Technological innovation is helping companies level up their operations while embedding sustainability at their core.

Technology is a key enabler for business transformation, especially in today’s time where breakthrough innovations enter the market at a high frequency. In Capgemini’s recent engineering and R&D trends survey, 63% of executives identified innovation and value creation through digital technologies as strategically important for their engineering and R&D functions over the next 12 to 18 months.

But how do these technologies help build more sustainable businesses? Let’s take a look.

Rewriting the sustainability narrative with AI

AI-based solutions are already transforming operations across industries in dramatic ways. They are quickly processing tremendous amount of data from disparate sources, increasing the speed of complex simulations and generating and validating design iterations for physical and software products.

As  sustainability regulations come into effect, AI’s role becomes even more impactful.  New requirements are stringent and range from providing product performance metrics for e.g. digital product passports, reducing environmental footprints and natural resource usage to improving material circularity and energy efficiency.

Meeting these demands requires engineering solutions to provide real-time, precise and reliable results, while using heterogenous data and information originating from multiple sources within one company and its value chain. This, by design, implies that enterprises must integrate multiple modalities: Text, diagrams, engineering models, and large volumes of product and manufacturing data, often including legacy and unstructured sources. By embedding AI into engineering workflows, organizations can improve decision-making and support sustainable design choices that meet regulatory and market demands.

As a part of data-driven product design, AI is reshaping how industries discover, design, test, and scale new materials. What once took years of trial and error in the lab can now be accelerated to months or even weeks through data-driven modelling, simulation, and generative design. For any company dealing with sustainable materials, recyclability, circular product design, or low carbon product development, AI is rapidly becoming indispensable.

When paired with other forms of technology, the potential gains multiply. For example, take digital twins, which are digital representatives of a real-world product or system. They are used across a wide range of industries and application areas. For example, car manufacturers use digital twins to simulate, test, and refine various aspects of vehicle development. This allows companies to e.g. optimize material use, improve design features, technical performance, and in-use energy consumption, reducing the environmental impact across the entire lifecycle of products.

Shifting the playing field with next-gen materials and bioengineering

Innovations in materials engineering are also poised to redefine sustainable business. Companies are working to create next-generation materials that are more efficient, adaptable, and durable, making them a win for sustainable engineering. Consumer Products’ companies seeking for more sustainable ingredients to replace harmful substances; the fashion industry is looking for leather alternatives; Car manufactures need to replace plastics in the interior; the Aviation industry is in need for more sustainable alternatives compared to kerosene – the list is endless, the demand for more sustainable materials is extremely high.

Developments in bioengineering are also driving sustainability. Companies are developing new enzyme- and culture-based technologies with the aim of replacing chemical-intensive processes. This shift would make production processes across industries – from food to consumer goods – more efficient and less polluting. AI is also accelerating advancements in engineering for agriculture, healthcare, and other fields. By optimizing water use, minimizing waste, and improving production processes, AI-driven bioengineering directly contributes to more sustainable operations.

The future is here with quantum technology

Quantum technologies have moved from theoretical physics labs into practical engineering applications, bringing concrete benefits for sustainability. While full scale quantum computing is still emerging, today’s advancements are already reshaping how engineers design and optimize complex systems at all scales – small molecules to simulations of complex systems. Quantum computers excel at solving optimization, chemistry, and simulation problems that are extremely hard for classical computers. In engineering, this is already changing the game for sustainability by enabling:

  • Material discovery and chemistry simulation (e.g., for electric vehicle batteries and hydrogen catalysts for electrolyzers)
  • Complex optimization in product and system design (e.g., lightweight structural or aerodynamic design)
  • Digital twins enhanced by quantum computing (e.g., to create more realistic multi-physics models or investigate chemical reactions in fuel cells, batteries or hydrogen systems)

Key takeaways

Sustainability and advanced digital engineering technologies are fundamentally intertwined. What truly stands out is how rapidly emerging technologies like AI, digital twins, bioengineering, and even quantum technologies are converging to reshape sustainable engineering.

Ultimately, the message is clear:

  • Technology is no longer just supporting sustainability goals. It is defining the next era of engineering
  • Sustainability is becoming a dynamic, technology-driven innovation space where engineering excellence and environmental responsibility finally move forward together.

Read the rest of our Engineering R&D Pulse 2026 report here.