How to Scale GenAI in the Workplace

As generative AI’s evolution continues, the next challenge for leaders is clear: making GenAI scale and deliver measurable value across their organizations.

As companies move from experimentation to enterprisewide adoption, many struggle not with the tools themselves but with the organizational transformation required to integrate them meaningfully into people’s daily work. Tools will keep evolving: It is the human side of the equation that determines whether GenAI initiatives truly succeed.

We studied one of the largest real-world generative AI deployments to date — at multinational pharmaceutical company Novo Nordisk. Its experience shows that success hinges not just on infrastructure but on how people think, adapt, and collaborate with AI. One critical lesson: While GenAI adoption and broader digital transformations have common roots, generative AI is uniquely disruptive, reshaping the nature of work itself in unprecedented ways.

Like many organizations, Novo Nordisk began with a familiar expectation: that GenAI would primarily drive productivity.   Guided by the leadership principle “time is the ultimate currency” and a campaign dubbed “Make Your Time Count,” the company launched its enterprisewide rollout of Microsoft’s Copilot GenAI tool in early 2024, with the goal of saving time and improving efficiency. And in many ways, the company hit that goal.

Each employee saved 2.17 hours per week, on average, once they began using the tool. But something unexpected also happened: Those hours weren’t what employees valued most. Employee satisfaction with Copilot was three times more strongly correlated with perceived improvements in work quality than with time saved. Employees reported quality enhancements in content summarization, content creation, and ideation. Interestingly, many employees reinvested the time they saved into people interactions, strategic planning, and creative work. As one put it, “I can spend more time and energy dedicated to strategizing and planning the rollout of my project.”

This insight challenges a central assumption of many GenAI rollouts: that the main value of the technology lies in raw efficiency. In practice, the promise of generative AI is broader and more human-centered.

Scaling GenAI: It’s Not Plug-and-Play.  Scaling generative AI isn’t just a technical challenge — it’s a change management marathon. The real work lies in supporting employees as they experiment, struggle, and eventually find their stride with these new tools.   As the company’s experience highlights, generative AI requires sustained training and support. GenAI effectiveness is about training people, not just AI models. Leaders should foster an ecosystem where employees feel supported, informed, and inspired to push the technology’s capabilities further.

Tailor GenAI Enablement by Business Function.  Different business functions require different types of support, however. Recognizing how people across roles and mindsets engage with generative AI is key to driving meaningful adoption.  At Novo Nordisk, Copilot’s impact varied significantly across functions, prompting a shift from uniform deployment to targeted enablement. Analysis comparing time savings and quality improvements across corporate, commercial, manufacturing, and research areas revealed sharp disparities.  To facilitate the process, Novo Nordisk pivoted from a uniform rollout to tailored enablement. It launched function-specific onboarding, created use-case playbooks and learning libraries aligned to job roles, and worked with Microsoft to customize Copilot features for different teams. This flexibility ensured that employees in both creative and precision-driven roles could find meaningful applications aligned with their workflows.

Contrary to some myths about digital natives, the data showed that Novo Nordisk’s senior employees tended to use generative AI more effectively than their younger peers.  Proving that Generative AI performance isn’t about tech savviness — it’s about contextual fluency, confidence, and the human ability to integrate new tools into nuanced workflows.

Overcoming Cultural Resistance and AI Shaming.  Not everyone at Novo Nordisk welcomed Copilot. Cultural resistance and so-called AI shaming posed significant hurdles, with some employees viewing GenAI as unethical or akin to cheating.  Novo Nordisk tackled the challenge with a multifaceted strategy, focusing on transparency and trust. The company rolled out ethical use guidelines, clarified expectations around output ownership and disclosure, and launched the “Spend Time to Save Time” campaign to reframe GenAI as a strategic enabler, not a shortcut.

Leaders scaling GenAI can adopt these strategies, as Novo Nordisk did, to mitigate cultural resistance:  Clarifying ethical use.  Normalizing GenAI use through champions.  Fostering safe spaces.  Addressing trust issues proactively.  And reframing AI’s role.

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