Digital Enablers of Circularity
Why information is the missing ingredient
Many circular economy strategies fail not because they are technically impossible or economically unviable, but because the right information is not available at the right moment to the right decision-maker. Digital technologies, including the Internet of Things, artificial intelligence, blockchain, and the Digital Product Passport mandated by the ESPR, are rapidly changing this, making circular loops visible, traceable, and actionable at scale.
The Information Problem in Circular Economy
The circular economy is fundamentally an information problem as much as a material one. Consider the chain of decisions required to circulate a product effectively. A repair technician needs to know what components the product contains and how to access them. A refurbisher needs to know the product's service history and remaining useful life. A recycler needs to know what materials are present and whether they contain hazardous substances. A secondary market buyer needs to know the product's condition and provenance.
Without this information, each party must either guess (leading to poor decisions and lost value) or invest in costly inspection and testing (adding friction that makes circular pathways economically uncompetitive). Digital technologies eliminate this information asymmetry by creating persistent, accessible records that travel with products throughout their lifecycles.
The Digital Product Passport (ESPR Article 9)
The most significant digital enabler of the circular economy in the regulatory sphere is the Digital Product Passport (DPP), mandated by Article 9 of the EU Ecodesign for Sustainable Products Regulation (ESPR, 2024/1781). The DPP is a standardised digital record, accessible via a data carrier (QR code, RFID chip, barcode) on the physical product, that provides key information about the product's environmental performance, material composition, and end-of-life instructions.
| Stakeholder | Information Needed | DPP Enables |
|---|---|---|
| Consumer | Environmental performance; repairability score | Informed purchasing; access to repair services |
| Independent repairer | Disassembly instructions; spare parts list; compatibility | Efficient repair without proprietary barriers |
| Refurbisher | Component status; service history; remaining life indicators | Accurate assessment for secondhand market pricing |
| Recycler | Material composition; hazardous substance location; disassembly sequence | Targeted material recovery; safe handling of hazardous content |
| Customs authority | Compliance status; product origin; environmental performance | Verification of ESPR compliance at border |
| Investor/ESG analyst | Lifecycle environmental footprint; circularity metrics | Comparable sustainability data across products and suppliers |
Technical Architecture of the DPP
The ESPR specifies several key architectural requirements for the Digital Product Passport. These requirements are designed to ensure that the DPP ecosystem is interoperable across industries and borders, accessible to diverse stakeholders, and resistant to data loss or manipulation:
- Decentralised management: DPP data is managed by economic operators (manufacturers, importers, distributors) rather than stored centrally by a government body, enabling faster adoption and reducing data sovereignty concerns.
- Unique product identifiers: Each product has a unique identifier linked to a centralised EU registry managed by the European Commission, enabling customs and enforcement access without requiring access to the full data set.
- Differentiated access rights: Different stakeholders receive access to different data layers. Consumers see simplified summary information. Repairers see technical documentation. Regulators see compliance data. Some commercially sensitive data is protected.
- Data carrier integration: Physical products must carry a data carrier (QR code, RFID, or similar) that provides the minimum information specified for the product category, ensuring access even without internet connectivity.
- Backup requirements: Independent service providers must maintain backup copies to ensure continuity if the manufacturer ceases to operate.
Analogy: The DPP as an Aeroplane's Logbook
Every commercial aircraft carries a comprehensive logbook recording every maintenance event, component replacement, inspection, and service check across its operational life. This logbook is mandatory, standardised, and accessible to all authorised parties: airlines, maintenance organisations, regulators, and potential buyers. It is precisely this information infrastructure that makes second-hand aircraft commercially viable and aviation safety auditable. The Digital Product Passport applies the same principle to consumer and industrial goods.
Internet of Things: Real-Time Product Intelligence
The Internet of Things (IoT) connects physical products to digital networks, enabling real-time monitoring of product condition, performance, and location. For circular economy purposes, IoT capability transforms passive products into active participants in circular systems, providing data that enables smarter maintenance, more accurate end-of-life timing, and optimised logistics for collection and recovery.
Rolls-Royce's TotalCare jet engine management system uses thousands of sensors per engine, streaming real-time performance data to engineering teams that monitor for early signs of component fatigue or failure. This predictive maintenance capability not only prevents costly in-service failures but enables Rolls-Royce to plan component overhauls at optimal timing, extending service intervals and reducing total maintenance cost while maximising engine life.
