Most SMEs Use AI; Few Measure Real Returns

# Quick summary Most small and medium enterprises (SMEs) are already using AI tools, but very few are extracting measurable business value. The difference between experimenting with AI and embedding it into operations and strategy explains why adoption hasn't translated into returns for most businesses.

# What the data shows

• Reported programme data indicates 98% of participating small businesses use AI in some form. These uses are often for quick wins such as content generation, administrative tasks, and basic automation.

• Almost 90% of AI-related hiring is concentrated within just 1% of companies, meaning deep internal capability and long-term investment are heavily skewed toward a tiny slice of firms.

# Why most SMEs aren't seeing returns There are three linked reasons in the reporting:

• Tactical use instead of strategic integration: many firms use point tools (for example, for content or admin), but they don't connect tools to business outcomes or workflows.
• Lack of measurement: with only 18% tracking ROI, leaders lack the feedback needed to iterate, prioritise, or scale high-impact uses.
• Resource concentration: large and well-resourced firms absorb the talent and hiring for AI, so most SMEs lack the people and infrastructure to move beyond experimentation.

# What institutions are doing Goldman Sachs is positioning itself to work with SMEs on AI adoption beyond short-term consulting, investing in advisory and support infrastructure and expanding presence outside London into cities such as Birmingham. The strategy aims to build longer-term commercial relationships with SMEs as they scale.

# Practical implications for SME leaders

• Start measuring: define simple, repeatable metrics for each AI initiative (time saved, lead conversion lift, cost per unit reduction) and track them.
• Prioritise depth over breadth: focus scarce resources on one or two high-impact integrations rather than many low-value experiments.
• Look for external partnerships that go beyond a one-off project to ongoing advisory and operational support.

# Where competitive advantage will form The reporting points to a coming split between businesses that remain in an experimentation loop and those that adopt AI as a core component of decision-making and operations. SMEs that embed AI into business models and measurement systems will be able to demonstrate tangible returns and scale more sustainably.

# Bottom line AI adoption among SMEs is widespread, but adoption alone isn't enough. Measurable impact depends on intentional strategy, clear metrics, and sustained capability. Firms and institutions that help SMEs bridge that gap stand to gain longer-term commercial relationships.