Why Human-Led Emotional Intelligence is AI’s Next Premium
Key takeaways
- AI will change work and the workforce, but it will strengthen the need for human emotional intelligence.
- Employers increasingly recognize that strong emotional and social skills are essential for leadership effectiveness, collaboration, and long-term organizational success.
- Trait- and ability-based emotional intelligence assessments can be used as an ongoing resource to understand how people behave and create emotionally intelligent teams, even in AI-enabled environments.
- Without scientifically validated measures and safeguards, like MHS assessments, AI integration risks bias, superficiality, or ethical missteps.
Artificial intelligence (AI) is advancing rapidly. AI can handle rule-based tasks at every level, drafting, analyzing, predicting, and optimizing, while at remarkable rates, take over routine administration and “busy work.” As skills shift with the rapid growth of this technology, the general understanding is that AI will not only replace entire jobs but will change the world of work altogether. In fact, a 2024 McKinsey Global Institute report notes, “By 2030, in a midpoint adoption scenario, up to 30 percent of current hours worked could be automated, accelerated by generative AI.”1 AI could replace as many as 300 million full-time jobs globally by 2030.2 However, this transition does not mean the “end of human work.” Rather, demand for social and emotional skills will grow rapidly, by about 26% in the United States and 22% in Europe across all industries,3 marking a fundamental realignment of which human roles and skills are most valuable.
But here is where things get interesting: As machines automate and take on greater cognitive load, the more valuable distinctly human capabilities become. Emotional intelligence (EI)—a set of emotional and social skills that influence the way we perceive and express ourselves, develop and maintain social relationships, cope with challenges, and use emotional information in an effective and meaningful way—will likely become the next premium.
Here’s why AI needs EI in the age of digital automation
We can’t automate the human condition
Much of the current AI discourse focuses on displacement: which roles will shrink, what will evolve, and who will emerge. That conversation is necessary, of course, but incomplete. Automation changes what we do; however, it does not eliminate the interpersonal skills required for most work. Sure, AI will reshape the more technical aspects of work (e.g., repetitive, predictable tasks), but organizations will still depend on leaders who can motivate teams, navigate conflict, and sustain trust during uncertainty.
Research suggests that employers increasingly prioritize social and emotional capabilities as technological disruption accelerates.1 Even in a society that has industrialized, using new technology to push individuals to be more machine-like in their output, AI has done the reverse: it has inverted this objective by returning mechanistic goals to the domain of machines. This movement within digital automation is where EI becomes a strategic requirement. Amid ongoing changes to workflows and decision-making, leaders still find themselves managing change, resistance, and personalities. Skillfully managed EI strengthens leadership with strong emotional self-awareness and impulse control, enabling a response to volatility without amplifying it; individuals who accurately perceive others’ emotions adjust their communication style accordingly and facilitate forward progress. Clearly, these are not abstract virtues but operational competencies we can’t simply automate away in AI-enabled organizations.
Performance isn’t just output anymore
Commentary from global business outlets similarly argues that EI is becoming more important for careers, leadership, and profits in the age of AI, as technical skills alone no longer differentiate performance.4 As noted in a 2024 survey of 692 global business leaders, “character-based traits such as integrity and [interpersonal skills] will become more important” for employees at all levels as AI and automation advance.5 Employers predict that uniquely human abilities like effective communication, ethical judgment, empathy, and adaptability will be in greater demand, since AI cannot accurately replicate these competencies.5
That said, the idea of long-term value creation is again supported by evidence linking EI to well-being, engagement, and constructive behavior.6 AI systems may identify emotional cues or optimize operational processes, but they cannot repair fractured trust or restore morale after a mismanaged change initiative. EI sits squarely at the center of this tension.
Leaders high in EI exhibit psychological safety and encourage open dialogue. They are better equipped to balance performance pressure with human capacity. Research suggests that EI is associated with key workplace outcomes, including job performance and organizational citizenship behaviors.7 These relationships matter more, not less, to performance outcomes even in technologically intensive environments.
Measuring what will matter: Trait and ability perspectives
If EI is to function as a human capability that differentiates performance, making precise and meaningful measurements will carry greater weight. Two complementary models dominate the literature for how EI is assessed: trait-based EI and ability-based EI.
Trait-based EI assessments measure EI by examining typical patterns of emotional functioning (i.e., how individuals perceive their own competencies and tendencies). MHS assessments like the Emotional Quotient Inventory™ 2.0 (EQ-i 2.0®) and the Emotional Quotient 360™ (EQ 360®) holistically measure an individual’s EI-related traits, characteristics, and competencies (either through self-report or perception of others), such as Self-Regard, Stress Tolerance, and Interpersonal Skills. Ability-based EI assessments, by contrast, evaluate performance on tasks that require emotional reasoning. The Mayer-Salovey-Caruso Emotional Intelligence Test™ Second Edition (MSCEIT® 2) measures individuals’ ability to identify, connect, understand, and manage emotions.
Each perspective offers distinct value. Trait-based assessments of EI measures reveal how people typically behave; ability-based measures assess what they can do. Research indicates that combining these approaches yields a more layered understanding of emotional functioning than using either method alone.8 In practice, this dual lens helps organizations identify levels of confidence and competence to target development accordingly.
In AI-rich environments, such precision matters. Leaders who overestimate their emotional skills may mishandle sensitive transitions. Conversely, individuals with strong emotional reasoning but low self-confidence may fail to deploy their strengths. An understanding of how individuals behave and what they do across a range of scenarios and perspectives will remain important.
