Editorial
Moderna recently made headlines — not for a vaccine or breakthrough drug, but for a bold redesign of its org chart. CEO Stéphane Bancel announced that the company would merge two of the most traditionally siloed departments: IT and HR.
Moderna seems to have figured out something most companies haven’t: AI doesn’t scale without a strong partnership between the people who best understand the technology and the people who best understand people.
AI Isn't Just Another Software Rollout
Too many companies treat AI like just another software rollout: pick a tool, schedule a training, check the box.
But AI isn’t another tech upgrade. It’s a full-scale shift in how people think, collaborate and make decisions.
Over half (56%) of employees say they don’t feel prepared to use AI at work, according to recent research from Jobs for the Future (JFF). Most training is too generic, too top-down and too disconnected from how people actually work.
This is where HR and IT need to lock arms. Together, they need to design training that is:
- Role-specific. Tailor it to the actual roles and tasks people perform — not just hypothetical use cases.
- Team-based. Train teams, not just individuals. When people learn together, they build shared norms, hold each other accountable and push each other to actually implement what they’ve learned.
- Psychologically safe. Design training that acknowledges fear and builds confidence. People are more likely to experiment with AI when they’re not afraid of getting it wrong.
Measure AI Metrics That Matter
Companies are also measuring AI as if it’s just another tech rollout, focused on traditional return on investment (ROI) metrics like cost savings.
According to our latest research from the Asana Work Innovation Lab, 59% of knowledge workers say their organization is tracking the ROI of AI tools in some way. But only a small percentage are measuring more human-centered ROI metrics. Are employees actually using the tools? Do they enjoy using them? Is the work itself improving? Just 23% of knowledge workers say their organizations measure employee satisfaction and only 11% say their organizations measure user adoption rates.
HR is best suited to own the human side of AI adoption: how people feel about it, talk about it and use it — or ignore it, resent it and pretend to use it. They have visibility into sentiment, engagement, trust and behavior — the signals that show whether AI is becoming part of the culture or just another item in your tech stack.
This is critical. Companies that measure human-centered ROI metrics are 37% more likely to report productivity gains. Make work better for people, and the business wins too.
Redefine the Role of a Teammate
AI adoption is deeply human, and deeply psychological. Our research shows that employees who see AI as a teammate — not just a tool — are 33% more likely to report productivity gains.
Why? Because they don’t just hand off tasks to AI and move on. They iterate. They ask follow-up questions. They treat AI like a partner, not just a transactional tool.
But that kind of relationship with AI doesn’t happen automatically. It requires a shift in how people think about work and in how organizations define roles, responsibility and collaboration.
Because once AI becomes a teammate, not just a tool, the old rules of teamwork start to change. And new questions need to be answered:
- If AI contributed to the outcome, who owns the result?
- If a decision goes sideways, who’s accountable — the person, the AI or both?
- How do you evaluate performance when the final product is created by both humans and machines?
Answering those questions requires a new, deeply human playbook for how teams share responsibility and credit, give feedback, and stay engaged when algorithms are part of the team.
AI Won’t Scale Without a Human Backbone
The history of technology shows us that technology rarely fails because it can’t do the job. It fails because humans resist using it. Ignore the human side, and even the most advanced AI system will gather digital dust, while employees quietly slip back into old habits.
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Editor's Note: For more perspectives on AI adoption, read:
- What it Takes for GenAI to Scale — Alan Pelz-Sharpe, Rebecca Hinds and Craig Durr join Three Dots to discuss why individual productivity gains with GenAI haven't scaled across the organization.
- How Generative AI Tools Are Shaping Employee Capacity — Generative AI tools can boost or drain employee energy — it's up to leaders to create the conditions for one or the other.
- Round Pegs and Square Holes: Why AI Adoption Requires a Focus on Culture — AI’s impact isn't inherent in the technology itself but in how it is deployed. Will it be a means to cut corners, or a catalyst for growth and innovation?
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