Artificial Intelligence and Circular Economy
Artificial intelligence is transforming circular economy operations across several domains:
- Waste sorting: AI-powered robotic sorting systems can identify and separate materials from mixed waste streams with greater accuracy and speed than human sorters, dramatically improving the quality and quantity of recovered secondary materials. Companies like AMP Robotics deploy machine learning systems that can sort over 80 material categories at speeds exceeding 160 picks per minute.
- Demand forecasting: AI can optimise inventory and logistics in sharing and leasing models, ensuring assets are available where they are needed and reducing dead inventory and excess repositioning movement.
- Design optimisation: Generative design AI can explore thousands of structural configurations for a given product, identifying designs that achieve required performance with minimum material use, automatically integrating circularity constraints such as single-material construction or standard fastener requirements.
- Market matching: AI platforms can match waste streams with potential users across industries and geographies, reducing the search costs that prevent industrial symbiosis relationships from forming.
Blockchain and Material Traceability
Blockchain technology provides immutable, transparent records of material flows and product histories. For circular economy applications, blockchain enables certification of recycled content claims, traceability of critical raw materials from mine to product to recycler, and verification of sustainable sourcing claims across complex supply chains.
Several pilot programmes have demonstrated blockchain's potential for circular economy traceability. The Renewal Workshop, which operates refurbishment programmes for apparel brands, uses blockchain to record the full provenance and refurbishment history of garments, enabling verified "circular fashion" claims that consumers and retailers can trust. The Everledger platform applies similar technology to diamonds, tracking stones from mine to consumer to detect conflict diamonds and enable legitimate secondhand trading.
Example: AMP Robotics and AI-Powered Waste Sorting
AMP Robotics has deployed AI-powered sorting robots at waste management facilities across the United States, Europe, and Asia. Each robot combines computer vision (trained on millions of images of waste materials), robotic manipulators, and real-time machine learning to identify and sort materials from mixed recycling streams. At one US facility, AMP Robotics robots increased material recovery rates by 35% while reducing labour costs by 60%. The system learns continuously, improving accuracy as it encounters new packaging designs and material combinations. As digital product passport information becomes available, AI sorters will be able to confirm material composition rather than inferring it from visual appearance alone.
Platform Economies and Circular Markets
Digital platforms have created circular markets that would have been prohibitively expensive to operate in the pre-digital era. eBay and Craigslist enabled peer-to-peer secondhand markets at national scale. Airbnb created global sharing for accommodation. Vinted and Depop have created fashion resale markets reaching millions of users. These platforms work by eliminating the information and transaction costs that previously made secondhand and sharing markets thin and local.
The next generation of circular platforms, supported by Digital Product Passport infrastructure, will extend these markets to complex manufactured goods where information asymmetry has historically been greatest. Industrial component trading platforms, certified refurbished electronics marketplaces, and building material salvage exchanges are all emerging as the DPP creates the information trust needed to make these markets liquid and scalable.
A digital twin is a virtual replica of a physical product, system, or process that receives real-time data from its physical counterpart and enables simulation, analysis, and optimisation without physical intervention. For circular economy purposes, digital twins enable designers to simulate the full lifecycle of a product before it is manufactured, testing different design choices against circularity metrics, maintenance scenarios, and end-of-life recovery pathways.
Siemens has developed digital twin capabilities for industrial equipment that track component wear in real time and predict remaining useful life with high accuracy. This enables maintenance to be scheduled at optimal timing: not too early (wasting component life) and not too late (risking failure and unplanned downtime). The same digital twin provides the end-of-life intelligence needed to plan disassembly and material recovery operations efficiently. As the technology matures, digital twins will become standard infrastructure for circular economy operations at the product and factory level.
Key Takeaways
- 1The circular economy is fundamentally an information problem: digital technologies eliminate the information asymmetry that makes circular pathways uncompetitive
- 2The Digital Product Passport (ESPR Article 9) travels with each product and provides differentiated access to material composition, repairability, service history, and disassembly instructions for consumers, repairers, recyclers, and regulators
- 3IoT sensors enable real-time product monitoring that supports predictive maintenance, optimised service timing, and smarter end-of-life recovery planning
- 4AI-powered robotic waste sorting can identify over 80 material categories at 160 picks per minute, improving recovery rates by 35% or more versus manual sorting
- 5Blockchain enables verifiable traceability of recycled content, critical material sourcing, and circular product claims across complex supply chains
- 6Digital platforms have created the information infrastructure for circular markets in secondhand goods; Digital Product Passports will extend this to complex manufactured goods where information asymmetry has been greatest