Our first webinar of 2026 gathered facility leaders from the USA, Europe and the UK to explore how AI is being used to maximise materials recovery facility (MRF) profits around the world. Despite operating in different regions with different material flows, regulation and goals, common ground soon emerged.
Together, they shared the challenges they’re focused on this year, how they plan to use AI to overcome them, and why human expertise has become more important than ever.
Key takeaways
The barriers to facility profitability in 2026 aren’t new. Inconsistent infeed material, sorting inefficiency and evolving compliance requirements are still front-of-mind for operators and analysts, but there is a growing sense of urgency about addressing them.
Operations Analyst Brian Popovich helps Murphy Road Recycling assess their processes, and identify opportunities to improve profits. For Brian, upstream sorting efficiency remains critical, with Murphy Road’s 15 Greyparrot Analyzer units revealing the major impact of minor sorting changes:
From a financial perspective, even a 1 to 2 percent decrease in capture rate or purity can make a meaningful margin impact.
We can measure it better now, but preventing it upstream is still one of the biggest challenges we face every day."– Brian Popovich, Senior Financial Analyst at USA Waste & Recycling
Despite managing facilities thousands of miles away, GreenTech’s CTO Alan Smith also has his eye on consistency and visibility:
Our sites operate with different goals, but they all come with the same challenge, which is the variability of input material.
One of the biggest challenges we’re going to face is adapting as material changes."– Alan Smith, CTO at GreenTech
For the Netherlands’ KSI Recycling, visibility and adaptation is even more closely linked to profitability. Plant Manager Foppe-Jan de Meer explained why gathering data on more product lines is a priority for 2026:
This year, we’re focused on increasing our AI coverage to get full mass balance data for our material flows.
Our commercial goals are driven by ... avoiding penalties for products that don’t meet government standards. By tracking mass balance on output streams, we can fine-tune processes for each stream to avoid those penalties."– Foppe-Jan de Meer, Plant Manager at KSI Recycling
Each business has a different use-case for AI waste analytics, with real-time visibility into waste streams enabling them to adapt to his year’s challenges in ways that weren’t possible without waste intelligence.
GreenTech’s facilities are responding to the fluctuating quality of infeed material with data-driven material blending – using live data to find the right “recipe” for their target product purity, and historical trends to negotiate with suppliers:
It’s like having a thousand eyes on your material. There’s no other technology that gives us this level of accuracy.
We shape our recipes using the information we get live. Because we buy both high- and low-grade bales, we blend to optimise cost.
We’re also using historic information to evaluate supplier performance."– Alan Smith, CTO at GreenTech
As the operators of the USA’s “MRF of the Year” in 2025, Murphy Road Recycling have built a reputation on high-quality products. Full facility coverage has empowered their team to spot any threats to purity as they arise, diagnosing and responding to issues before they threaten quality:
We use live data to track when purity begins to swing. Dashboards and automated alerts allow operators to intervene immediately. We’re not waiting to get that information from customers 3 weeks downstream.
Purity has become one of our competitive advantages at our facility. In a rising market, we’re first out of the gate. In a declining market, buyers still want our materials."– Brian Popovich, Senior Financial Analyst at USA Waste & Recycling
At KSI Recycling, AI has become an essential pillar of process optimisation – an evolution that has led Foppe-Jan and his team to pursue full coverage of their infeed and outfeed lines this year:
We knew that our machinery became contaminated as more material was processed, and data revealed that the amount of recoverable material in residue was increasing as a result.
We’ve adapted our cleaning scheme in response. We now do it two or three times per shift, depending on whether it’s a PP line, or a Tetrapak line, for example. Now we’re able to prevent quality deviations before they happen."– Foppe-Jan de Meer, Plant Manager at KSI Recycling
AI is helping facility managers adapt to operational variables, but panelists also revealed that they’re using it to become more agile as waste regulation evolves. Waste is now a priority for environmental policymakers, but this will bring sorting and reporting challenges along with it in 2026.
