From AI Novice to AI Champion: The OECD Maturity Ladder for SMEs

What the OECD G7 AI Taxonomy Means for Your SME

In April 2026, the OECD released "Empowering SMEs in the age of AI", introducing a G7 taxonomy that classifies AI-using companies along two axes: the complexity of the AI deployed (off-the-shelf tools versus customised, agentic solutions) and the scope of deployment (isolated tasks versus organisation-wide rollout). This produces four quadrants — Novices, Optimisers, Explorers and Champions — giving you, for the first time, a diagnostic tool that shows exactly where your company stands and what the concrete next step looks like.

The Four Maturity Stages in Detail

AI Novices – 76% of AI-Using SMEs

Novices use simple, off-the-shelf AI tools for isolated tasks — most commonly in marketing, where the OECD finds 70% of off-the-shelf AI use is concentrated. The issue is rarely a lack of willingness; it is the absence of organisational embedding. Isolated tool use, however successful, does not by itself move a company forward on the ladder.

AI Optimisers – Off-the-Shelf Tools, Broader Rollout

The remaining share of AI-using SMEs — the remaining share — falls into the Optimisers quadrant: they still rely on off-the-shelf tools, but have extended their use beyond a single department to the wider organisation. The jump from Novice to Optimiser is organisational, not technological — it is about systematically transferring one successful tool to further teams.

AI Explorers – 5%, Customised but Limited

Explorers already invest in customised or agentic AI solutions, for example for demand forecasting — the OECD's most common use case for customised AI, at 39%. Deployment, however, remains confined to individual functions, typically because organisation-wide governance and data access are still missing.

AI Champions – 3.6%, Customised and Organisation-Wide

Champions combine both dimensions: customised or agentic AI solutions deployed across the entire organisation. At 3.6%, they form the smallest group — but also the one with the most demonstrable effect on productivity and competitiveness.

Where Does Switzerland Stand?

In Switzerland, roughly 34% of SMEs use AI, according to the 2025 AXA labour market study — lower than the OECD average of 61%. Yet the underlying pattern holds: the challenge here is not awareness, but organisational integration beyond isolated use cases. How Swiss leadership teams anchor AI as a management priority rather than an IT project is explored in How mid-sized companies anchor AI as a leadership priority and gain real competitive advantage.

From Novice to Champion: The Concrete Path

1. Novice → Optimiser: Stop treating successful off-the-shelf tools as isolated wins; systematically roll them out to further teams and processes.
2. Optimiser → Explorer: Define initial customised or agentic use cases where off-the-shelf tools have reached their limits.
3. Explorer → Champion: Establish governance, data access and clear ownership so customised solutions can scale across the entire organisation.

Why Organisation Matters More Than Tool Choice

The OECD taxonomy makes one thing clear: the difference between a Novice and a Champion rarely lies in the quality of the AI models used. It lies in the organisational capacity to turn a pilot into a scaled, company-wide operation. Companies that underestimate this transition tend to remain stuck in what is often called the pilot trap — running promising experiments that never scale into measurable returns.

Before investing in further tools, it is worth revisiting the strategic fundamentals: AI strategy for Swiss SMEs — avoiding the three biggest mistakes in the global race offers a grounded perspective on exactly this question.