Why AI Threatens Middle Management Before Coders: Insights from Entrepreneur Anupam Mittal

Artificial intelligence (AI) is reshaping the workplace in profound ways, but its impact is not uniform across job roles. Entrepreneur and investor Anupam Mittal, known for his role on Shark Tank India, highlights a critical shift: AI is poised to disrupt middle management before it significantly affects coders. This perspective challenges the common narrative that software developers and coders are the first to face automation risks. Instead, Mittal points out that traditional managerial roles, especially those focused on coordination and seniority-based authority, are becoming increasingly obsolete in the AI era.

Middle managers often serve as intermediaries, facilitating communication, overseeing routine processes, and enforcing hierarchical structures. AI technologies, with their capabilities in data processing, task automation, and decision support, can efficiently handle many of these functions. As a result, the value proposition of middle management is diminishing. Mittal argues that this trend is driven by AI's ability to streamline workflows and reduce the need for human oversight in coordination tasks, which historically have been a core responsibility of managers.

The future of work, according to Mittal, favors what he terms "Individual Contributor Plus" professionals. These individuals combine deep expertise with the ability to leverage AI tools to amplify their productivity and output. Unlike traditional managers who primarily focus on supervising teams, these contributors emphasize building tangible products and delivering measurable outcomes. Their success hinges on integrating AI into their workflows to enhance creativity, efficiency, and innovation rather than merely managing people or processes.

This shift has broader implications for organizational structures and career development. Companies may need to rethink promotion pathways that traditionally reward managerial roles as the pinnacle of career advancement. Instead, fostering growth opportunities for individual contributors who excel in applying AI could become the new norm. Furthermore, the emphasis on measurable outcomes aligns with a results-driven culture, where value is assessed based on concrete deliverables rather than hierarchical status.

Mittal’s insights also suggest that coders and technical professionals are not immune to AI’s influence but may experience its effects differently. While AI can automate certain coding tasks, the demand for skilled developers who can design, implement, and oversee complex AI systems remains strong. Therefore, rather than being displaced, coders might evolve into roles that require higher-level problem-solving and AI integration skills.

In summary, Anupam Mittal’s analysis underscores a nuanced understanding of AI’s impact on the workforce. It challenges assumptions about which roles are most vulnerable and highlights the importance of adaptability and AI proficiency. For professionals and organizations alike, embracing the "Individual Contributor Plus" model could be key to thriving in an AI-driven future.