AI Transformation: A Human-Centered Approach to Unlocking Organizational Value

In today’s rapidly evolving digital landscape, organizations are racing to adopt artificial intelligence. However, many are also falling into the trap of focusing solely on efficiency and automation. The real value of AI lies in its ability to enhance human capabilities and foster creativity and innovation, rather than simply increase activity.

In this article, I’ll showcase an example of this value by outlining a strategic, human-centered approach to AI implementation, drawing insights from a successful internal HR transformation by Microsoft. I’ll also add my key takeaways for senior leaders and executives along the way.

The Perils of ‘Top-Down Mandates’

Recent research from Upwork highlights a concerning disconnect: While 96% of C-suite leaders believe AI will enhance productivity, 77% of employees say that AI has actually increased their workloads. I think of this as “fake productivity,” where AI makes employees busier and causes them to feel more overworked, yet fails to deliver real gains or innovation.

Kelly Monahan, managing director of the Upwork Research Institute, pointed to the root of the problem. “The real challenge isn’t AI technology—it’s outdated organizational frameworks,” she said. “To bridge the glaring disconnect between executive expectations and employee experiences, we need a fundamental paradigm shift in how organizations approach AI, and how they organize talent and work. Leaders must move away from top-down mandates and cultivate a more collaborative, supportive environment that empowers employees to fully harness AI’s potential. Aligning technological adoption with organizational systems and workforce development is not just important—it’s critical.”

The Pressing Question

This disconnect between executive expectations and employee experiences raises critical questions about the role of generative AI (GenAI) in the workplace. If simply introducing AI tools is not enough to drive real productivity gains and innovation, what approach should organizations take? How can companies move beyond “fake productivity” to unlock the true potential of AI while improving the employee experience?

The answers may lie in a fundamental shift in how we approach AI integration—one that puts human needs and experiences at the center of the transformation process.

Human-Centered Transformation: A Path to Value

Microsoft describes its Copilot as an “AI assistant integrated into Microsoft 365 apps to boost productivity by automating tasks and providing intelligent suggestions.” Copilot is an important technology, but equally significant is what we can learn from Microsoft’s “customer zero” implementation. In this instance, being customer zero means that Microsoft spared no effort in understanding, then implementing, the processes to have a successful AI adoption. What it learned is so relevant that whether your organization uses Copilot or not, this case matters to you.

In Microsoft’s initiative, HR played two major roles: as a strategic partner in the internal rollout of Copilot across the company, and as the subject of its own transformation through a human-centered AI implementation. From my perspective, this approach offers valuable insights for organizations seeking to harness the full potential of AI.

Over the last 18 months, Christopher Fernandez, Microsoft’s corporate vice president of HR, has led an AI transformation within his department, emphasizing a human-centered approach. In my podcast interview with Fernandez for SHRM’s The AI+HI Project, he explained how he views AI as a tool to augment human capabilities, rather than replace them.

“The future of AI will wholly be hinged upon how human beings see and interact with the technology,” Fernandez emphasized in our enlightening discussion. And this philosophy very much guided the transformation at Microsoft, focusing on enabling employees to use AI in ways that served both their personal aspiration to enjoy their experience of work and the organization’s broader objectives.

The goal of this approach was to remove drudgery from everyday tasks, create capacity for higher-value activities, and democratize access to information across the HR function. As Fernandez said, “The ability for people to use technology in service to their goals and their aspirations—as well as the organization that they’re a part of—needs to be central to how we think about practical application of technology.”

Keeping this philosophy at the center, Fernandez and his team designed a strategic implementation process to ensure AI enhances the employee experience, fostering a sense of agency rather than alienation.

Designing a Strategic Implementation Process with Humans at the Heart

Microsoft’s HR AI transformation, under Fernandez’s leadership, followed a strategic three-step process prioritizing human needs and organizational alignment. This approach created a virtuous feedback loop in which the three steps transformed into a continuous learning and adjustment cycle with humans at the center. 

