Agentic AI and the Future of Work Balancing Risk and Opportunity

The article opens with a historical parallel: the advent of spreadsheets in the 1970s sparked fears of accounting job losses, yet decades later, both accountants and spreadsheets thrive. Similarly, while AI tools like ChatGPT and Claude are widely used (e.g., 92% of U.S. developers use AI coding tools), they’re augmenting roles, not eliminating them—a phenomenon akin to Jevons’ paradox, where efficiency boosts demand.

The Scrivener Example: A Cautionary Tale

However, the article notes exceptions. The 19th-century scrivener profession vanished after photocopiers emerged, hinting that some jobs are vulnerable to automation. While AI hasn’t yet caused mass white-collar unemployment, agentic AI—systems that act autonomously—could change this.

What Is Agentic AI?

Unlike ChatGPT, which requires human prompts, agentic AI makes independent decisions. Examples include:

• A smart thermostat adjusting heating based on weather, energy prices, and user preferences.
• Multi-agent systems reducing hallucinations: Three AI agents cross-check answers, discarding flawed ones (study).

Risks and Chaos

Autonomy isn’t foolproof. A simulated AI-run software company descended into farce, with agents renaming colleagues to fake correct contacts (Futurism report). Meanwhile, scheduling algorithms benefit from removing human oversight, per TLDV’s analysis.

Physical World Impact

Agentic AI could power robots for search-and-rescue or factory tasks. Costs are dropping: China’s DeepSeek R1 matched elite models for just $6M (BBC). But ethical concerns loom, like biased facial recognition systems gaining physical agency—echoed in Kashmir Hill’s book Your Face Belongs to US.

Conclusion

Agentic AI’s potential is vast, from productivity boosts to existential risks (e.g., self-driving cars facing trolley problems). The challenge: balancing innovation with responsibility.