AI use in product design key to lowering environmental impact
A new report by Tech Mahindra and MIT Technology Review Insights states that 80% of a product's environmental impact is determined during its design stage.
The report explores how enterprises can leverage artificial intelligence to enhance sustainability outcomes in product design and development, noting that the use of AI-powered tools - such as digital twins, simulations, and rapid prototyping - can significantly optimise designs for functionality, manufacturability, and sustainability. According to the research, these tools can contribute to a marked reduction in waste, emissions, and use of resources.
AI and design
The study underscores that while adoption of AI in product development is increasing, most organisations remain in exploratory phases. Full-scale implementation of AI tools in these processes is still limited, with enterprises citing cost, knowledge gaps, and fast-changing market dynamics as significant barriers to broader adoption.
Regulatory and societal pressures are also mounting, with businesses expected to balance the dual demands of continual innovation and shrinking environmental footprints. This is placing an increased emphasis on integrating sustainability considerations into every stage of product development.
"Enterprises today are under increasing pressure to innovate while reducing their environmental footprint. At Tech Mahindra, we empower enterprises to achieve this by embedding AI into the earliest stages of product development through tools like digital twins, simulations, and rapid prototyping. The joint study with MIT Technology Review Insights reinforces the importance of measurable, AI-driven frameworks that reduce emissions and help businesses future-proof their models responsibly," said Narasimham RV, President - Engineering Services, Tech Mahindra.
Sustainability challenges
According to the report, nearly 80% of a product's environmental impact is set at the design stage, highlighting the critical role of early-stage decisions in sustainability outcomes. AI-driven modelling tools are positioned as strong enablers of this approach, allowing companies to move toward optimised and more sustainable products early in the process.
However, the study highlights key challenges that remain. Among these are customer confusion about what constitutes a genuinely sustainable product, rapidly evolving regulations and standards, a shortage of specialised talent, and the absence of clear sustainability metrics for organisations to track and report progress.
Metrics and frameworks
The report argues that measurable sustainability metrics and AI-led frameworks are crucial if businesses are to overcome these hurdles and realise tangible environmental and commercial benefits. Enterprises capable of implementing such systems, the study claims, can gain a substantial competitive advantage, particularly as scrutiny from regulators and consumers grows.
"The joint study with MIT Technology Review Insights reinforces the importance of measurable, AI-driven frameworks that reduce emissions and help businesses future-proof their models responsibly," said Narasimham RV.
Competitive advantage
Alongside detailing current industry limitations, the report suggests that integrating AI into existing design processes not only aligns enterprises with sustainability targets but may also foster innovation and long-term business resilience. Leveraging AI to meet sustainability objectives is seen as both a response to external pressures and a driver for fresh approaches in product development.
The report concludes that organisations able to adopt measurable AI-led frameworks and overcome these persistent challenges may find sustainability to be an engine for transformation, ensuring both compliance with new expectations and contributions to broader environmental goals.