Most businesses understand that AI has the potential to alter their operations, but knowing where to apply it is difficult. Companies across industries are investing billions of dollars in AI, aiming to streamline operations, increase efficiency, and gain a competitive advantage. Despite these efforts, many organisations struggle to turn AI adoption into real economic value. The issue is not the technology itself, but how organisations choose to utilise it.
Workhelix, a Palo Alto-based tech-enabled services company, aims to tackle this challenge. Instead of applying AI indiscriminately across entire business units, Workhelix takes a more precise approach by breaking down job roles into individual tasks and assessing each one for its suitability for AI adoption. This methodology, developed through years of research by leading academics, provides businesses with a clear roadmap to AI implementation and a framework to track its impact.
A Data-Driven Approach to AI Adoption
Workhelix was co-founded in 2022 by a team of prominent researchers and technology experts, including Erik Brynjolfsson, Andrew McAfee, Daniel Rock, and James Milin. Brynjolfsson, the director of Stanford’s Digital Economy Lab, has spent years studying the intersection of technology and productivity. He argues that companies often fail in AI adoption because they take an overly broad approach.
