Upcoming public speech
- Place: SCTE AI/ML WG Meeting
- Date/time: July 16th, Thursday 11AM US Mountain Time
- Topic: AI Labor and Human Labor: Cost, Capability, and the Work That Remains.
- LinkedIn Announcement: https://www.linkedin.com/groups/16903013/
Suggested outline
Building on my recent discussion with Fortune and my article on The AI Labor Divide, the presentation will examine why AI should not yet be understood as a universal substitute for human labor. At the enterprise level, AI deployment still involves significant costs, including compute, inference, data integration, monitoring, human review, governance, and workflow redesign. Therefore, the recent wave of layoffs, particularly among large technology firms and AI-capex-intensive companies, should be interpreted with caution. It reflects not only AI adoption, but also post-pandemic overhiring corrections, investor pressure to demonstrate productivity gains, and broader corporate efforts to rationalize labor costs.
At the same time, the presentation will emphasize that the long-term implications for workers are substantial. As inference costs decline, data-center capacity expands, and firms become more disciplined in how they deploy AI across workflows, a growing number of tasks will become economically contestable. The near-term transition is unlikely to be a simple replacement of human workers by AI systems. Rather, it will involve a restructuring of work in which fewer employees may be expected to produce more output through effective use of AI tools. The key distinction will increasingly be between ordinary human labor and AI-leveraged human labor. The presentation will therefore focus on what this means for employees and managers in the cable and telecom sector, including which tasks are most exposed, which human capabilities remain durable, and how workers can strengthen their value through domain expertise, judgment, accountability, coordination, and effective oversight of AI-enabled workflows.