Dr. Gleb Tsipursky – The Office Whisperer
Nirit Cohen – WorkFutures
Angela Howard – Culture Expert
Drew Jones – Design & Innovation
Jonathan Price – CRE & Flex Expert
Every technology revolution — from the digital to mobile and cloud — followed a similar pattern: choose a platform, test it, create guidelines, and train users.
That formula worked when we digitized what was already there. But AI doesn’t do that. It’s a fundamental redesign of how organizations operate, including roles, workflows, and leadership mindsets. And that is nothing like any technology upgrade we’ve ever done.
Why Traditional Approaches Fall Short
Once AI enters the workplace, the lines of responsibility blur. Who owns the output — the person, the algorithm, or a hybrid of both? Who corrects errors when AI learns incorrectly? Who determines whether to trust or question an AI-generated insight? These are operational questions, best answered by those closest to the work and its value chain.
That’s why the real challenge is human change management and not the technical execution.
In a conversation on The Future of Less Work podcast, Mary Alice Vuicic, Chief People Officer at Thomson Reuters, highlighted that successful AI integration hinges on people, not platforms. At her organization, both the CIO and CHRO co-lead the AI initiative, reflecting a dual commitment to both technology and transformation.
“This is about two equal parts technology and change management,” she emphasized.
Work Reimagined: A Recruiting Case Study
Historically, people were end-users of technology. Now, they are collaborators in adaptive systems. Talent acquisition offers a glimpse into this new reality. Recruiters once spent their days coordinating interviews, scanning resumes, and managing administrative tasks. It was necessary but repetitive, leaving little room for strategic thinking.
With AI automating much of this, recruiters are shifting their focus to high-value human contributions: assessing potential, aligning skills with evolving needs, and shaping future talent strategies.
Their roles are evolving from transactional task managers to strategic talent architects. They are shifting their attention from simply filling roles to engineer the talent ecosystem. And that changes their expertise and their role in providing human insight in the process.
Vuicic described how, in one acquisition, an employee’s curiosity about AI led to a removal of what she called “no-joy” work.” They eliminated 95% of that administrative work,” she recalled, “and we got a higher quality output… in a fraction of the time.”
That freed the team to focus on strategic elements like talent retention and cultural integration.
The AI-Driven Work Redesign Cycle
Transforming work with AI isn’t something IT can handle in isolation. It requires leadership from those embedded in the work itself. A structured approach like the AI Work Redesign Loop can help guide this change.
First, define success by impact, not output. Consider what meaningful outcomes look like. For example, a sales team might aim for deeper client relationships over more calls. A hospital might value improved patient recovery over faster discharges. These goals should determine where AI delivers real value.
Next, analyze the components of work. Break tasks into those that can be automated, those that benefit from AI support, and those that require human intuition. This lens reveals how AI changes the nature of contribution, not just process.
Then, map out human-AI interaction. What needs a human eye? Where is human context essential? What data, systems, or guardrails are required?
This is where new capabilities emerge: critical thinking, ethical reasoning, and the ability to shape how AI fits into daily decision-making.
Finally, redefine performance metrics. Traditional KPIs reward speed and cost-efficiency. AI-ready organizations need to measure trust, quality, adaptability, and continuous learning.
The best metric may not be how much is automated but how much collaboration and insight AI enables.
What emerges is a new blueprint for value creation. A dynamic framework that clarifies how AI and people work together, what new skills are needed, and how work evolves over time.
Why Work Needs a Redesign
In the past, new tools were handed to employees. Today, they’re being given new collaborators. Without a thoughtful integration strategy, the potential of AI is lost.
AI compresses time and expands capacity, unlocking space for creativity, curiosity, and connection. But when organizations fail to align workflows and decision-making structures with AI’s capabilities, the result is inefficiency and frustration.
The answer lies in a new operating model — one that integrates people, processes, and smart systems into a seamless workflow. The most successful organizations won’t be the ones that automate the most. They’ll be the ones that reimagine how human talent and technology co-create value.
