I recently spoke at Web Summit and AWS’ CHRO Summit about a topic that lies at the heart of how businesses are evolving in the age of artificial intelligence (AI): the role of human data in shaping human intelligence. While AI is undoubtedly transformative and revolutionary, its power is fundamentally limited by the quality of the data we give it. According to McKinsey, biases in data—whether from uneven collection practices or human judgment—can embed and even magnify societal inequalities when AI systems analyze, learn from, and act on that data, resulting in far-reaching and unintended consequences.
In other words, if we feed AI flawed, incomplete, or superficial data, we’re not just limiting its potential—we’re amplifying our own biases and mistakes.
AI: A Rocket Ship for Understanding (If It Gets the Right Data)
Humans are extraordinary. We’ve achieved incredible things with even the most basic tools. The moon landing? We made that happen with a computer less powerful than today’s toaster ovens. Steve Jobs once described computers as “bicycles for the mind” because they amplified human abilities. By that logic, AI is a rocket ship for the mind, capable of processing data and revealing insights that we as humans could never see on our own.
But here’s the catch: AI only knows what we teach it. And if we’re building on a flawed foundation, AI will reflect those flaws right back to us. This is why a staggering 80% of AI projects fail, according to a recent Rand Corporation study.
Even AI knows its limitations. For instance, when asked how it could help HR write job descriptions, ChatGPT provided an impressive list of capabilities but included this caveat:
“AI-generated descriptions may require human oversight to ensure that the nuances of the specific job and company culture are well represented. In some cases, AI might miss the emotional or aspirational aspects that can be important in attracting top talent.”
The problem isn’t AI itself—it’s the data we’re giving it. Traditional numbers like turnover rates and engagement scores give a snapshot of what employees are doing and thinking, but don’t explain why. Performance reviews focus on skills and objectives but lack understanding of how work actually gets done. This disconnect leads to flawed decision-making, perpetuating bias and limiting AI’s ability to deliver meaningful insights.
But human data, or the real-time, nuanced interactions and feedback exchanged between people, provides a richer, more authentic understanding of workplace dynamics. This is where recognition data changes the game.
Recognition: The Foundation for Human Data
Recognition data refers to the insights gained from analyzing messages of appreciation and gratitude shared between employees. It is one of the purest forms of human data because when someone says “thank you” or “great job,” it captures not just what employees do, but the value and impact of their efforts.
Take this real recognition note:
“Lisa, I just want to say how much I appreciate the clarity and persuasiveness of your presentations during client visits. Your partnership with the design team is an incredible example of teamwork across departments.”
The right AI setup can associate qualitative performance indicators in written feedback––like quality, clarity, persuasive, partnership, and teamwork––with Lisa, and compare her work to her peers’. It can identify Lisa as a potential mentor or partner for new hires and connect which qualities drive the best business results.
Collectively, these moments of recognition—where employees acknowledge and celebrate each other’s contributions, milestones, and progress—generate a treasure trove of insights into performance, collaboration, and culture. This human data provides a rich understanding of how people interact, lead, and engage within an organization—offering insights into areas that traditional HR tools often struggle to measure.
Putting Human Data to Work
Now imagine aggregating this data across thousands of companies—resulting in billions of data points about how work actually happens. To put this into perspective, a million seconds is about 12 days, while a billion seconds span 32 years—nearly the length of an entire career. The result is a focused and comprehensive collection of human interactions that can be analyzed by AI tools to reveal best practices, unearth hidden gems or quiet influencers, and even quantify the return on HR investments.
Let’s say you ask AI to identify the most influential person in a recent product launch. Traditional data might point to a project manager or designer, but AI trained on recognition data might surface an unexpected result: the office manager, Emily. Emily wasn’t in the meetings or on the project plan, but her behind-the-scenes support—coordinating schedules, tracking down approvals, and organizing the team—was what kept the project on track.
Recognition moments capture these hidden contributions. They act like the memory orbs from Pixar’s Inside Out—not just storing emotions but revealing critical insights about who contributes, how they perform, and what behaviors drive success.
I’ll give you another example: In a recent experiment, I asked AI to identify the biggest flight risk at Workhuman. The result? Me. As a CEO, I don’t receive much recognition, so the data flagged me as disengaged. While I’m not going anywhere, this example underscores how AI can surface unexpected insights, prompting proactive solutions.
A Giant Leap Forward
With AI, HR leaders now have the ability to measure, manage, and optimize the intricate, subjective, and uniquely human interactions that drive company success. This is more than just data—it’s a new strategic lens that positions HR as a central, influential force in shaping business outcomes and ensuring sustainable growth.
The organizations that lead us into the future will be the ones that use human intelligence to augment their human data, turning everyday interactions into actionable insights that drive culture, innovation, and performance. This is how we move from intuition to insight, from guesswork to strategy. Recognition data is the rocket fuel that powers this journey, enabling HR leaders to become true strategic partners in the C-suite.
I’m a firm believer that greatness doesn’t come from machines—it comes from people. In other words, you need human intelligence to unlock the full potential of an organization. The future of work depends on how we use AI to amplify human intelligence. So, let’s start with the data that truly matters—human data.