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There’s no shortage of conversation around AI and computer vision, but far less clarity on what happens after the first successful use case.

That’s exactly the focus of In Plain Sight, a podcast series by viso.ai, exploring how visual AI is moving from isolated pilots into real-world operational deployment.

In Episode 1, the discussion centres on a critical challenge: "how do you scale computer vision without creating unnecessary complexity?"

Because this is where many organisations stall.

Early success is common, whether in safety monitoring, quality control, or operational visibility. But scaling that success across sites, teams, and systems is where things become harder. Rollouts slow down, alert fatigue creeps in, and what once delivered value becomes difficult to manage.

What’s explored here is a shift in thinking:

→ Moving from simple detection to operational foresight
→ Designing systems that are structured, not disruptive
→ Building programmes that scale with control, not chaos

The episode breaks down the practical decisions that separate pilot projects from scalable strategies, highlighting why some organisations gain momentum, while others plateau after early wins.

For those working across infrastructure, logistics, manufacturing, or complex enterprise environments, the implications are clear:

Technology alone isn’t the challenge, implementation is.

And as organisations look to improve efficiency, accountability, and long-term sustainability across their operations, understanding how to scale these systems properly becomes increasingly important.

You can also meet the team from viso.ai in person at Circular Tech Expo 2026, where we bring together the organisations shaping the future of technology lifecycle, infrastructure, and enterprise systems.