UNLEASH World, Paris—At a media briefing during UNLEASH World, Workhuman President Tom Libretto and Chief Human Experience Officer KeyAnna Schmiedl detailed the company’s vision for the future of work, positioning employee recognition as the critical data source for driving business outcomes and powering the next generation of predictive HR technology.
The focus of the conversation centered on the launch of Human Intelligence, a new capability that applies sophisticated AI and natural language processing (NLP) to the vast amount of data generated by employee recognition moments. This innovation is transforming the simple “thank you” into an actionable, predictive tool for talent management.
Recognition as the Core Business Driver
Tom Libretto emphasized that Workhuman’s mission—making work more human by valuing employee effort—has always been tied to hard business metrics. The impact of recognition goes far beyond “table stakes” metrics like engagement and eNPS.
“We love getting deep into analyzing and correlating the impact of recognition,” Libretto said, noting bespoke work with clients in various sectors:
- Manufacturing: Analyzing recognition frequency against plant productivity, avoidable safety incidents, and absenteeism.
- Services: Correlating recognition activity with billable hours targets for consultants.
Libretto stressed that after 20 years of continuous innovation, the company is now at a “new frontier” with the introduction of Human Intelligence.
AI: Replacing Work, Not Jobs
KeyAnna Schmiedl spoke about the evolving role of HR, moving away from process enforcement and toward being a “truth partner” focused on business success. She was emphatic about reframing the conversation around Artificial Intelligence.
“AI should be replacing work, not jobs,” Schmiedl stated. “It is our job to think about what are the jobs of the future, and that’s always going to involve a human. AI does work; it doesn’t do a job.”
This sentiment grounds the use of AI in clear, human-centered use cases, a principle Libretto underscored from a vendor perspective: “It starts with… what are the use cases that are going to be made better or more efficient… if we apply statistical scoring in this part of the application?”
The goal is to leverage technology to “identify the real intrinsic value of humans at work.”
Human Intelligence: The Authentic View of Talent
The application of AI to recognition data addresses a long-standing weakness in traditional HR systems: the performance management process. Libretto argued that annual or semi-annual reviews are “incomplete at best” due to recency bias and individual biases.
Workhuman’s AI parses the rich language used in recognition messages—the observed behaviors, the company values exhibited, the business impact, and the emotional sentiment—to create a “much more authentic and robust view of a person in an organization, their contribution now, but importantly what their contribution may look like into the future.”
This “democratized intelligence” allows users to enter prompts and receive actionable insights, such as:
- “Who would be the best mentor for this new hire?”
- “Who’s demonstrating leadership characteristics that predict a promotional advancement within the next six months?”
This ability to surface deep, reliable skills data, validated by peers and managers, is where Workhuman is finding the greatest excitement among clients.
Addressing Critical HR Challenges
The hosts also fielded questions on how this technology addresses specific pain points for HR practitioners:
The Need for Data Density
The power of Human Intelligence depends on the volume of recognition. Schmiedl noted that even smaller organizations can generate rich data if participation is active. The data is relative to the size of the organization, but the common factor is a high frequency and velocity of recognition.
Performance Management
Schmiedl detailed how Workhuman’s internal performance review process (Reflections) is transformed by integrating recognition data. Employees no longer spend time writing detailed logs; they simply pull in their crowdsourced moments of recognition and developmental feedback. “What I want to focus on is, what is the most effective conversation that we need to have?” she explained, noting that the AI will soon summarize key themes to cut down on writing time for managers.
The Dopamine System & Private Feedback
Responding to a question about the emotional drivers and the need for off-the-record conversations, Schmiedl confirmed that the system is built to manage the spectrum of feedback:
- Public Awards: Everyone sees the award and content.
- Title-Public: People see the award title and can congratulate the recipient, but the content remains private.
- Private Awards: Allows managers to acknowledge difficult or sensitive “hard things that are the least favorite part of our jobs” without public fanfare, mitigating the “gosh” factor of public praise for non-glamorous work.
Proactive Nudging (The Dark Spots)
Workhuman’s platform uses nudge technology to look for “dark spots” around an organization—areas or individuals with a lack of recognition. The system can prompt or nudge a manager: “So-and-so hasn’t been recognized in six months. That may be for good reason, but it’s just something you should know about.”
Strategic Positioning
When asked how Workhuman sees itself in the crowded HR tech market—especially as its capabilities bleed into skills and talent management—Libretto was clear: “Fundamentally, we’re an employee recognition service provider. And that’s the utility that we’re allowing organizations to leverage.”
While acknowledging the overlap with skills management and talent analytics, he welcomed the synergy. “We can just provide better, more authentic and validated skills data than you’re going to get by asking your employees to self describe.”
The takeaway for HR leaders is that the company is aiming to be the system of truth for employee contributions and future potential, powered by the continuous, authentic feedback loop of recognition.