Bentley Introduces AI System to Enhance Leather Quality

We start with a shift that’s capturing the attention of forward-thinking manufacturers: the move beyond generative AI into something more dynamic. Agentic AI is gaining traction for its ability to take real-time action across production plants – monitoring, responding, and learning on the fly. It’s no longer just about generating insights; it’s about executing them autonomously.

But smart decisions still depend on solid data foundations. This week, we take a closer look at why integrated analytics systems are key to scaling advanced AI tools. When data silos fall, true end-to-end visibility starts to emerge. So where do most businesses get stuck?

In food production, AI is being used to reduce waste and improve line efficiency. One team of researchers is helping companies pilot real-time forecasting tools – and the early results are looking promising. Could better AI access drive innovation in this heavily regulated sector?

Meanwhile, a new camera network is quietly improving surface inspection for complex components. By blending autofocus optics with edge AI, this system is catching tiny defects – faster and more consistently than human eyes ever could.

Elsewhere, the luxury sector is using AI not to replace craftsmanship but to enhance it. One recent deployment is transforming the way leather hides are inspected for imperfections, helping artisans work with only the finest materials – without sacrificing sustainability goals.

Across the board, enthusiasm for AI is clearly growing. A recent report found that over 90% of manufacturers plan to ramp up AI investment within the next two years. But many are still navigating the same familiar obstacles: siloed data, talent shortages, and unclear governance.

Which brings us to a more sobering finding: less than a third of businesses that identify as ‘advanced’ in AI have actually brought use cases to market. So what’s holding things up – and what separates the experimenters from the implementers?

One company offers a real-world snapshot of what works. By focusing AI deployments on measurable wins – like predictive maintenance, intelligent order management, and chatbot-guided problem solving – they’ve built momentum and trust with every iteration. It's a reminder that AI doesn't have to be big to be impactful.

And finally, a thoughtful perspective on how AI can help future-proof the UK’s manufacturing base. Could new technology help solve the workforce gap, not by replacing workers, but by elevating their roles?

We hope you enjoy this week’s insights and, as always, to stay ahead of the curve in the world of alternative protein production, you can follow us on LinkedIn for daily updates and breaking news. In the meantime, we hope you have another amazing week!

Bentley Introduces AI System to Enhance Leather Quality

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