AI Intelligence Brief

Sun 29 March 2026

Weekly Brief — Curated and contextualised by Best Practice AI

76Articles
Editor's pickEditor's Highlights

Alphabet and Meta Pledge $305 Billion, CEOs Admit Zero Impact, and Memory Stocks Shed $100 Billion

TL;DR Alphabet and Meta announced $305 billion in AI-related capital expenditures for 2026. Goldman Sachs reported AI added zero to US economic growth in 2025 despite $410 billion in investments. OpenAI shut down its Sora video platform and canceled a $1 billion Disney deal. Chinese authorities blocked the $2 billion sale of AI startup Manus to Meta and barred its founders from leaving the country. Fortune cited CFOs projecting 502,000 AI-attributed job losses this year, a ninefold increase from 2025. Memory chip stocks lost $100 billion in value as research showed AI data centers need far less capacity than expected.

Economics & Markets

22 articles
AI Investment & Valuations9 articles
AI Productivity7 articles

Labor & Society

26 articles
AI & Employment12 articles
Editor's pick
Guardian· 8 days ago

Divide between Silicon Valley and ordinary people grows ever larger

Big tech believes the future is AI while everyday Americans remain wary; and the dangers of riding in a Tesla Cybertruck Hello, and welcome to TechScape. I’m your host, Blake Montgomery. This week in tech, we discuss a moment of divergence between Silicon Valley and everyday people; deep cuts at Meta to maximize spending on AI; writers caught using AI; and the frightening, fiery crashes of the

Editor's pickPAYWALL
Bloomberg Opinion· 7 days ago

AI washing is masking an insidious labour crisis

Companies citing AI adoption as reason for job cuts — 'AI washing' — using AI as rhetorical cover for cost-cutting.

Editor's pick
The World Data· 7 days ago

AI Job Displacement Statistics 2026

GenAI investment increased nearly 8x since November 2022. Gap between automation and retraining creates human cost.

Editor's pick
Medium· 7 days ago

The New Reality of Work: AI, Restructuring, and the Labor Market in 2026

Global job market undergoing most profound structural shift since industrial revolution in 2024-2026.

Editor's pick
Harvard Business Review· 6 days ago

HBR research: generative AI reshaping, not erasing, white-collar work

New research in HBR finds early evidence that generative AI is reshaping white-collar work through task-level substitution rather than wholesale job elimination, with differential effects by occupation. Jobs requiring codifiable knowledge face higher automation risk; those requiring tacit, experiential knowledge are more complemented by AI. One of the first empirical snapshots of AI's actual labou

Editor's pickTechnology
TechCrunch· 10 days ago

Are AI Tokens the New Signing Bonus or Just a Cost of Doing Business?

TechCrunch

AI Skills & Education7 articles

Technology & Infrastructure

10 articles

Adoption & Impact

14 articles
AI Adoption & Diffusion9 articles
Editor's pickPAYWALLTechnology
feeds· 9 days ago

Companies Aren’t Ripping Out Business Software for AI. Here’s What They’re Doing Instead.

Tech leaders at large corporations say that, for now, they’re vibe-coding their own small, custom apps, and putting pressure on their software vendors.

Editor's pick
Daily AI News· 9 days ago

AI Adoption Increases Operating Costs

Token usage is becoming a real operating cost for enterprises as AI adoption moves from experimentation to scaled deployment. Companies are starting to track tokens as a proxy for compute spend, productivity, and governance. Leaders need new budgeting and measurement frameworks because AI is one of the first major enterprise software categories where successful usage can materially increase the bi

Editor's pick
Daily AI News· 9 days ago

Best AI Users

The strongest users of large language models are more ambitious, treat AI as a reasoning partner, delegate complex tasks with clear objectives, and use it as a general cognitive tool rather than just a shortcut. This shifts the question from simple adoption metrics to what sophisticated AI use actually looks like across the workforce.

Editor's pickTechnology
Daily AI News· 8 days ago

Scaling AI Agents Successfully

To scale AI agents successfully, think of them like team members. This framing surfaces useful reminders around permissions, scope, security, and accountability, but most of those cautions were seen as familiar governance basics rather than new guidance for experienced AI leaders.

Editor's pickTechnology
VentureBeat· 7 days ago

The Three Disciplines Separating AI Agent Demos

The three disciplines separating AI agent demos from real-world deployment

Editor's pickPAYWALL
Bloomberg Opinion· 7 days ago

AI is hitting the sweet part of the S-curve

Drawing on Jevons Paradox, AI is entering steepest part of adoption S-curve. Greater efficiency expands demand rather than constraining it.

Editor's pick
@emollick· 6 days ago

The whole reason for the J-curve for new technologies is that there is some cost to learning and experimentation. And for AI, there may be outsized returns to really bold (and often quite cheap) experiments. Fast follower is a risky strategy with exponential improvement happening

The whole reason for the J-curve for new technologies is that there is some cost to learning and experimentation. And for AI, there may be outsized returns to really bold (and often quite cheap) experiments. Fast follower is a risky strategy with exponential improvement happening

Editor's pick
@emollick· 6 days ago

I think that if companies are not failing at all with their AI efforts it is a sign that they are not being ambitious enough. This is a fundamentally new technology that we do not know how to use well. Achieving breakthroughs will require experimentation, which require failure.

I think that if companies are not failing at all with their AI efforts it is a sign that they are not being ambitious enough. This is a fundamentally new technology that we do not know how to use well. Achieving breakthroughs will require experimentation, which require failure.

Editor's pick
Daily AI News· 9 days ago

Best AI Users

The strongest users of large language models are more ambitious, treat AI as a reasoning partner, delegate complex tasks with clear objectives, and use it as a general cognitive tool rather than just a shortcut. This shifts the question from simple adoption metrics to what sophisticated AI use actually looks like across the workforce.

Geopolitics

3 articles

Other

1 articles
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