A score out of 100, a 6-axis radar and a prioritised action plan to move from POC to production. No jargon.
An AI maturity assessment measures a company's real capacity to create value with artificial intelligence: strategy, data, team adoption, industrialisation, skills and governance. The result places the organisation on an objective scale and prioritises the actions that move AI from pilot stage to production.
Each dimension is scored out of 100. Strategy and governance carry more weight in the overall score: they are the two locks that most often block the move to production.
An AI ambition decided at the right level, use cases prioritised by impact and a named owner. Without a clear direction, initiatives stay scattered.
AI systems' access to reliable, locatable and governed data. An agent is only as good as the information it can reach.
Real day-to-day usage by teams, beyond the early adopters. AI that is not used produces no value.
Moving pilots into production: monitoring, reliability, IT integration. This is the dimension where most companies fail.
The internal capacity to use, supervise and evolve AI systems, from leadership to business teams.
The rules that make AI auditable: who validates what, decision traceability, EU AI Act and ISO 42001 compliance.
Your overall score places your company on one of 4 levels. The vast majority of organisations currently sit on the first two.
AI is a topic of conversation, not yet a practice. The risk: staying stuck at the intention stage while the market moves ahead.
Real usage exists, but it’s barely industrialised and barely governed. The classic trap: staying stuck at the PoC and never generating ROI.
Agents in production and governance starting to take shape. The challenge now: scaling without losing control.
AI that is steered, governed and creating measured value. Your challenge: keep the lead and extend the advantage.
The 2025 studies converge: AI adoption is massive, production remains rare. That gap is precisely what this assessment measures, by weighting the dimensions that decide whether AI scales.
46% of AI proof-of-concepts are abandoned before reaching production
S&P Global Market Intelligence, 202595% of generative AI pilots show no measurable P&L impact
MIT, The GenAI Divide, 2025Only 21% of companies deploying AI agents have mature governance in place
Deloitte, State of AI in the Enterprise, 2026Over 40% of agentic AI projects will be cancelled by the end of 2027
Gartner, 2025Gartner, MIT or IBM describe maturity states: they tell you where you are. The Koneetiv framework builds on that foundation and makes it operational on the bottleneck the numbers point to: moving to production and governing AI agents.
| Gartner AI Maturity Model | 5 levels, from awareness to transformation | Describes a state, not the path through the production wall |
|---|---|---|
| MIT Sloan and BCG | 4 adoption profiles (Pioneers, Investigators, Experimenters, Passives) | A research segmentation, not a self-assessment tool |
| IBM AI Ladder | 4 data-centric rungs (Collect, Organize, Analyze, Infuse) | Data angle, predates generative AI and agents |
| Microsoft Agentic AI Maturity | 5 stages oriented towards Copilot adoption | Tied to the Microsoft ecosystem |
| Koneetiv framework (2026 edition) | 6 dimensions scored out of 100, weighted towards production and governance, specific to AI agents | Free, no email required to start, instant result and a PDF action plan |
8 plain-language questions, each with 4 answer levels and an "I'm not sure" option scored as zero: not knowing means not steering. The scale is deliberately strict and non-linear: high scores reward rare practices, not intentions.
Each dimension is scored out of 100, then aggregated into an overall score with extra weight on strategy and governance. The action plan prioritises your 2 or 3 weakest dimensions, adjusted to your industry: healthcare, finance and the public sector push data security and compliance to the top.
Yes. The score, the 6-dimension radar and the 3-tier action plan are free. You simply leave a work email to reveal the detail and receive a recap.
About 3 minutes: 8 questions in plain language, no jargon, with an “I’m not sure” option every time. No preparation needed.
Your company’s AI maturity across 6 complementary dimensions: strategy & vision, data & technical foundations, adoption & usage, industrialisation, skills and governance. These are the six levers that move an AI project from PoC to production.
No, quite the opposite. Every question is explained in plain language, with a concrete example for each answer, and an “I’m not sure” option that’s never penalised: we then estimate the value for you.
A PDF with your score out of 100, your 6-dimension maturity radar and your 3-stage action plan, prioritised on your weakest areas: what you can start on your own, the quick win to run with Koneetiv, and the structural project.
Your answers are used to generate your result and, if you leave your email, to send your report and prepare a possible conversation. No data resale, one-click unsubscribe.
The Koneetiv framework distinguishes 4 levels: Explorer (0-25, AI is a topic of conversation), Experimenter (26-50, real usage but barely industrialised), Industrialiser (51-75, systems in production under governance) and Pilot (76-100, AI steered as a strategic asset). Reference models, such as Gartner's 5 levels, describe a comparable progression.
Yes. Unlike generic maturity models, the industrialisation and governance questions explicitly target AI agents: systems that act autonomously on real processes. That is the criterion separating companies ready for agentic AI from those accumulating pilots.