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Dear Readers,
The ground beneath global finance is shifting faster than ever: AI is no longer just an abstract force in labs or boardrooms, but a tangible driver of trade, asset management, and even monetary policy. When algorithms can forecast inflation in real time or automate billion-dollar investment decisions, the old playbook of slow reports and cautious adjustments starts to look like ancient history. The question is no longer if AI will reshape the economy, but how deeply it will redefine the rules.
In today’s issue, we explore how the WTO sees AI lifting global trade by over a third, why McKinsey predicts asset managers will compete on tech culture rather than returns, and how central banks are flirting with real-time AI models to steer monetary policy. Alongside this, we bring you the latest from OpenAI, xAI’s Grok 4 Fast, and sharp insights on what it means when the entire economy is treated like a learning machine. Let’s dive in - because the next chapter of finance is already being written.
In Today’s Issue:
⚡ Grok 4 Fast just dropped, bringing near top-tier AI performance
📈 The WTO predicts AI will boost global trade
💼 McKinsey reveals how AI is set to revolutionize asset management
🏦 Central banks are turning to AI for real-time data to make faster
✨ And more AI goodness…
All the best,
OpenAI has released a large-scale study on how people are using ChatGPT.
The way ChatGPT is used is constantly changing. A large-scale study now shows the purposes for which ChatGPT is used today.
Grok 4 Fast pushes boundaries
Grok 4 is once again shifting the price-performance ratio in AI, marking a new leap forward. However, the GPQA Diamond benchmark used to date appears to have reached its limits, as test errors make a 100% result impossible – tougher benchmarks are needed.
The economy as a learning machine
OpenAI expects the entire economy to transform into a kind of “reinforcement learning machine.” AI models will learn from recordings of how skilled workers perform their daily tasks, supported by targeted data sets and experts who work on real-world tasks in applications.
Over the next few weeks, we are launching some new compute-intensive offerings. Because of the associated costs, some features will initially only be available to Pro subscribers, and some new products will have additional fees.
Our intention remains to drive the cost of
— #Sam Altman (#@sama)
6:45 PM • Sep 21, 2025
In the coming weeks, OpenAI will release some very computationally intensive products. An exciting time lies ahead.
Mustafa Suleyman (CEO of Microsoft AI): Today, LLMs are only one-shot prediction engines. With persistent memory and long-term predictions, they could soon be able to plan entire courses of action like humans. → Actionable AI by the end of 2026 – “breathtaking,” according to Suleyman.
The Takeaway
👉 Grok 4 Fast delivers near Grok 4-level performance with significantly lower token consumption—ideal for everyday AI and projects with limited budgets.
👉 A model with combined modes (reasoning + non-reasoning) reduces latency and costs without compromising on meaningfulness.
👉 Real-time web and X browsing plus large context windows make answers more current and relevant, especially for dynamic questions.
👉 Lower prices enable broader access to state-of-the-art AI: for developers, educators, NGOs—not just large companies.
A model that thinks, learns, and surfs—and is more economical than ever before: Grok 4 Fast from xAI combines smart computing power with affordable costs. It achieves results similar to those of Grok 4, but requires about 40% fewer tokens for thinking—which pays off noticeably when it comes to complex tasks.
What makes it special: Grok 4 Fast combines reasoning mode (for complex thinking tasks) and non-reasoning mode (for quick answers) in one model. It can also browse the web and X (formerly Twitter) in real time, incorporate images or videos, and thus make answers more up-to-date and accurate. Context windows of up to 2 million tokens enable deep conversations or extensive documents without constantly having to “start thinking again.”
When models like Grok 4 Fast can deliver performance without astronomically large data centers or expensive token budgets, access to AI opens up to more developers, more applications, and more innovation.
We may be at the beginning of a new phase in which “grande” AI does not automatically mean “extremely expensive.” How will tool stacks change when efficiency becomes the standard? What new projects will become possible when costs fall proportionally and performance increases?
Why it matters: Grok 4 Fast dramatically reduces the cost of high-quality AI performance without any noticeable drop in performance. This means that advanced AI usage is no longer just for the wealthy or large corporations.
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WTO: Artificial intelligence as a driver of global trade and productivity
The WTO report predicts that AI could increase global trade by 34–37% by 2040 and that global GDP will be 12–13% higher than it would be without massive AI integration. The main drivers are lower trade costs and efficiency gains in logistics, compliance, and communication—particularly through automatic translation and better infrastructure. The distribution of these gains will depend heavily on how much countries and regions invest in digital infrastructure, education, and fair regulatory conditions. For investors, this means focusing on locations/companies with high-tech infrastructure and favorable regulations; for monetary policy, it means figuring out how to manage inflation and inequality when productivity increases at different rates.
How AI Could Reshape the Asset Management Industry
McKinsey estimates that generative AI can bring significant efficiency gains in asset management: for example, around 8% cost savings through faster research and reporting, and around 5% through automation in risk/compliance. Significantly higher productivity gains are also possible in technology and IT services. Turning point: The integration of AI into core processes is shifting competition from returns alone to speed, data access, and internal engineering culture. For markets, this means that differentiation between asset managers will depend more on technological capabilities and regulatory certainty.
AI and monetary policy – real-time data as a game changer
Central banks are beginning to use AI models to forecast inflation, growth, and market sentiment. This shortens response times and allows for more precise interventions, but it also poses new risks: non-transparent models can exacerbate misguided policies. As a result, monetary policy is shifting from traditional indicators to data-driven real-time signals—an opportunity for more efficient control, but also a problem of legitimacy. For investors, this means more volatile markets and tougher competition for information advantage.
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