Step 1: Experimentation and Empowerment

Many companies begin building AI fluency by exposing employees to GenAI through prompting. Microsoft, however, took a simpler approach to advance fluency further. It prioritized getting people comfortable with technology—“not AI as we define it today, just automation,” Fernandez clarified—by introducing low-code/no-code tools that empowered HR professionals to automate manual tasks without deep technical expertise. “Step one was to get people comfortable with how technology can work in service to them,” he explained.

By enabling employees to leverage their domain expertise and automate their work, Microsoft fostered their sense of agency and ownership over the technology. This initial step built trust and confidence among employees, laying the foundation for successful AI integration across the organization. When employees saw their peers automate workflows and free themselves up for higher-order work, they believed the narrative in a way that couldn’t be pushed from the top down.

Microsoft called these early experimenters “citizen developers” who showed their peers how to benefit from AI and demonstrated that the company deeply valued their domain expertise. “The citizen developers [were] central to all of this,” Fernandez said. “They know their domain the best [how to apply workflows] and created a sense of community, credibility, and collegiality that only they authentically could.”  

As they moved beyond creating no-code or low-code applications, the citizen developers quickly realized that the available technology revolved around asking the right questions.

>> My Key Takeaway for Senior Leaders and Executives: You don’t need the resources of Microsoft to understand the importance of designing AI implementations to focus on building trust. Employees need to see their peers accessing the freedom promised by GenAI tools in a way that shows them the true value that their domain expertise has to you, the organization. Further, empowering someone to be a citizen developer and participate in your innovation process communicates that you respect their knowledge base, which goes a long way to reduce fear of change. Trust, empowerment, and respect are not “feel-good” steps; they are the only way to secure buy-in for reinvention that will meet your business objectives.

Step 2: Business Architecture Alignment

One of the contributors to “fake productivity” is the running of AI experiments that aren’t tied to business needs. To avoid this, leaders must balance creating an environment for employee experimentation with directing efforts toward organizational objectives. Microsoft addressed this by providing a “business architecture” road map identifying “areas of greatest impact” without over-directing use cases. Coupled with a responsible AI framework, this freedom plus gentle guidelines drove very intentional experimentation and decision-making.

Fernandez explained that when this architecture is communicated organizationwide, citizen developers can “affiliate with that business architecture and coalesce around main deliverables,” imagining new workflows to advance reinvention. This approach roots people in a “larger architectural consideration,” helping employees understand the outcomes the organization aims to achieve across functions.

At Microsoft, employees began to see how their individual applications fit into the wider company architecture, advancing it and improving experiences for themselves and colleagues. This sense of agency and impact fostered collaboration across HR functions and increased excitement among communities of practice to innovate even more.

As momentum grew, something special happened: Employees began to leverage their incumbent knowledge, experiments, and cross-functional communities to help refine the business architecture itself through an innovation intake process.

“The business architecture became more refined—not in a vacuum or top-down, but through truly collaborative work with communities across the HR function,” Fernandez said. He added that as the architecture evolved, employees realized, “‘Wow. The work we’re doing is directly impacting our ability to enable better employee experiences broadly in the company.’”

So, for employees, step one established the value of technology that they have agency over, and step two demonstrated the value of connecting their work to larger organizational goals.

>> My Key Takeaway for Senior Leaders and Executives: The innovation you seek for your business objectives is embedded in your people’s sense of agency. Design a system that allows your employees to see their impact on organizational goals and their own work experiences, in a way that supports your wider narrative. Communicate the wider areas of focus to guide experimentation—but don’t micromanage!—and allow what comes back to help evolve your business goals.

Step 3: Purposeful AI Implementation with ‘Hero Cases’

The pressure around AI has led many organizations to rush into wide-scale implementations. However, Microsoft’s example suggests a more measured approach: identifying where and in what business context you want to apply advanced AI tools such as Copilot.

As Fernandez explained, Microsoft leveraged an innovation intake process to gather ideas from the communities of practice. These ideas were evaluated through crowdsourcing and input from individuals with the relevant business architecture insight, resulting in a prioritized list of use cases based on potential impact. Microsoft then tested, documented, and revised these use cases based on their direct impact on the evolving business architecture and a “complete thought” about what each would achieve.

