New science-backed model will measure the effectiveness of human-AI collaboration.
As organizations accelerate AI investment and adoption, required human behaviors in the workplace are changing – and so is the nature of job performance itself. Overlaying rapidly evolving technology onto old ways of working creates a costly blind spot that rewards activity over quality and allows AI misuse and over-reliance to thrive.
The highest performing organizations of the future will be defined by their ability to understand, measure and develop the human capabilities that make AI work. Global talent management experts Talogy are introducing a new, science-backed model designed to identify and eliminate those critical blind spots in human-AI teamwork.
With this narrow, short-term focus on immediate efficiency and productivity increases, organizations face serious operational risks. According to Talogy’s Chief Scientist, Ted Kinney, the new model will equip leaders and HR teams with the insights and guidance needed to optimize human-AI collaboration for an agile, future-ready workforce.
“Organizations are focused on measuring AI literacy, self-reported competence, and usage frequency. However, we risk oversimplifying the problem with AI adoption if we ignore the actual quality of the human-AI interaction.
“There is a critical need for organizations to understand how each individual interacts with AI – and the quality of the collaboration. Effectiveness can vary from person-to-person, with some over-relying on AI, others not trusting it enough.
“Without this deeper insight, organizations are putting performance at risk,” Kinney said.
Moving beyond adoption to AI optimization
Talogy’s new Human AI Collaboration Model combines insights from I/O psychology, human factors, cognitive science and educational psychology to map an individual’s natural potential for AI collaboration, how well they work with AI and if it strengthens their skills and outcomes or erodes their capabilities over time.
By identifying specific human strengths and development areas, the model enables employers to optimize human-AI workflows while safeguarding independent critical thinking.
These insights debut within Talogy’s flagship personality assessment, Talogy Caliper™. This integration allows leaders to identify the personal characteristics that shape how a person engages with automated tools, focusing on the foundations of human-AI collaboration:
- Judgment – How people evaluate information, uncertainty, context, and risk.
- Curiosity – How people learn, explore, and adapt as work and tools change.
- Connection – How people communicate, collaborate, challenge, and stay accountable in AI-enabled work.
Kristin Delgado, psychologist and Talogy’s manager of assessment innovation, led the model’s development and commented, “We designed this to help HR and business leaders understand how an individual’s foundational capabilities and skills are shaping the effective use of – and collaboration with – AI.
“Ultimately, we want to see the workforce of the future strengthen their skills and drive better outcomes alongside AI. Overlooking this critical blind spot risks eroding workforce capability – a risk no business can afford to take.”
Chief Scientist Ted Kinney emphasized that comfortable use of AI and knowledge of AI tools are not the differentiators they used to be. “Knowing how to use AI doesn’t predict better collaboration. What separates strong collaborators from weak ones is the judgment, curiosity and connection they bring to the AI workplace.
“Organizations that shift from static measures of AI familiarity towards a deeper, more nuanced understanding of AI’s role are the organizations that will thrive alongside the AI of tomorrow.”
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