From traditional manufacturing companies using AI in robots to build smart factories to tech startups developing automated customer service and chatbots, AI is becoming pervasive across industries.

“AI is no longer just in assistant mode, but is now playing autonomous roles in robotics, driving, knowledge generation, simulating our hands, feet, and brains,” says Lan Guan, global lead for data and AI at Accenture.

This episode is part of our “Building the future” podcast series. It’s a multi-episode series focusing on how organizations, researchers, and innovators are meeting our evolving global challenges. We understand the importance of inclusive conversations and have chosen to highlight the work of women on the cutting edge of technological innovation, and business excellence.

Researchers are similarly unlocking the value of AI through machine learning and robots that are developed to augment rather than replace human capabilities across manufacturing, health care, and space exploration. The robots of the past were kept in cages on factory floors and in labs, but this new era of AI-enabled robotics allows humans to work interdependently with robots to boost productivity, increase quality of work, and enable greater flexibility, says Julie Shah, professor in the department of aeronautics at MIT. Shah is also the co-lead of the Work of the Future Initiative at MIT.

“Sometimes it can feel as though the emergence of these technologies is just going to sort of steamroll and work and jobs are going to change in some predetermined way because the technology now exists,” says Shah. “But we know from the research that the data doesn't bear that out actually.”

Although there are longstanding concerns about AI taking jobs and vastly changing workforces across the globe, Guan and Shah paint a picture of a future where AI empowers and supports human innovation. Taking a human-centered approach enables human invention and ingenuity to be augmented by AI and AI-enabled technologies. A critical question Shah asks throughout her research is: “How do we develop these technologies such that we're maximally leveraging our human capability to innovate and improve how we do our work?”

With more and better collected data, researchers and organizations alike have the opportunity to learn from the future when deploying AI and robotics. From ethics to varied use cases, the AI landscape is constantly shifting and decisions that academics and enterprises make now can have long term ramifications. A strategic practice of foresight offers a solution of envisioning multiple futures and forming strategies in the present.

“I'm very optimistic about all these amazing aspects of flexibility, resilience, specialization, and also generating more economic profit, economic growth for the society aspect of AI,” says Guan. “As long as we walk into this with eyes wide open so that we understand some of the existing limitations, I'm sure we can do both of them.”