“Hero cases” emerged as well-defined, impactful scenarios that demonstrate the full potential of AI when aligned with both business objectives and employee needs. These cases served as exemplary models of how AI could significantly enhance HR operations and employee experiences. It’s clear from researching AI adoption successes and failures that securing outcomes enabled the scaled impact required. Fernandez explained this as “thinking through, from start to finish, what the use case is trying to accomplish, the means and methods by which you’re going to accomplish it, and what the resulting outcomes will be.”

Finally, based on these “hero cases” and the refined business architecture, Microsoft implemented Copilot and other AI tools. This final step ensured AI integration was purposeful and value-driven—and directly improved HR operations and employee experiences. From my perspective, this process facilitates the transition from experimentation to large-scale implementation, allowing enterprises to see the broader impact they aim to achieve. The process also allows employees to truly realize that it’s their depth of professional understanding that enables them to ask the right questions and unlock the value of tools such as Copilot—reaffirming their own value. Just as training tightens algorithmic fit, this process tightens organizational fit with AI while unlocking greater human potential.

As Fernandez said, “That in turn led to a virtuous feedback loop where we could constantly see evolution of the business architecture, coupled with input into how we thought about utilization of intelligent automation. [We observed] business architecture influencing the deployment, [and] the deployment influencing the architecture, all with the underpinning of human beings being at the center.”

>> My Key Takeaway for Senior Leaders and Executives: Take the time to identify the “hero cases” most likely to achieve your widest business goals, but be sure to develop those with your internal expertise. And as Fernandez told me, “This can’t be done to people, you have to do it with people.”  Indeed!

Ensuring Transformation through Holistic Measures of Success

Real measurement is the best way to avoid “fake productivity.” Microsoft measured the success of its AI transformation through quantitative and qualitative metrics. Quantitatively, the company tracked efficiency gains, cycle times, and net satisfaction scores, all of which showed significant improvement post-implementation. Qualitatively, it monitored employee feedback, using AI itself to analyze thousands of verbatims to capture the true sentiment of the workforce. This comprehensive approach provided clear evidence that both business outcomes and employee well-being were genuine.

“Yes, you’re creating efficiencies,” Fernandez stressed, “but you also want to make sure that those efficiencies are in service to a greater effort: in your work and in your collaboration to achieve outcomes that are human-centered and human-oriented.” And the biggest challenge? Shifting people’s perception of AI from a tool to an entirely new way of working.

The iterative process at Microsoft has not only yielded practical outcomes but also strengthened Fernandez’s vision for the future of HR in the AI era. As AI becomes more integrated into the workplace, HR’s role is evolving from administrative to strategic. Fernandez envisions HR professionals as “architects of employee experience” in the AI era, focusing on unlocking human potential and applying behavioral science to technology adoption. This positions HR as a central player in the successful integration of AI.

>> My Key Takeaway for Senior Leaders and Executives: Microsoft’s approach showcases HR’s strategic evolution in the AI era. HR becomes crucial in facilitating tech engagement using behavioral science, assessing human experiences to encourage adoption, and creating supportive ecosystems. By positioning HR as a key innovator in designing human-centered implementations and employee experiences, you have a meaningful role to play in your organization’s reinvention.

AI’s Transformation of Work and Society

To truly harness the transformative power of AI, organizations must go beyond efficiency-focused implementations and adopt a human-centered approach. Human-centered AI implementation drives genuine productivity and innovation, aligning technology with both employee needs and organizational goals. By prioritizing employee experience, fostering a culture of collaboration, and matching AI initiatives with organizational goals, companies can unlock the full potential of AI and avoid the pitfalls of “fake productivity.” As Microsoft’s journey demonstrates, organizations that place human value at the core of their AI strategies will not only drive genuine innovation but also create sustainable growth and a more fulfilling workplace.

Crucially, only successful transformations will deliver the ROI and business growth needed to create new jobs and the new economic models, value, and opportunities our society needs AI to generate. While reinventing work and society is a challenge bigger than any single organization, I believe it will be built through the aggregate success of all those who transform themselves. Leaders who successfully implement human-centered AI strategies will not only drive innovation and sustainable growth in their organizations but will also contribute to reshaping the future of work for the better.