Intelligence Bank
43 companies classified across 2 runs. Data from 2026-05-26 to 2026-05-26.
AI Maturity Distribution
Latest classification per company. Based on public website text only.
AI Maturity by Sector
Score distribution across every sector. Cell intensity reflects company count.
| Sector |
1 Dormant |
2 Curious |
3 Experimenting |
4 Implementing |
5 Native |
Total |
|---|---|---|---|---|---|---|
| Electric Vehicles | 3 | · | · | · | · | 3 |
| Engineering Consultancy | 2 | · | · | · | · | 2 |
| IT Consultancy | 2 | · | · | · | · | 2 |
| Agritech / LED Systems | 1 | · | · | · | · | 1 |
| Automotive | · | 1 | · | · | · | 1 |
| Automotive Powertrain | 1 | · | · | · | · | 1 |
| Autonomous Driving (AI) | · | · | · | · | 1 | 1 |
| B2B Digital Marketing Agency | · | · | · | 1 | · | 1 |
| B2B E-commerce SaaS | 1 | · | · | · | · | 1 |
| B2B Fintech | · | · | · | 1 | · | 1 |
| B2B Software (Accounting/HR) | · | · | 1 | · | · | 1 |
| Bioprinting / Life Science | 1 | · | · | · | · | 1 |
| Connected Vehicles (IoT) | · | 1 | · | · | · | 1 |
| Construction | 1 | · | · | · | · | 1 |
| Fuel Cells / Cleantech | 1 | · | · | · | · | 1 |
| HR Tech SaaS | · | · | · | 1 | · | 1 |
| Heavy Trucks & Industrial | 1 | · | · | · | · | 1 |
| Industrial Manufacturing | · | 1 | · | · | · | 1 |
| Logistics | · | · | 1 | · | · | 1 |
| Marine & Industrial Power | 1 | · | · | · | · | 1 |
| Marine Engineering | 1 | · | · | · | · | 1 |
| Medical Devices | 1 | · | · | · | · | 1 |
| Shipping & Logistics | · | 1 | · | · | · | 1 |
Most Observed Signals
AI-evidence patterns from classified companies, ranked by how many companies show each signal.
Run History — Picture Over Time
Each agent run and its score breakdown. The mini bars show how AI maturity was distributed in that run's companies.
| ICP | Date | Co. | 1–5 breakdown | Avg score |
|---|---|---|---|---|
| schools in göteborg, högstadie, gymnasie, högskola, bot… | 2026-05-26 | 8 |
|
1.13/5▼ |
| schools in göteborg, högstadie, gymnasie, högskola, bot… | 2026-05-26 | 8 |
|
1.25/5 |
▲ higher avg than previous run ▼ lower Full run history →
Sector Breakdown
| Sector | Cos. | Avg maturity | Opportunity |
|---|---|---|---|
| Autonomous Driving (AI) | 1 |
|
— |
| HR Tech SaaS | 1 |
|
— |
| B2B Fintech | 1 |
|
— |
| B2B Digital Marketing Agency | 1 |
|
— |
| Logistics | 1 |
|
1 warm |
| B2B Software (Accounting/HR) | 1 |
|
1 warm |
| Shipping & Logistics | 1 |
|
1 warm |
| Industrial Manufacturing | 1 |
|
1 warm |
| Connected Vehicles (IoT) | 1 |
|
1 warm |
| Automotive | 1 |
|
1 warm |
| Medical Devices | 1 |
|
— |
| Marine Engineering | 1 |
|
— |
| Marine & Industrial Power | 1 |
|
— |
| IT Consultancy | 2 |
|
— |
| Heavy Trucks & Industrial | 1 |
|
— |
| Fuel Cells / Cleantech | 1 |
|
— |
| Engineering Consultancy | 2 |
|
— |
| Electric Vehicles | 3 |
|
— |
| Construction | 1 |
|
— |
| Bioprinting / Life Science | 1 |
|
— |
| B2B E-commerce SaaS | 1 |
|
— |
| Automotive Powertrain | 1 |
|
— |
| Agritech / LED Systems | 1 |
|
— |
Opportunity Index
Score 2–3Companies that show AI awareness but haven't yet structured it. The highest-ROI outreach targets.
High Adopters
Score 4–5Already implementing or native. Skip outreach — or study them as benchmarks.
Market Intelligence Brief
AI-generated synthesis of all classified data. Refreshed from admin panel.
# Market Intelligence Brief: AI Maturity Across 43 B2B Companies
Prepared for GO MO Group | AI-Led Marketing Adoption Analysis
The overall picture is stark: AI adoption in this dataset is heavily back-weighted, with 30 of 43 companies (70%) scoring a 1 — Dormant. Only 6 companies score 3 or above, and just one company has reached Native status. This is not a market in mid-transition; it is a market that has largely not started. The score 2 cohort (7 companies) represents the only meaningful movement off the floor, suggesting a thin but real layer of companies that have begun experimenting without committing. For GO MO, this distribution is actually favorable: the addressable gap between where most companies sit and where they need to be is enormous, and the competitive window for an agency positioning around AI-led marketing is open.
The clearest immediate opportunities sit in three sectors: HR Tech SaaS, B2B Fintech, and B2B Digital Marketing Agency — all scoring 4 — alongside the Autonomous Driving company at 5. These are buyers who already understand AI as infrastructure, not novelty. They will respond to sophisticated, outcome-driven pitches rather than foundational education. Logistics and B2B Software (Accounting/HR), both at 3, represent a secondary tier worth prioritizing: they show operational AI awareness and are likely approaching a marketing inflection point where internal capability gaps become visible. GO MO's strongest near-term pipeline is in these five to six companies, where conversations can skip the "why AI" stage entirely and move directly to deployment and measurement.
The dormant sectors are not equal in their strategic value. Electric Vehicles (n=3, avg=1) is the most important to watch: it is the largest single-sector cluster in the dataset and scores uniformly at the floor, which suggests either a systemic capability gap across the segment or a shared cultural resistance to AI adoption in marketing specifically. Given the commercial pressure EV companies face to differentiate in a crowding market, this disconnect between competitive urgency and marketing maturity is a genuine business problem GO MO can frame a solution around. Engineering Consultancy (n=2, avg=1) and IT Consultancy (n=2, avg=1) are similar — firms that sell expertise but are not yet applying it to their own marketing — a positioning contradiction that makes for a sharp, credible entry narrative.
The non-obvious pattern here is the complete absence of mid-range scores in technology-adjacent hardware sectors. Connected Vehicles (IoT), Automotive, and Automotive Powertrain all sit at 2 or 1, despite operating in