CAC 40 and Nasdaq Top 10: what size does not tell you about AI maturity

By Paul-Antoine TUAL, AI Transformation Leader, Croissance et Transitions, July 2026; factually revised on 6 September 2026.

This study places a market snapshot beside an internal AI-maturity grid, two useful instruments provided their scopes, dates and evidential limits remain explicit.

• Market capitalisation and index weight are dated market data governed by index rules.
• The maturity measure is a proprietary public-source assessment with no interviews or internal documents.
• Rank gaps describe twenty companies and demonstrate neither causation, a general law nor future performance.
• The CAC 40 panel relates to July 2026; the Nasdaq panel retains a scope selected in January 2026.

Observing AI maturity through public information

AI maturity is treated as a collective execution capability, observed here only through the traces that a company chooses or is required to publish.

• Steer: connect uses to strategy, budget, accountable owners and measurable objectives.
• Operate: control data, run a workable architecture and maintain systems in production.
• Transform: build skills, involve employees and deploy in significant processes.
• Control: inventory systems, address risks, document controls and communicate results accurately.

Comparison with market capitalisation adds another perspective, but the two columns do not measure the same underlying reality.

• A company may sell AI components or services while publishing little about its own internal governance.
• A highly communicative company may provide more public evidence without covering every real practice.
• A low rank may therefore indicate weak capability, insufficient evidence or both; the study cannot always distinguish them.

Index and panel date	Three largest capitalisations in the historical scope	Three highest documented-maturity scores
CAC 40, July 2026	LVMH · L’Oréal · Hermès	L’Oréal · Sanofi · Schneider Electric
Nasdaq, January 2026 scope	NVIDIA · Apple · Alphabet	Alphabet · Meta · Amazon

The table summarises the internal study’s historical results without suggesting that market rank explains maturity rank.

• Only one company appears in both trios for each panel: L’Oréal in Paris and Alphabet in the Nasdaq panel.
• The averages of the published scores are 3.05/5 for the CAC 40 panel and 3.16/5 for the Nasdaq panel.
• These are descriptive differences; no representative sampling or statistical test supports generalisation.

The analysis grid, dimension by dimension

The grid spreads the score across eight dimensions so that extensive communication or a few use cases cannot by themselves offset weaknesses in governance, data or control.

• Strategy and governance each carry 15%, or 30% together.
• Data, technology, talent, deployment and risk each carry 12%.
• Financial and non-financial communication carries 10%.
• These weights express the author’s methodological judgement and are not a market standard.

Dimension	Question considered	Example of public evidence	Interpretive limit
D1 · Strategy (15%)	Is AI steered and funded?	roadmap, budget, dated objective	budget does not prove value created
D2 · Governance (15%)	Who decides and reports?	committee, executive owner, board reporting	a published structure may remain formal
D3 · Data (12%)	Are provenance, quality and rights documented?	catalogue, indicators, traceability	silence does not prove absent controls
D4 · Technology (12%)	Can systems remain in production?	MLOps, testing, drift monitoring, rollback	described architecture does not prove performance
D5 · Talent (12%)	Are staff prepared and involved?	training, skills, labour agreement	training volume does not measure useful adoption
D6 · Deployment (12%)	Do uses reach core processes?	volumes, users, attributable gains	usage, revenue and profit are distinct
D7 · Risk (12%)	Are systems and duties mapped?	inventory, classification, controls, incidents	a policy alone does not establish compliance
D8 · Communication (10%)	Are claims precise and tracked?	recurring metrics, corrections, costs	greater disclosure improves observability

Five levels for classifying the panel’s scores

The overall score is the weighted average of eight dimensions and is read through five internal levels whose thresholds compare score sheets but correspond to no external certification.

