Research
AI Monitor

AI Monitor. Where your company really stands on AI.

Six validated dimensions, an evidence-based picture of your starting position. The finding that runs through the data: acceptance isn't what's missing – the ability to keep adapting data, processes, roles and governance is.

Publisher
Teklens logo
Academic partners
ETH Zürich
University of St.Gallen
Context Debt Index · personalised assessment

Compare your product-delivery context maturity.

Four questions produce your personal Context Maturity score. You then receive a recommended Teklens experiment and the adjacent AI-readiness benchmark for your industry.

1. Specifications reliably point to affected code paths and technical constraints.
rarely truesystematically true
2. Jira, pull requests, documents and decisions are traceably connected.
rarely truesystematically true
3. Drift between specification and code becomes visible before QA or production.
rarely truesystematically true
4. Reviews end with evidence, status and a clear approval trail.
rarely truesystematically true

This preview runs locally in your browser; your answers are not stored.

The Context Debt Index will be published quarterly.

Teklens will publish anonymised, aggregated patterns from these assessments, with sample sizes, segment limits and a clear separation from the joint AI Monitor research with ETH Zurich and HSG.

Continue to the industry benchmarks
Pre-release · First results

Where companies stand today

162 responses, six dimensions. Filter by industry, size, role or region – and see where the gaps open up. The full report follows in autumn 2026.

Headline findings

What the data says

Acceptance is not the bottleneck: staff embrace AI – 4.0 of 5, just 6% push back. What is missing is the ability to adapt data, processes, roles and governance at the same pace. Six findings show where that gap opens up.

66 vs 50
Adoption outruns readiness

Adoption scores 66 of 100; the groundwork beneath it – clean data, integration, governance, the ability to adapt – sits at 50. People moved faster than their organisations could follow.

6 in 10
Shadow AI is the norm

87% get AI tools from their employer – and 6 in 10 also use personal ones. That work runs with no security review and no audit trail.

54 vs 42
Leaders see a different company

The top of the house puts AI readiness at 54 of 100; the people doing the daily work put it at 42. Twelve points apart – there is no shared picture.

60 vs 44
The adaptive gap

Strong on what stays put – people, culture, leadership (60 of 100). Weak on what keeps moving: adapting processes, working with partners, keeping up with regulation (44).

3.6 → 3.3
Commitment without budget

Backing for AI scores 3.6 of 5. Once it is about budget, people and a plan, it slips to 3.3 – encouragement is free.

30 pts apart
Same company, different planet

When several people from one company answer, their scores land about 30 points apart. Colleagues a desk away rate the same organisation completely differently.

What this means for your role

Two roles. Two consequences.

The same evidence, a different consequence depending on what you own.

C-level · Board54 vs 42

A shared picture before the next investment.

Leaders rate AI readiness twelve points higher than the operational layer. Activity isn't what's missing – a shared view of where you stand is.

What this means for leadership
CTO · VP Engineering66 vs 50

The foundation before the next tool.

Adoption is ahead of the foundation. Data quality, integration and adaptable processes decide whether AI reaches production safely.

What this means for engineering

Context: the Monitor figures shown are international self-assessments. Regional segments indicate direction; they are not a representative DACH benchmark.

Industry
Size
Role
Region
20406080100LeadershipInternalAssetsTechFoundationDataEngineExternalAlignmentDynamicCapabilities
Average (benchmark)n=162

Basis: 162 valid responses (106 with demographic attribution), AI Monitor 2026 – published by Teklens, in collaboration with ETH Zurich and the University of St. Gallen. Values are self-assessments normalised to 0–100. Industry, size and role are grouped into readable clusters (weighted mean). Regional segments indicate direction; they are not a representative DACH benchmark.

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Methodology

Quantitatively measured. Differentiated by organisational level.

Standardised self-assessments, triangulated across organisational levels (CxO/Board vs. VP). Scored per dimension and per company, plus a variance analysis that surfaces perception gaps.

For the DACH region there is an additional academic deep dive (HSG master’s thesis, 64 valid responses, mostly senior management). Its sharpest finding: openness to change is the highest-scoring of all 19 questions – "adapting structures and processes" the lowest. Exploratory, not a representative benchmark.

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Dimensions
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Questions
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Org levels (CxO vs. VP)
Behind the study

Who runs the AI Monitor

Published by Teklens, in collaboration with the research partners University of St. Gallen (HSG) and ETH Zurich.

Kathrin Wolff
Kathrin Wolff
Research partner
Prof. Dr. David Finken
Prof. Dr. David Finken
Professor of Marketing × Technology (TUM) and Senior Research Affiliate (ETH Zurich)
Marc Gasser
Marc Gasser
Teklens
Simon Scheurer
Simon Scheurer
Teklens
The study runs on ReadyAI
Inside the report

What you receive

The full report arrives in autumn 2026.

Sign up: we'll notify you at release – and you'll be among the first to receive the results.

How the research becomes a decision: AI Leadership Lab