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Work Futures Lab Founder Explains Why AI’s Biggest Impact Will Be Redesign, Not Replacement

Babson professor Sebastian Fixson says AI's biggest impact won't come from replacing jobs, but from redesigning workflows, value streams, and the way organizations create value.

Emma AscottbyEmma Ascott
July 22, 2026
in Tech
Reading Time: 4 mins read
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Work Futures Lab Founder Explains Why AI's Biggest Impact Will Be Redesign, Not Replacement

Companies seeing the strongest AI results are changing processes alongside technology, while those simply adding AI tools often see far smaller productivity gains.

This article is based on the Allwork.Space Future of Work Podcast episode “Why AI Is Changing Jobs Before It Changes Employment with Sebastian Fixson” Click here to watch or listen to the full episode.

Artificial intelligence has sparked endless predictions about job losses, automation, and the future of employment. But one question often receives far less attention: What is AI doing to the structure of work itself?

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The biggest impact of AI may come from changing the tasks inside jobs, forcing organizations to rethink workflows, decision-making, and how employees create value.

That was the focus of a recent episode of The Future of Work® Podcast, where we spoke with Sebastian Fixson, Professor of Innovation & Design at Babson College and founder of the Work Futures Lab. Fixson studies how organizations build innovation capabilities through design thinking, digital tools, artificial intelligence, and organizational design.

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His central argument: AI’s value will depend less on the technology itself and more on whether companies are willing to redesign the systems around it.

AI’s Biggest Impact May Happen Inside Jobs

Much of the AI debate focuses on whether certain jobs will disappear. Fixson argues that this framing misses a more immediate transformation happening inside organizations.

The impact of AI depends on where you look. Policymakers may focus on entire industries and employment numbers. Executives may look at company performance and competitive advantage. Employees experience AI through the daily tasks that make up their jobs. Those perspectives can produce very different conclusions.

Research experiments have already shown that AI can significantly improve performance on specific tasks. Studies examining AI-assisted work have found productivity gains of around 30% on certain creative tasks, such as producing marketing content.

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But real workplaces are more complicated. A job involves dozens of interconnected responsibilities, organizational processes, and human relationships. Simply adding an AI tool does not automatically produce the same results seen in controlled experiments.

The challenge now is understanding how AI changes the way work is organized.

Companies Need to Redesign Workflows, Not Just Add Tools

Fixson believes many organizations are approaching AI too narrowly by treating it as a software implementation rather than an organizational change. Jobs exist within larger systems. When AI changes how tasks are completed, companies may need to rethink entire workflows and value streams.

That requires leaders to ask fundamental questions: What value does the organization create? Which activities support that goal? Where can AI improve performance? Where is human judgment still essential?

This type of redesign is difficult because companies often have years of accumulated processes, technology systems, and cultural habits that shape how work gets done.

The technology may be advanced, but organizations still have to adapt the environment around it.

Experience May Become More Valuable in an AI Workplace

AI adoption also creates an interesting challenge for employees at different career stages. Experienced professionals often have an advantage because they have developed the judgment needed to evaluate whether an AI-generated result is accurate, useful, or missing important context.

That expertise comes from years of exposure to problems, customers, industries, and organizational dynamics. For younger workers, the challenge is different. They may be expected to use AI tools while still developing the professional judgment needed to assess their output.

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As AI becomes more common, organizations may need to rethink how they develop expertise and create opportunities for employees to build that judgment.

The Future of Work Will Depend on Human-AI Collaboration

Fixson sees AI as a tool that can change how people work rather than simply reduce the need for people.

The key question is what parts of work become more valuable when routine tasks are automated. In some cases, AI may remove repetitive responsibilities and allow employees to focus on higher-value activities. In others, it may reduce the parts of work that people find meaningful.

The difference depends on how organizations implement the technology. A translator, for example, may experience AI differently depending on how the tool is introduced. If AI handles basic translation and leaves humans with editing and quality checks, the work may feel less rewarding. In another field, AI may remove tedious tasks and allow professionals to spend more time on creative problem-solving.

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Productivity alone does not determine whether the quality of work improves.

AI Gives Companies a Chance to Rethink Work

Fixson compares the current AI transition to previous technological changes, such as the introduction of shipping containers, which transformed global logistics by changing entire systems rather than improving a single task. The same could happen with AI.

The organizations that benefit most may be those willing to imagine new ways of operating rather than simply adding AI onto existing structures. That requires involving employees in the process. Workers often understand the details of their jobs better than anyone else, and their input can help companies identify where AI can create meaningful improvements.

The future of work will be molded by the choices organizations make about how work is designed, how employees participate, and how humans and AI systems work together.

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For leaders navigating AI adoption, the biggest challenge may be rethinking what their organizations are designed to do in the first place.

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Tags: AIFUTURE OF WORK® PodcastLeadershipTechnologyWorkforce
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Emma Ascott

Emma Ascott

Emma Ascott is the Associate Editor for Allwork.Space, based in Phoenix, Arizona. She covers the future of work, labor news, and flexible workplace trends. She graduated from the Walter Cronkite School of Journalism and Mass Communication at Arizona State University, and has written for Arizona PBS as well as a multitude of publications.

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