AI in Product Ops: What Changed (and Why)
AI transformed my product operations when I treated it like a workflow partner, not a chatbot: automation for repeatable tasks, decision intelligence for trade-offs, agentic AI systems for end-to-end handoffs, and real evaluation to reach production-grade reliability.
AI Marketing Ops: Real Results, Less Chaos
AI transformed my marketing operations when I treated it like a teammate with guardrails: invest where ROI is measurable (faster cycles, less rework, scalable content production), track brand discovery across AI summaries/overviews, and prepare for AI agents as the next gatekeepers—without losing human connections.
AI & Data Science Ops: Real Results, 2026
AI and data science ops improved most when we treated generative AI as an organizational resource, built ‘AI factories’ (platform + methods + data + algorithms), invested in AI-ready data, and matured leadership (hello, chief data officer). Agentic AI is real but entering the trough of disillusionment; edge AI and smaller domain optimized models will quietly win on latency, cost, and sovereignty. Open source AI is speeding up governance and capability—if you operationalize it. Plan for denser hybrid computing (even quantum assisted) as AI infrastructure evolves toward 2026.