HR leaders should draw on lessons they learned from leading through the pandemic to learn how to best leverage AI technology for business success.
By Melissa Knotts
More than five years after the pandemic rapidly accelerated digital transformation, organizations are still experiencing the same pattern of fast, reactive change in today’s workplace. These days the catalyst is the AI boom. However, this change now demands a more intentional approach of redesigning systems and improving data to avoid repeating past mistakes.
AI is reshaping everyday workplaces, and HR leaders should draw on the following lessons of the pandemic era to ensure AI drives productivity and successful digital change.
The Importance of Cross-Team Collaboration
One of the biggest lessons from the pandemic workplace was the redesign of structures and processes—not just within teams, but across them. For HR, the pandemic underscored that teams can only operate at their highest capacity when relying on and partnering with others throughout the organization. This lesson is clear today, as teams find siloed AI efforts counterproductive. AI permeates every layer of the business, and effective transformation depends on leaders having a detailed, cross-functional understanding of each team’s workflows. These moments force leaders to step back, reassess how teams operate, and often rethink processes. Collaboration becomes essential, making company-wide partnership a determining factor.
Rather than moving hastily, the AI era requires first a “slow down to speed up” approach. AI becomes significantly more effective as teams assess their operational needs through partnership. For example, HR now often works more closely with IT to ensure the data underlying AI-driven systems is clean and structured. As with the move to cloud, cross-team collaboration is a prerequisite for success. Without it, AI initiatives cannot reach their full potential.
Balancing Speed with Responsible Decision-Making
AI adoption carries significant cultural implications. Organizations must shift from being merely “change ready” to becoming “change seeking,” actively experimenting with AI as necessary rather than simply reacting to it. HR leaders face the challenge of balancing speed with risk, understanding that the cost of standing still may outweigh the risks of moving fast. This paradoxical problem requires pairing a company-wide vision with bottom-up execution: leadership setting the strategic direction, while teams experiment and operationalize AI responsibly.
One of the clearest risks is premature workforce reduction. Many companies assume AI will fill productivity gaps or in some cases, entire roles. A similar story occurred within the pandemic-era workplace. As companies faced uncertainty and rapid change, HR leaders were often forced to make large-scale workforce decisions quickly, sometimes without the full picture. A recent MIT study underscores this gap, finding that 95% of companies investing in AI have reported no measurable ROI. Restructuring before productivity gains are proven can force companies into expensive reversals later.
Building Foundations for Responsible Adoption
As organizations adopt AI at a rapid pace, one of HR’s most critical responsibilities is both preparing people and the systems to use these tools effectively. Training employees properly is only half the challenge—equally important is ensuring the data behind the tools are accurate and trustworthy. Without these two foundations working in tandem, initiatives struggle to scale and produce reliable outcomes.
Organizations are experimenting with creative ways to engage staff and promote learning, including the following.
- AI learning weeks, in which leaders roll out AI-assisted development plans that allow employees to experiment with the tools in personal roles.
- AI hackathons, which give staff the opportunity to generate ideas for integrating AI into company workflows.
Beyond training and productivity support, HR must guide leaders through a fundamental shift in management. This includes moving from managing headcount to scaling with digital labor, such as pairing one new hire with two new AI agents. Skills are becoming the new currency with AI fluency emerging as a premium skill. Growth is no longer linear; with AI, employee performance will be tracked in far more dynamic ways.
At the same time, AI accuracy is determined by the data it uses—a principle often characterized as “garbage in, garbage out.” This is true for many HR AI tools, such as recruiting systems. If the data is inaccurate, the insights provided will be equally flawed. This lesson was reinforced in the pandemic era, when many organizations rushed to adopt cloud systems and remote workflows without first ensuring their data was accurate and well-structured.
The same principle applies to today’s AI boom. Skipping foundational steps like auditing datasets, resolving inconsistencies, and ensuring integration across all platforms can hinder long-term transformation. Organizations that invest in both training and strengthening data quality early will yield a measurable impact.
AI Digital Transformation in 2026 and Beyond
The pandemic wave of digital transformation reshaped how people work—and five years later, its impact is still evident. Similarly, AI is set to shift the workplace in profound ways, from daily workflows to company structures. Looking ahead, learning habits within the workplace will become far more dynamic and real-time, driven by AI-augmented learning cultures.
By applying the tools learned from previous digitally transformative waves, organizations that move thoughtfully will be best positioned to thrive in the AI era.
Melissa Knotts is chief people officer at Vasion.