Level	Score	Interpretation in this study	Historical count
Emerging	< 1.8	little structure or public documentation	0
Exploratory	1.8 ≤ score < 2.6	early uses with limited steering or evidence	1
Structured	2.6 ≤ score < 3.5	visible arrangements and uses, partial results	13
Integrated	3.5 ≤ score ≤ 4.2	broader integration and more evidence	6
Transformative	> 4.2	business-model change with documented control	0

The distribution mainly describes this grid’s calibration and the observed companies’ disclosure levels.

• Thirteen companies sit at Structured, six at Integrated and one at Exploratory.
• None reaches Transformative, which does not establish that the level is objectively unreachable or that no company anywhere has reached it.

Connecting each score to its evidence level

The evidence level makes each score open to challenge, provided missing disclosure is never converted into a finding that an operational practice does not exist.

• Documentary: an identified public document directly supports the assessment.
• Declarative: the company makes a claim without enough public material to test it.
• Mixed: some components are supported and others remain declarative.
• Absent: the review found no evidence in its corpus, which remains different from “does not exist”.

What the grid does not measure

A desk review cannot replace an internal diagnostic because the most consequential operating dimensions are often the least visible in regulated filings and investor presentations.

• No interviews, technical tests, system registers or internal documents were examined.
• Strategy, risk and communication receive comparatively high public exposure.
• Data quality, technical debt, resilience and control effectiveness remain hard to establish externally.
• The results should guide audit questions rather than close the diagnosis.

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The CAC 40 through the grid: what size does not predict

The Paris panel shows substantial gaps between market rank and documented-maturity rank, although those gaps jointly reflect practices, publication quality and scoring choices.

Rank	Company	Internal score	Level
1	L’Oréal	3.64	Integrated
2	Sanofi	3.51	Integrated
3	Schneider Electric	3.40	Structured
4	Safran	3.12	Structured
5	Air Liquide	3.10	Structured
6	BNP Paribas	3.03	Structured
7=	LVMH	2.88	Structured
7=	TotalEnergies	2.88	Structured
9	Airbus	2.76	Structured
10	Hermès	2.15	Exploratory

The useful reading returns to the evidence behind each score instead of seeking one explanation in size or sector.

• L’Oréal and Sanofi had more public evidence across several dimensions in the reviewed corpus.
• Hermès publishes little on AI, so its last place also measures limited disclosure.
• Companies in the same sector may differ sharply in disclosure, governance and deployment.

The LVMH lesson: three rankings, three different answers

LVMH illustrates why total capitalisation, CAC 40 weight and maturity score must remain separate measures, each answering a precise question.

• Total market capitalisation depends on share price and shares outstanding.
• Euronext weights the CAC 40 by free-float-adjusted market capitalisation under its capping rules [1].
• The maturity score comes from the grid and evidence corpus described above.
• A gap among the three ranks is neither an anomaly nor a causal relationship.

Nasdaq panel: visible capabilities and limits of evidence

The Nasdaq panel should be read as a historical ranking of the scope selected in January 2026, without retrospectively replacing it with July’s ten largest capitalisations.

Rank	Company	Internal score	Level
1	Alphabet	3.91	Integrated
2	Meta	3.79	Integrated
3	Amazon	3.64	Integrated
4	Microsoft	3.54	Integrated
5	Netflix	2.88	Structured
6	ASML	2.86	Structured
7	Apple	2.78	Structured
8	Tesla	2.76	Structured
9	NVIDIA	2.73	Structured
10	Broadcom	2.71	Structured

Netflix and ASML preserve the original scope, while subsequent market-cap changes do not retrospectively alter scores calculated for that panel.

• The Nasdaq-100 covers 100 large non-financial Nasdaq-listed companies and uses modified market-cap weighting [2].
• Nasdaq listing, Nasdaq-100 membership and a place among its ten largest capitalisations are distinct statuses.
• Any update must select the panel at one common date before scores are recalculated.

AI suppliers: distinguishing commercial strength from documented maturity

NVIDIA’s and Broadcom’s low positions indicate that the reviewed corpus documented some internal capabilities less fully, without establishing a causal link between selling AI infrastructure and organisational maturity.

