Circular Economy operators must lean into data and AI to cope with the upcoming regulatory tsunami
By Jody Fullman, Chief Information Officer, Reconomy
The circular economy is in the midst of a profound shift. An unprecedented wave of waste and recycling regulation is making its way across Europe as governments seek to embed circularity throughout the economy. This transformation will place significant new demands on data for businesses both in terms of volume and quality.
For companies operating in the circular economy and helping businesses meet reporting requirements, they need to be looking ahead to the next five to 20 years to ensure they are match fit to support customers in complying with this rapidly changing landscape and heightened data scrutiny.
This article will look at some of the key regulatory and technological trends shaping this market and how the industry needs to adapt.
The shifting regulatory backdrop
Vast swathes of regulation are progressing across the EU and UK and are due to come into effect over the next few years. One of the main pieces of legislation is Extended Producer Responsibility (EPR) requiring producers to fund the collection, sorting and recycling of products they place on the market. EU member states are already required to operate EPR schemes for packaging, batteries, WEEE electronics, and the EU recently approved new regulations to extend EPR to additional sectors, most notably textiles.
The EU is also developing Digital Product Passports to provide a digital record of a product’s complete lifecycle. Meanwhile, the UK is set to deploy one of the world’s largest Deposit Return Schemes (DRS) in 2027 and is also establishing a Digital Waste Tracking System to replace the current paper-based method with a transparent digital system to monitor waste from creation to disposal. Together, these initiatives represent seismic shifts in how data is captured and managed.
Robust data platforms with new global products will be needed
To remain competitive for the next 20 years, circularity operators must have best-in-class data and technology platforms capable of handling this explosion of information.
Operators will need to move away from legacy, fragmented and monolithic technology stacks to modern, cloud-native data platforms that can process vast quantities of unstructured data from multiple sources. These platforms must then be able to turn this data into structured, actionable insights that customers can use to meet their reporting obligations and drive better decision-making about product design, reuse and recycling.
Digitising the supply chain
A crucial step in achieving this readiness is digitising the supply chain, replacing manual, email-based data collection with automated connectivity that provides real-time operational visibility and data sharing between customers, suppliers and central systems.
The advantages to customers
By investing in these data-driven systems, circular economy operators can deliver far more transparent and efficient services. Customers can benefit from faster data transfer, fewer manual interventions and greater data accuracy and consistency.
One of the most significant opportunities for customers – particularly those in the FMCG, grocery and fashion sectors – is the potential to use these data insights to drive better decision-making about product design which can materially lower costs under schemes such as EPR.
Customers in these sectors can use detailed reporting to understand precisely what packaging or textile materials they are currently placing on the market and how that compares with their peers, enabling them to redesign products to lower packaging weights, improve recyclability and cut costs.
Be in lockstep with customers
Ultimately, circularity operators will need to evolve in lockstep with their customers who are themselves investing heavily in AI and data platforms. Those who invest early in scalable infrastructure platforms will be able to lead the next wave of innovation across the circular economy and play a pivotal role in helping businesses optimise resources, prevent waste, lower carbon emissions and costs.
FAQs: Understanding data, AI and circularity
Data provides the visibility needed to understand where materials come from, how they’re used and where they end up. With accurate data, businesses can identify inefficiencies, measure circularity progress and make smarter decisions about reuse, recycling and resource recovery.
AI enables automation and prediction. It can help operators optimise waste collection routes, identify reusable materials, or model the impact of design changes on recyclability, turning data into actionable insights that drive sustainability and savings.
Many supply chains still rely on manual, disconnected systems. The challenge is to integrate data across suppliers, customers and regulators securely and in real-time. Doing so requires modern cloud-based infrastructure and strong data governance frameworks.
Reconomy’s tech-enabled, people-powered approach combines data platforms, digital connectivity and regulatory expertise to help organisations close the circularity gap. From compliance and reporting to design optimisation and reuse logistics, our integrated solutions make circularity achievable and measurable.
Artificial intelligence is set to be one of the most powerful enablers of the circular economy. By combining human expertise with advanced analytics, AI can turn raw data into insight, driving smarter design, efficient operations, and measurable sustainability outcomes.
Design
AI can model and optimise product lifecycles from the outset, helping designers choose materials that are easier to reuse or recycle, predict how products will perform over time, and assess the environmental impact of design decisions. This reduces waste before a single item is made.
Operations
Within operations, AI can automate resource management, optimising waste collection routes, predicting maintenance schedules, or dynamically matching supply with demand. This reduces downtime, energy use and unnecessary emissions while improving traceability.
Business models
AI enables new circular business models such as product-as-a-service, repair and resale platforms, and data-led take-back schemes. These models not only extend the life of products but also create new revenue streams while supporting compliance goals.
– Learn more about circular economy business models
Infrastructure
AI-driven analytics have the potential to underpin circular infrastructure, from smart materials recovery facilities to connected logistics networks. These systems can learn from data patterns to continuously improve performance and reduce resource waste at scale.
Data and decision making
Data is the foundation of circularity, and AI is the engine that makes sense of it. By processing large, complex datasets from across the supply chain, AI provides actionable insights that help businesses understand material flows, track compliance, and identify areas for improvement.
Challenges and risks
While AI offers transformative potential, it also brings challenges, from the energy demands of training algorithms to the need for transparent governance. There is a risk that, without careful oversight, AI could unintentionally reinforce unsustainable practices or lead to greenwashing if data is used without proper verification.
Policy and regulatory alignment
As technology advances, policy frameworks must evolve in step. Regulators need to keep pace with innovation, ensuring that AI tools are deployed ethically and that data integrity and privacy remain protected. Strong governance will be essential to maintain public trust and drive genuine circular outcomes.
Reconomy’s Circular Economy Framework
To make circularity real, we need consistent, enabling infrastructure. That’s why Reconomy has proposed a 10-point regulatory framework covering:
- Seven key resource streams across key sectors, such as fashion (e.g. textiles, packaging, electronics).
- How to embed the four waste management methods (reuse, recycling, recovery, and compliance)
- Incentives for landfill reduction, better separation, and investment in infrastructure innovation.
Read our full framework to understand how we can simplify, scale, and regulate for a circular economy.
Download our circular economy frameworkFurther reading and resources
Wanting to learn more? Explore further reading and resources available from Reconomy.