The medtech industry is on the cusp of a transformative era. The convergence of key enabling technologies–AI, Robotics and advanced materials science–is reshaping the art of the possible across work, workforce and workplace. Take for example software development. Much of medtech product innovation and development workflows are built-on software. It is no surprise that cracking the code of software development remains a top priority. Generative AI tools like GitHub Copilot X can automate coding tasks, generate test cases and document code, allowing software development to be completed up to 55% faster. Think about how progress like this will speed up software development for medical devices and healthcare applications.

AI can also aid in discovering new product designs, identifying potential flaws faster in manufacturing and analyzing patient data to predict the likelihood of diseases for early detection and intervention. For example, Edwards Lifesciences is using AI capabilities with their new Acumen heart catheters to predict potential complications during heart surgery. This AI system analyzes real-time data and alerts surgeons to potential issues, enabling them to take proactive measures and potentially save lives. 

Further, companies are using the power of AI to equip their people. Talent continues to be a top priority for medtech companies–an AI-enabled workforce could be a true differentiator. Companies are already racing ahead with implementation to gain a competitive advantage. For example, Moderna unlocked “thousands of hours of productivity” through its AI platform, mChat, launched in partnership with OpenAI. AI-powered chatbots and voice assistants can handle administrative customer requests, troubleshoot issues and determine appropriate support documentation in real-time. This allows top talent to focus on the highest ROI for time invested. 

In addition to AI’s impact on work and workforce, AI-powered real estate decisions could allow medtech companies to unlock yet another frontier. Predictive models could analyze vast amounts of data related to supply chain, labor markets, transportation costs and other relevant factors to help companies identify optimal locations for their manufacturing facilities. AI algorithms could also simulate various scenarios based on different location choices, helping decision-makers understand the potential risks and benefits associated with each option.