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The Impact of AI on Cognitive and Emotional Intelligence in the Workplace


Artificial intelligence (AI) is rapidly advancing and becoming integrated into more aspects of work. While AI can take over some routine cognitive tasks, many jobs still require human intelligence, creativity, judgment and interpersonal skills.


Today we will examine how AI is impacting the cognitive and emotional dimensions of jobs.


Defining IQ and EQ


Cognitive intelligence, or IQ, refers to logical, analytical abilities needed to process information and solve problems. IQ involves skills like memory, critical thinking, quantitative analysis and technical proficiency (Goleman, 1998). Emotional intelligence, or EQ, comprises the personal and social abilities required to manage emotions and relationships effectively. Key EQ capabilities include self-awareness, self-regulation, empathy, social skills and motivation (Goleman, 1995). While IQ focuses more on "hard" cognitive tasks, EQ underpins "soft" interpersonal job demands.


Both IQ and EQ are needed in today's jobs. Research shows high IQ alone does not guarantee career success - EQ plays a crucial complementary role (Goleman, 1998). At the same time, pure "people skills" are insufficient without a requisite level of cognitive acumen. The most effective workers exhibit a balance of technical proficiency and emotional aptitude for their roles (Cote & Miners, 2006). However, AI's rise poses questions about what parts of jobs rely more on human vs. machine intelligence.


AI's Impact on Hard and Soft Skills


Below we will look at research and examples of AI's differential effects on cognitive vs. emotional job dimensions.


Cognitive Tasks Being Automated


Many routine, rule-based cognitive tasks are vulnerable to automation by AI systems. Research finds jobs heavily involving data collection, data processing, routine decision-making and physical dexterity face high automation potential (Frey & Osborne, 2013). For example, AI has taken over basic data entry, algorithmic financial analysis, quality assurance checking and repetitive manual labor. This allows human workers to focus on more complex cognitive work demanding skills like strategic thinking, problem-solving and technical troubleshooting that remain challenging for AI to replicate (Manyika et al., 2017).


Emotional Skills Still Core to Many Jobs


While AI excels at fast, consistent logic-based operations, EQ abilities have proven more resilient to automation. Interpersonal skills like building trust, active listening, conflict resolution and showing empathy are inherently human strengths less subject to replacement by technology (Kim et al., 2018). Jobs centered on caring for others, managing people, teaching/training, and creativity/innovation therefore retain a high need for human EQ (Spiezia & Lim, 2016). Researchers forecast roles involving social-emotional interactions, like healthcare providers, teachers and recruiters, will maintain a prominent human role alongside AI (Vincent, 2019).


Blending IQ and EQ in Hybrid Jobs


However, in many careers a combination of cognitive and emotional skills will be required working side-by-side with AI. For instance, paralegals now use AI tools to conduct legal research far quicker than humans alone but still need human judgment to interpret results appropriately (Meyer, 2020). Similarly, while AI can diagnose medical images, physicians rely on EQ to compassionately counsel patients, establish trust, and apply clinical expertise AI cannot replicate (Topol, 2019). As a result, hybrid human-AI teaming requiring balanced IQ-EQ is forecast as a future norm across industries like law, healthcare and customer service (Vincent, 2019).


Industry Examples


Below are three industry examples that illustrate how IQ-EQ blends are emerging in specific career contexts with AI integration.


Finance - AI-Assisted Financial Advisors


In wealth management, AI handles basic portfolio creation and analysis but financial advisors still use their EQ to build long-term client relationships based on trust and understanding of life goals beyond financials alone (Investopedia, n.d.). Leading firms now offer "robo-advisors" supporting humans through personalized advice at scale. For instance, Betterment pairs clients with certified financial advisors to answer questions while its AI-powered tools automate investing based on a client's risk profile and financial plan developed jointly with an advisor. This model enhances advisors' EQ impact with AI-powered portfolio management at lower costs for mass-market clients.


Manufacturing - Collaborative Robotics in Auto Plants


In auto manufacturing, collaborative robots (cobots) work safely alongside humans by handling repetitive production tasks like parts assembly and material handling. However, EQ skills remain key for workers to problem-solve production issues, train new cobots, and oversee quality control where judgment is still needed (Deloitte, 2018). At BMW and GM plants, workers monitor cobot-assisted assembly and focus on more mentally engaging jobs like equipment configuration, programming updates and troubleshooting alongside robotics using their technical know-how. This use of collaborative AI supports human workers rather than replacing them outright.


Healthcare - AI-Powered Virtual Assistants for Clinicians


In healthcare, AI clinical decision support tools are augmenting clinician IQ - for instance, flagging abnormal test results or providing differential diagnosis suggestions. Meanwhile, health chatbots or intelligent virtual assistants are handling basic patient inquiries to free up clinician time. However, the EQ aspects of direct patient care, counseling and complex treatment planning still require human providers (Topol, 2019). For example, Anthropic's PBCare AI assistant helps doctors by extracting patient data to populate forms and scheduling templates, while doctors focus on face-to-face care demanding high EQ like diagnosing conditions and devising treatment plans jointly with fully-informed patients. This keeps clinicians central in the care experience even with AI productivity aids.


Conclusion


AI is changing the IQ and EQ balance differentially across jobs and industries depending on their specific cognitive and emotional requirements. While routine IQ tasks are readily automated, most jobs still rely on enriched EQ from human judgment, interpersonal skills and creativity that AI cannot yet replicate. As a result, future work will involve more hybrid human-AI symbiosis requiring balanced IQ-EQ from all involved. For organizations and leaders, this means investing in both employees’ technical acumen and their social-emotional abilities to thrive alongside increasingly intelligent machines. As AI continues advancing work, cultivating high-performing IQ-EQ teams equipped for collaborative roles with technology will sustain human competitive advantages in the years to come.


References


 

Jonathan H. Westover, PhD is Chief Academic & Learning Officer (HCI Academy); Chair/Professor, Organizational Leadership (UVU); OD Consultant (Human Capital Innovations). Read Jonathan Westover's executive profile here.



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