• The score covers governance, data, talent, internal deployment, risk and communication.
• The commercial strength of a product or component is not a variable in this measure.
• The sample cannot test a correlation between being a supplier and internal maturity.

Comparing averages by dimension

Dimension averages show where public evidence differed between the panels, without establishing why those differences arose.

Dimension	CAC 40	Nasdaq	Descriptive gap
D1 · Strategy	3.3	3.6	Nasdaq +0.3
D2 · Governance	3.2	3.2	tie
D3 · Data	2.4	2.1	CAC 40 +0.3
D4 · Technology	3.1	3.4	Nasdaq +0.3
D5 · Talent	3.1	2.4	CAC 40 +0.7
D6 · Deployment	3.3	3.8	Nasdaq +0.5
D7 · Risk / compliance	2.7	3.3	Nasdaq +0.6
D8 · Communication	3.2	3.4	Nasdaq +0.2

Four observations organise these numbers while keeping observation, interpretation and regulatory requirements separate.

• Data: D3 is the lowest average in both panels, supporting further questions about provenance, quality, rights and traceability.
• Deployment: the Nasdaq panel publishes more observable material on D6, with no causal link to the index established.
• Talent: the CAC 40 panel’s largest lead is D5; labour agreements and training plans create evidence but do not alone measure adoption.
• Risk: US filings make some risks more visible, while European compliance depends on the actor’s role and each system’s category.

The AI Act timetable must be applied system by system because the amended Regulation now separates two principal dates for high-risk-system obligations [3].

• Annex III: 2 December 2027 for systems under Article 6(2).
• Annex I: 2 August 2028 for systems under Article 6(1).
• Transitional conditions and duties already in force require separate analysis; a maturity score never establishes compliance.

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Where is the value going?

Placing the rankings together mainly encourages readers to separate financial value creation, operating capability and quality of evidence, three questions requiring different data.

• Infrastructure suppliers capture a visible share of AI spending, which does not measure their internal governance.
• Users may create value through processes, products or decisions, provided results and costs are attributed cautiously.
• For an SME or mid-cap, the practical priority is a steered use-case portfolio, controlled data, clear accountability and verifiable results.
• Sovereignty choices concern dependency, reversibility, data location and business continuity.

How to read these two rankings without falling into traps

A rigorous reading retains every figure’s date, scope, definition and evidence level before comparing ranks.

• Date every capitalisation and panel composition.
• Distinguish total capitalisation, free float, index weight and index membership.
• Compare only companies selected under the same rule and at the same date.
• Read every score with its evidence; “not published” does not mean “non-existent”.
• Treat neither a rank nor an average gap as a price forecast or causal result.

Disclaimer. This article is educational and informational; it is neither investment advice nor a recommendation to buy or sell, and the internal scores are neither financial ratings nor certifications.

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If you lead an SME or mid-cap and want to turn these questions into concrete decisions, see the Junyr Method™ and Junyr AI maturity audit.

Sources

The index rules and legal timetable below were rechecked on 6 September 2026, while the scores remain the historical output of an unaudited internal study.

• [1] Euronext, CAC 40 Index Factsheet, 31 March 2026: https://live.euronext.com/sites/default/files/documentation/index-fact-sheets/CAC_40_Index_Factsheet.pdf
• [2] Nasdaq, Nasdaq-100 Index Methodology, effective 1 May 2026: https://indexes.nasdaqomx.com/docs/Methodology_NDX_Effective_May_1_2026.pdf
• [3] Regulation (EU) 2026/1744 amending the Artificial Intelligence Act, including Article 113: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32026R1744
• [4] Croissance & Transitions, internal studies AI Maturity, CAC 40 Top 10 (13 July 2026) and AI Maturity, Nasdaq Top 10 (14 July 2026), unpublished detailed grids without independent audit.