Your Team Already Has More AI Capability Than You Realise

Most business leaders worry their organisation is falling behind on AI. They see headlines about transformation, read case studies from enterprises with dedicated innovation teams, and wonder how their own business will ever catch up.

But here's what I've learned from working with dozens of SMEs across manufacturing, retail, financial services, and the charity sector: most teams have far more AI capability than they realise.

The problem isn't lack of adoption. It's lack of visibility.

The Hidden AI Landscape in Your Business

Last week I ran an AI and automation workshop with Dogs for Good, a charity that creates life-changing partnerships between people and assistance dogs. We started with a simple question: "Who's using AI, and for what?"

The room lit up.

People were genuinely surprised – sometimes amazed – at what their colleagues were already doing. The finance team had been using AI to streamline donor communications. The puppy training coordinators were experimenting with content generation for social media. The events team had discovered ways to automate enquiry responses.

None of this was coordinated. None of it was formally tracked. And critically, none of it was visible across the organisation.

What Visibility Unlocks

Once the team could see what was already happening, something shifted. The conversation moved from "Should we be doing this?" to "What else could we do?"

By the end of the session, they'd identified use cases that will genuinely transform their work:

• Better triaging of public enquiries to reduce admin burden

• Enhanced content planning that maintains their authentic voice at scale

• Educational games to support their outreach and awareness programmes

• Process improvements that free up time for the work that truly matters – supporting people and dogs

The breakthrough wasn't about introducing new tools or complex systems.

It was the team showing each other what was already possible.

Why This Pattern Matters

I've seen this same dynamic play out in manufacturing businesses, professional services firms, retail operations, and now charities. The pattern is consistent:

• Individual team members are experimenting. 

  They've found AI tools that solve immediate problems. They're getting value. But they're doing it quietly, often unsure whether it's "allowed" or whether anyone else would care.

• Leadership assumes there's limited activity. 

  Without visibility, senior teams underestimate how much capability already exists in the organisation. They worry about getting started when, in reality, dozens of people have already begun.

• Knowledge stays siloed. 

  The marketing person who's cracked content repurposing doesn't know the operations manager has solved a similar problem with process documentation. The finance team's breakthrough with report generation never reaches the sales team struggling with proposal writing.

• Potential stays unrealised. 

  Without cross-pollination of ideas and approaches, teams miss obvious opportunities to apply successful experiments in new contexts.

The Confidence Paradox

This connects to something I call the confidence paradox in AI adoption. Business leaders simultaneously over-estimate and under-estimate what AI can do.

They over-estimate the sophistication required – assuming AI adoption needs enterprise-scale investment, dedicated teams, or technical expertise most SMEs don't have.

They under-estimate what's already achievable – missing the fact that practical, valuable AI usage is already happening in their business, often with free or low-cost tools.

The result? Paralysis at the leadership level while experimentation flourishes underground.

Making the Invisible Visible

The solution isn't complicated, but it does require intentional action.

• Create space for sharing.

  Regular forums where team members can demonstrate what they're doing with AI – not formal presentations, just "show and tell" sessions that make experimentation visible and valued.

• Document what's working. 

  Simple records of which tools are being used, for what purposes, and with what results. This doesn't need to be a complex knowledge management system. A shared document works fine.

• Celebrate experimentation. 

  Make it clear that trying things, learning, and sharing findings is valued behaviour. Remove the uncertainty about whether AI usage is "allowed."

• Connect the dots. 

  Help teams see patterns across different departments. When the finance team's solution mirrors a problem in operations, make that connection explicit.

• Give people permission. 

  Many teams are waiting for formal guidance before they feel confident experimenting openly. Simple, clear guidance about what's encouraged and what's off-limits transforms shadow AI into confident innovation.

From Individual Experiments to Organisational Capability

What happened at Dogs for Good illustrates a broader principle: your organisation's AI capability isn't determined by what leadership has commissioned. It's determined by what your people are already doing – plus what becomes possible when they can see and build on each other's work.

The teams that are winning with AI aren't necessarily the ones with the biggest budgets or the most sophisticated strategies. They're the ones that have made their existing capability visible, created conditions for safe experimentation, and helped knowledge flow across departmental boundaries.

If you're a business leader wondering how to "get started" with AI, there's a good chance your team has already started. Your job isn't to drive adoption from scratch. It's to surface what's already happening, remove barriers to sharing, and help your people realise the capability they already possess.

Huge thanks to Ed Bracher OBE and the brilliant Dogs for Good team for the opportunity to work with them. (And to Tobi the assistance dog for stealing the show and reminding everyone what truly matters.) Learn more about their life-changing work at dogsforgood.org.

This insight is part of an ongoing series exploring the real challenges SME leaders face with AI adoption. If you're navigating similar questions in your business, let's talk.