Study
SustainabilityRecentStrong effect

AI Capabilities Accelerate Circular Business Models

Artificial intelligence offers significant potential to enhance the efficiency and implementation of circular business models by enabling integrated intelligence, process automation, robust infrastructure, and ecosystem orchestration.

Technological Forecasting and Social Change · 2024

01

Key Findings

  • 01AI can act as an efficiency catalyst for circular business models.
  • 02Four pivotal AI capabilities are identified: integrated intelligence, process automation and augmentation, AI infrastructure and platform, and ecosystem orchestration.
  • 03Firms often face challenges in developing sophisticated processes and routines to effectively utilize AI for circular business models.
02

Application

Design takeaway

Integrate AI capabilities strategically into the design and operation of circular business models to enhance efficiency and overcome implementation hurdles.

How to apply

When designing a new product or service with circularity in mind, consider how AI can optimize material flows, predict product lifecycles, facilitate remanufacturing, or enable better end-of-life management.

Project actions

  • 01Consider how AI tools could be used in your design project to improve resource efficiency or product longevity.
  • 02Research specific AI applications relevant to your chosen circular business model (e.g., AI for waste sorting, AI for predictive maintenance).
03

Method & Evidence

AimHow can AI capabilities be leveraged to enable and accelerate the adoption of circular business models?
MethodLiterature Review and Synthesis
ProcedureThe researchers conducted a comprehensive review of existing literature to identify and synthesize the key AI capabilities that are essential for the successful implementation of circular business models. They developed a framework to categorize these capabilities and map their role in overcoming adoption barriers.
ContextBusiness strategy and technology adoption for sustainability

Variables

IV["AI Capabilities (Integrated intelligence, Process automation, AI infrastructure, Ecosystem orchestration)"]
DV["Effectiveness and adoption of Circular Business Models (CBMs)"]
CV["Industry sector, Company size, Existing technological infrastructure, Regulatory environment"]
04

Strengths & Limitations

Strengths

  • +Provides a synthesized framework of AI capabilities for CBMs.
  • +Identifies key barriers and pathways for AI integration in circularity.

Limitations

The research is a synthesis of existing literature, so practical implementation details and specific case studies might be limited.

Reliability & validity

The reliability and validity of this synthesis depend on the quality and comprehensiveness of the reviewed literature. The framework's validity is supported by its ability to categorize and explain the relationship between AI and CBMs.

Think critically

To what extent are the identified AI capabilities universally applicable across all types of circular business models, or are they context-dependent?

05

Design Principles

"Leverage AI for enhanced efficiency and integration within circular systems."

As the demand for sustainable practices grows, understanding how emerging technologies like AI can support circular economy principles is crucial for design and business strategy. This insight highlights specific AI capabilities that can be leveraged to overcome implementation challenges and drive successful circular business model adoption.

06

What This Means for Your Design

AI can make circular business models work better by helping companies manage resources more efficiently, automate processes, build the right tech systems, and work with partners.

How to use in your project

  • 1.Use this research to justify the integration of AI in your design process for a circular product or system.
  • 2.Cite this paper when discussing the technological enablers of circular business models in your design project.
07

Add to My Project

08

Quick Cite

(2024). Artificial intelligence capabilities for circular business models: Research synthesis and future agenda. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2023.123189 Retrieved from https://designdex.org/study/8e8efab2-a2a9-437e-bd81-36e6c84c1c43/ai-capabilities-accelerate-circular-business-models

Paragraph starter

This research highlights the critical role of Artificial Intelligence in enabling and accelerating circular business models. By developing capabilities in integrated intelligence, process automation, AI infrastructure, and ecosystem orchestration, organizations can overcome significant barriers to circularity, leading to enhanced efficiency and resource management.

09

Source

Technological Forecasting and Social Change

Artificial intelligence capabilities for circular business models: Research synthesis and future agenda

journal · 2024

View source

Questions about this research

What does the research say about ai capabilities accelerate circular business models?
Integrate AI capabilities strategically into the design and operation of circular business models to enhance efficiency and overcome implementation hurdles. Evidence: Technological Forecasting and Social Change (2024).
Why does "AI Capabilities Accelerate Circular Business Models" matter for design?
As the demand for sustainable practices grows, understanding how emerging technologies like AI can support circular economy principles is crucial for design and business strategy. This insight highlights specific AI capabilities that can be leveraged to overcome implementation challenges and drive successful circular business model adoption.
How can designers apply this research?
Integrate AI capabilities strategically into the design and operation of circular business models to enhance efficiency and overcome implementation hurdles.
What were the main findings?
AI can act as an efficiency catalyst for circular business models.. Four pivotal AI capabilities are identified: integrated intelligence, process automation and augmentation, AI infrastructure and platform, and ecosystem orchestration.. Firms often face challenges in developing sophisticated processes and routines to effectively utilize AI for circular business models.
What research method was used?
Literature Review and Synthesis.
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2024 journal from Technological Forecasting and Social Change.
What should I do differently in my next project?
When designing a new product or service with circularity in mind, consider how AI can optimize material flows, predict product lifecycles, facilitate remanufacturing, or enable better end-of-life management.
What are the limitations?
The research is based on a synthesis of existing literature, and practical implementation challenges may vary across industries and organizational contexts.
Is there evidence that circular business affects design outcomes?
Artificial intelligence can significantly boost the effectiveness of circular business models, but companies need to develop specific capabilities in areas like data integration, automation, technological infrastructure, and collaborative networks to fully realize its potential. As the demand for sustainable practices Source: Technological Forecasting and Social Change (2024).
Where does this business models research apply?
Business strategy and technology adoption for sustainability It sits within sustainability research on designdex.org.

Related research topics

circular business design research · evidence on circular business · does circular business improve design outcomes · business models studies for designers · circular business and business models findings · sustainability research evidence