AI is commodifying knowledge work — break down workflows to find augmentation opportunities¶
Insight: Leading organizations (Metalab, Superside) leverage AI fundamentally differently from average users — they auto-generate localized creative based on design systems and content guidelines, while average users generate stock art. Product teams should decompose their work into three workstreams (Operations, Creativity, Productivity), then break each into discrete activities to identify what AI can augment or automate. Anthropic's own Economic Index shows AI use is most prevalent in computer/mathematical occupations; design and creative tasks aren't core use cases yet.
Detail: Sara Vienna (Metalab CDO) identifies that product orgs are built around delivery, not design excellence — this must shift. Design must move from creating pixel-perfect interfaces to ones that adapt and spawn based on user interactions. McKinsey research finds the biggest barrier to scaling AI is not employees (who are ready) but leaders who aren't steering fast enough. The practical action plan: Plan projects with templates, Communicate ideas better through AI iteration, Question rationale with AI, Compile broader inspiration, Analyze larger datasets, Challenge concepts through AI variants, Create more deliverables through automation.