Convergence transformation The combination patterns in engineering biology demonstrate how biological and digital systems are becoming increasingly intertwined, creating transformative capabilities that extend far beyond traditional applications. These combinations, empowered by advancements in AI, have significantly accelerated the value chain transformation into new product categories and can now address previously unsolvable challenges. Traditionally, engineering biology technologies operated mainly in the healthcare industry, with long go-to-market strategies due to extensive research and development as well as certifications. Now, with recent breakthroughs in AI, it is transforming the value chain by enabling engineering biology to learn from data, recognize patterns, and be much more precise and tailored to complex environments, creating new applications in consumer goods, energy and the food industry.As engineering biology technologies continue to mature, investors remain optimistic about the potential of start-ups in this field.17 Venture investment appears to have stabilized at levels seen prior to the COVID-19 pandemic-era spike. However, due to the inherent technological complexity, high capital requirements and extended go-to-market timelines, capturing investor interest remains challenging. As narratives increasingly shift towards planetary outcomes, application areas beyond healthcare are expected to become more attractive for investment. The cross-cutting and technologically complex nature of the engineering biology technology poses significant barriers in devising comprehensive yet efficient policy and regulatory frameworks. Early policy decisions are especially influential, as they shape the speed and scale at which bio- based, tech-driven approaches can be adopted. Momentum varies widely across regions, influenced by national priorities, regulatory readiness and the ability to integrate bio-based innovation into broader industrial strategies. CASE STUDY 6 The Commonwealth Scientific and Industrial Research Organisation (CSIRO) The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has embraced application and development of AI for scientific research, incorporating advanced ML capabilities directly into its scientific workflows. By integrating AI specialists into multidisciplinary research teams, CSIRO enhances its ability to achieve precise molecular design, optimize complex biological processes and perform real-time experimentation across various scientific disciplines. These initiatives accelerate research, enabling rapid simulation and iterative development. They reinforce CSIRO’s leadership in engineering biology and enhance its capacity to address complex challenges across healthcare, agriculture and energy sectors. This approach creates a continuous feedback loop of innovation, significantly amplifying CSIRO’s cross-industry impact. AI for plant protein AI-driven biological modelling to optimize crop resilience, improve yields and reduce environmental impact. By predicting yield, taste and functional properties of different plant proteins, they accelerate new ingredient and product development, reducing time-to-market while promoting innovation. Precision fermentation for food innovation CSIRO uses precision fermentation to engineer microorganisms that produce animal-free proteins and fats. This enables the development of lactose-free, sustainable dairy alternatives, meeting growing consumer demand, unlocking potential new market segments. Technology Convergence Report 29

Technology Convergence Report 2025