The news: AI use outside of content creation still ranks low among small and medium-sized businesses (SMBs) despite interest, showing a gap between curiosity and capability.
While two-thirds of SMBs use AI for marketing and content creation, only 35% are applying it to customer service, per Revenued’s AI Usage Among Small Businesses report. Demand is strong for tools like ChatGPT for content, but many businesses still lack the confidence or readiness to deploy AI for higher-level tasks.
Other SMB AI uses:
- 28% use it to draft or edit documents and 11% for scheduling and administration.
- 5% apply AI for managing workflows, such as tracking tasks and planning projects.
- Only 1% use it for meeting notes and research, despite heavy emphasis from tools like Google’s Gemini for this use case.
Although exploration of novel use cases is moderate, interest is clear: Over 90% of respondents now use at least one AI tool in operations, up from 60% at the start of 2025.
What’s dragging AI down: One of the major hurdles for SMBs expanding their AI use is limited training and expertise among workers, which is compounded by uncertainty around spending and outcomes. Without better preparation and clearer expectations, broader AI experimentation could remain out of reach.
- 26% of SMBs cite training and skills barriers as a top concern around AI adoption, and 18% worry about accuracy and reliability of AI outputs.
- 16% are concerned about AI’s costs, and 8% see an unclear path to returns on investment.
Our take: If SMBs want AI to move beyond content creation, they’ll need to invest not just in tools but in training, governance, and measurable pilots.
To close the gap between interest and implementation, brands should:
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Use upskilling as a differentiator. Position AI education as a core aspect of employee training. Companies that equip employees now will have a competitive edge once workflows mature.
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Start with low-risk pilots. Instead of jumping straight into mission-critical tasks, SMBs can trial run AI on back-office processes like invoice drafting, crafting FAQs for websites, or basic scheduling to build internal confidence and data.
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Build trust in outputs. Combine AI with human oversight rather than replacing staff. Showing employees how AI assists their work, not threatens it, can reduce resistance and errors.