Smith and the GreenTech team feel policy’s impact most clearly when sorting food-grade material. Thankfully, they have found that regulators are receptive to automation and the use of AI:
Being able to confirm that food-grade streams are less than 5% non-food grade material is the key measure. There’s no other process compared to AI in which you can do that accurately.
We did have to show the technology to regulators and explain what it does, but once that was understood, they accepted the systems’ data"– Alan Smith, CTO at GreenTech
In the Netherlands, de Meer is optimistic about achieving automated compliance reporting in 2026. What is currently a time-consuming manual process may soon be fully automated by AI:
Every month, we report on material quality to our local government. We employ three people four days a week working on manual sorting, and only gather three samples for each monomaterial stream.
By the end of this year, I expect to have automated reporting up and running. We’re working with the Greyparrot team to show regulators that the data is accurate enough for monthly reports."– Foppe-Jan de Meer, Plant Manager at KSI Recycling
The process Foppe-Jan described is already underway in the UK, where the Environment Agency is currently reviewing an AI sampling framework designed by Greyparrot analysts.
2026 may mark the year that MRFs were freed from one of their most costly obligations, and regulators gained unprecedented visibility into waste flows.
Smith, de Meer and Popovich may be advocates for AI waste analytics, but they’re not the only stakeholders impacted by adoption. Encouraging facility operators, engineers and commercial teams to adopt and trust the data gathered by systems like Analyzer is vital.
As Popovich put it:
AI can trigger alerts and identify trends, but still requires operators to act on that information quickly and correctly.
It’s not currently doing the work – that’s our team. It’s used as a tool to help make sure our operation is always moving forward."– Brian Popovich, Senior Financial Analyst at USA Waste & Recycling
Staff need to trust the data they’re acting on to achieve that forward progress, and panellists described a similar journey from skepticism to enthusiasm. Each views the initial skepticism as an essential part of the AI adoption process:
Our team were skeptical at first. That’s a good thing, because they challenged the system’s results and pushed it to its limits.
After stress-testing through the calibration process, they can now rely on the system."– Foppe-Jan de Meer, Plant Manager at KSI Recycling
For Smith, hands-on testing gave way to vocal support for AI expansion:
We saw resistance from the team at first, but once they started to interpret the data and use it to adjust recipes, there was a change in their opinions towards the technology.
Once they realised that it would make their lives easier, they really embraced it. Now they’re pushing for further facility coverage to get them more information to act on."– Alan Smith, CTO at GreenTech
Popovich noted that at Murphy Road Recycling, operators have made that feedback loop as visible as possible:
People really respond when they can see the impacts of their actions on performance. That’s why we have a live KPI dashboard displayed on a dedicated screen on the facility floor."
– Brian Popovich, Senior Financial Analyst at USA Waste & Recycling
Along with internal enthusiasm for waste intelligence, AI is driving external interest, and attracting new generation of tech-savvy leaders to the waste sector. After facing a years-long labour shortage, leaders are embracing the renewed interest in the circular economy.
Popovich has noticed that trend in the USA:
What we’ve seen across the board is people interested in working for companies investing in this modern technology. We’ve been able to use Greyparrot and other advancements as a recruitment tool."
– Brian Popovich, Senior Financial Analyst at USA Waste & Recycling
de Meer sees the same change happening in the EU:
We’ve changed our recruitment process, removing things like forklift operation from the standard skillset we expect. Afterwards, we got a different kind of person reacting.
They may not like some of the older machinery, but they do like the AI."– Foppe-Jan de Meer, Plant Manager at KSI Recycling
The webinar revealed that industry leaders now believe that that change will mean the difference between profits and losses in 2026, and the years that follow. MRFs have different priorities and different regional requirements, but for expert financial analysts like Popovich, successful facilities will have one thing in common:
Over the next five years, the sites that stay ahead will be the ones built to adjust quickly. That means investing in new technology now, training people to use and understand data, and designing operations that can absorb change rather than be disrupted by it.
If you can combine AI insights with human judgement, you’ll start outperforming your peers."– Brian Popovich, Senior Financial Analyst at USA Waste & Recycling
Learn more about the AI that KSI Recycling, Murphy Road and GreenTech are using here.