of commercial success. Provider descriptions show operating mechanisms and public offers; they do not prove audience size, revenue, retention or incremental consulting sales. Some evidence was abstract-only, with that limit retained.
The inspected BCG and McKinsey AI survey publications use aggregate comparisons. BCG's Most Innovative Companies 2023 also demonstrates that a consultancy can publish named rankings under a different construct. No client relationship or consent arrangement is inferred. Mayden's publication choice is contextual, not a universal claim about consultancy practice.
The future participant instrument
Keep practice, outcome and evidence-confidence records separate. Specify the assessment entity, eligible work, reference period, respondent role, evidence unit and intended decision before choosing a scale. A candidate enterprise composite may be formative; reflective subscales require their own justification. High internal consistency does not validate a formative index, and correlations generated partly by the scoring formula cannot establish construct validity.
Before intake: appoint accountable humans; obtain content review; specify permissions, secure storage and retention; conduct English/Arabic cognitive interviews and mode checks; predeclare pilot questions and acceptance rules. Before benchmark claims: conduct independent coding and role checks, an appropriate test–retest design, sector/language comparability work, construct/outcome evaluation and sensitivity analysis. Analytical sample requirements follow intended comparisons and precision. A 40–60-company capacity scenario is not a statistically justified validation sample or regional norm.
Seek several knowledgeable perspectives where feasible; preserve disagreement rather than averaging it away. Distinguish no, unknown, not applicable and unavailable evidence. Record workflow breadth and sustained use. No percentiles, certification or “validated score” until the relevant empirical and governance gates are passed. Paid advice and prior Mayden involvement must be recorded as potential conflicts and confounders.
Collection, governance and longevity
The collector is a manually invoked, bounded public-source checker with an approved URL register, access/robots checks, limits, pacing, hashes and retrieval receipts. HTML matches are leads; PDF collection is fingerprint-only. It has no private-system credentials, paid-data connector, continuous schedule or authority to accept, score or publish claims. It is not an official government crawler. DNS resolution remains subject to the host resolver outside its HTTP deadline. A production service would need an owner, validated extraction, source-family management, secure storage, monitoring and review capacity.
The accepted programme design separates research from commercial influence: no fee buys inclusion, favourable assessment or suppressed findings. Accountable human roles and external assurance have not yet been appointed. The proposed charter provides stop-release authority, conflict/recusal records, equal correction handling and versioned change decisions; implementation and actual sign-offs must be reported rather than assumed.
Future change reports must distinguish operating change from discovery, access recovery, coding correction, scope, sample composition and method change. Track attrition, mergers, respondent replacement, interventions and translation/mode revisions. Bridge studies are required before interpreting materially changed instruments on one trend line. Fund and accept the next wave before promising a cadence.
Mayden owns its original analysis and software subject to applicable rights, not third-party publications, public facts or a participant's entrusted material. The AI Native Index remains a working name; no trademark clearance or registration is claimed. The ambition is a durable organisational benchmark. This publication does not claim that ambition has already been achieved.
Selected methodological foundations
OECD/JRC composite-indicator handbook ↗; scale-development primer ↗; formative/reflective measurement ↗; NIST AI RMF ↗; W3C provenance model ↗. These inform choices; none validates Mayden's instrument.