Emotional intelligence is no longer a static part of business development
Traditional assessment has long provided valuable insights through reports and debriefs, but it now represents the foundation for something more dynamic. In the AI era, organizations are increasingly seeking development embedded in the flow of work, reinforced by timely feedback and coaching; interest in EI-enabled technology is also growing.
MHS partners, trainers, and coaches use our EI assessments as a foundation for driving meaningful, measurable outcomes with their clients (being learners, supervision groups, and organizations). By grounding development in objective EI data, they tailor coaching and training interventions, and achieve strong rapport, emotional sensitivity, and assurance with clients. Even as these clients move forward with self-awareness, improvements in their interpersonal effectiveness, and strengthened emotionally intelligent leadership behaviors, they now have the resources to notice patterns with greater emotional oversight. But this targeted approach doesn’t just accelerate development. EI-enabled training that can also deliver tangible business impact, including increased psychological safety, stronger trust and communication, healthier organizational cultures, and improved return on investment. Partners, trainers, and coaches demonstrate progress over time, linking EI development to sustained performance, engagement, and resilience, which reinforce EI’s strategic value.
At the same time, an emerging trend at some organizations like Microsoft, IBM, and Google is exploring the broad integration of emotion analytics across enterprise and consumer applications.8 Healthcare providers are also considering EI for advanced diagnostics and treatment technologies, where AI chatbots and virtual therapists evaluate patients’ emotional states through voice, facial expressions, and text communication.8 As technology improves the ability to detect emotions, individuals in the workplace will be valued for their skills to perceive, navigate, and leverage this emotion data to effectively accomplish their work. As the workplace evolves, from AI adoption to data-driven talent strategies, the value of human capabilities is simultaneously increasing and setting a precedent that technology cannot easily replace.
Organizations that understand this shift are placing greater emphasis on emotional judgment, empathy, adaptability, and ethical leadership, while expecting development efforts to be measurable, scalable, and integrated. This development is where MHS partners, coaches, and trainers are already leading: using EI assessments like the EQ-i 2.0, EQ 360, and MSCEIT 2 alongside coaching, training, and digital tools to create a connected, future-ready approach. Rather than treat EI as a standalone effort, this group is using scientifically validated tools and ethical safeguards to embed these efforts within broader leadership and talent ecosystems to support organizational priorities and technological change.
Even as technology advances and trends emerge, the result is an integrated strategy with the individuals and cultures that advance with it.
The human advantage with the EQ-i 2.0, EQ 360, and MSCEIT 2
Although AI will assume more technical responsibilities, EI will likely make individuals more invaluable. Where the EQ-i 2.0, EQ 360, and MSCEIT 2 are optimized to measure EI, and high levels of EI are important for leadership, these tools can be helpful in identifying and selecting future leaders—or coaching middle- to high-level candidates and employees with potential.
Organizations that treat EI as measurable, developable, and integral to strategy will be better positioned to navigate the volatility AI introduces. They will hire with greater clarity, develop with greater precision, and lead with greater steadiness.
AI will continue to evolve, as will the demands placed on leaders. At that intersection, EI will lead as a durable advantage (and premium) in an age defined by intelligent models in need of the human touch.
Want to learn more about the EQ-i 2.0, EQ 360, and MSCEIT 2? Get in touch with a member of our team today!
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References
1 McKinsey Global Institute. (2024). A new future of work: The race to deploy AI and raise skills in Europe and beyond. McKinsey & Company. https://www.mckinsey.com/mgi/our-research/a-new-future-of-work-the-race-to-deploy-ai-and-raise-skills-in-europe-and-beyond
2 Briggs, J., & Kodnani, D. (2023). The potentially large effects of artificial intelligence on economic growth. Goldman Sachs Global Investment Research. https://www.gspublishing.com/content/research/en/reports/2023/03/27/d64e052b-0f6e-45d7-967b-d7be35fabd16.html
3 Bughin, J., Hazan, E., Lund, S., Dahlström, P., Wiesinger, A., & Subramaniam, A. (2018). Skill shift: Automation and the future of the workforce. McKinsey & Company. https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce
4 Morel, D. (2025). Emotional intelligence is more important than ever in the age of AI. Forbes. https://www.forbes.com/sites/davidmorel/2025/01/13/importance-of-emotional-intelligence-in-the-age-of-ai/
5 Cardon, P., Fleischmann, C., Logemann, M., Heidewald, J., Aritz, J., & Swartz, S. (2024). Competencies needed by business professionals in the AI age: Character and communication lead the way. Business and Professional Communication Quarterly, 87(2), 155–180. https://doi.org/10.1177/23294906231208166
6 Xu, H., Li, Y., & Wang, J. (2025). Effects of employee–artificial intelligence collaboration on counterproductive work behavior: A conservation of resources perspective. Frontiers in Psychology, 16, Article 1521673.
7 Miao, C., Humphrey, R. H., & Qian, S. (2017). A meta-analysis of emotional intelligence and job performance: Testing the mediating role of job satisfaction. Journal of Occupational and Organizational Psychology, 90(2), 177–202. https://doi.org/10.1111/joop.12173
8 Global Market Insights. (2025). Emotion AI market size & share 2025 to 2034. https://www.gminsights.com/industry-analysis/emotion-ai-market
9 Terblanche, N. (2024). AI-based coaching: Opportunities and challenges. Journal of Leadership Studies, 18(1), 84–87. https://doi.org/10.1002/jls.21876
