A rational conversation on where AI is actually going | Benedict Evans

2026-05-24 · Source: Lenny's Newsletter · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Corporate Strategy & Leadership · Depth: Intermediate, extended

Summary

Benedict Evans, an independent analyst, posits that AI represents a transformative shift comparable to the internet or mobile, characterizing the current phase as an "internet 1997 moment" where much remains unbuilt and uncertain. He challenges widespread fears of job displacement, arguing that historical patterns show automation consistently creates new roles, citing examples like spreadsheets and software development tools. Evans highlights that the true value in many professions lies beyond easily automatable tasks, explaining why AI labs are investing in consulting services to integrate AI into complex workflows. He suggests that foundational AI models may eventually become commoditized, with significant value accruing to application layers and distribution channels. Evans also addresses anti-AI sentiment, noting it's a mix of valid concerns and misinformation, and emphasizes the radical uncertainty of AI's future impact, urging engagement rather than avoidance.

Key takeaway

For leaders and professionals navigating the AI landscape, recognize that while AI is transformative, its long-term value may not reside solely in foundational models. Instead, focus your investment and development efforts on building robust application layers and securing strong distribution channels. Actively engage with AI tools to understand their evolving capabilities and identify non-automatable aspects of your work. Avoid dismissing AI, as direct engagement is crucial for adapting to future shifts and maintaining competitive advantage.

Key insights

AI is a transformative platform shift, akin to the internet's early days, with value shifting to application layers and distribution.

Principles

• Automation historically creates more new jobs than it displaces.
• The core "job" often transcends automatable "tasks."
• Foundational AI models may commoditize, shifting value to applications.

In practice

• Engage directly with AI to understand its capabilities.
• Focus on complex problem-solving beyond automatable tasks.
• Prioritize distribution for AI-powered product success.

Topics

• AI Platform Shifts
• Job Automation
• AI Value Chain
• Foundational Models
• Application Layer
• Distribution Strategy

Best for: Director of AI/ML, Investor, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Lenny's Newsletter.