This Week in AI

5 curated reads for the week of March 30, 2026

0 of 5 read this week

Business7 minGood for Sunday

State of AI trust in 2026: Shifting to the agentic era

McKinsey

McKinsey’s trust survey frames the big shift from “AI that might say the wrong thing” to agentic systems that can do the wrong thing—trigger actions, misuse tools, or exceed intended scope. Useful if you’re trying to scale AI beyond pilots: it lays out where organizations tend to be weakest (governance, risk processes, and ownership), and what “trust maturity” looks like in practice.

#trust#governance#agents

Tools5 minGood for midweek

Powering Product Discovery in ChatGPT

OpenAI

OpenAI is expanding shopping in ChatGPT into a more structured product-discovery experience: richer browsing, comparisons, and clearer paths from “I’m exploring” to “I’m deciding.” The strategic signal is distribution—AI is competing with search and marketplaces by becoming the first place people go when they don’t yet know what they want.

#shopping#search#commerce

Models3 minGood for midweek

Lyria 3 Pro: Create longer tracks in more Google products

Google (The Keyword)

Google’s Lyria 3 Pro is a music-generation model aimed at creators: longer tracks (up to ~3 minutes), more control over song structure (intros/verses/choruses), and availability across more Google surfaces. The non-technical takeaway is productization: “models” matter most when they show up as usable features inside tools people already use to create.

#music#creative#products

Regulation6 minGood for Friday

Protecting People from Harmful Manipulation

Google DeepMind

DeepMind summarizes new work on the risk of AI-enabled persuasion and releases measurement tools for evaluating “harmful manipulation” more rigorously. The value for non-technical readers is the shift toward testable safety claims: instead of vague assurances, this is an attempt to define what counts as manipulation and measure it systematically.

#safety#misinformation#evals

Regulation7 minGood for Sunday

A people-first vision for the future of work in the age of AI

Brookings Institution

Brookings argues the near-term risk isn’t only job counts—it’s job quality, bargaining power, and who benefits from productivity gains. The actionable part is a concrete “people-first” agenda: build scalable training pathways, strengthen institutions that support workers, and shape deployment so AI augments work rather than silently degrading it.

#workforce#labor#policy

Going Deeper

Optional reads for those who want more. (Some may be behind a paywall)

Gemini 3.1 Flash Live: Making audio AI more natural and reliableGoogle (The Keyword)More technical than the main list, but a useful deep dive on what makes real-time voice assistants feel “human” (latency, robustness, multilingual).
Inside our approach to the Model SpecOpenAIA readable governance explanation of how OpenAI defines “model behavior” and updates it as capability and usage scale.
Where to look for generative AI risksMIT SloanA clean non-technical framework: “embedded” vs “enacted” risk, plus a practical inventory + ownership approach for reducing exposure.

Professional Impact Spotlight

Journalist

AI is reshaping journalism from transcription to first drafts, with the biggest risk falling on local news and commodity content.

Read the full breakdown →