The U.S. Federal Reserve is about to begin its first real rate-cutting cycle since the COVID-19 pandemic. And we think that this time, the timing couldn’t be more explosive…
Because unlike in the past, when businesses spent resulting incremental liquidity on buybacks or office expansions, today’s corporate boardrooms have just one singular obsession: Artificial Intelligence.
That’s why we’re confident that the flood of liquidity coming after the Fed cuts rates this month isn’t going toward more cubicles, delivery vans, or advertising slots.
It’ll go straight into GPUs, data centers, software pilots, and robotics development and rollouts instead.
In other words, it’s time to get ready for the next parabolic leg of this market.
And we think we know just how to play it…
The Policy Backdrop: Inflation, Jobs, and the Federal Reserve Pivot
After the fastest rate-hiking cycle in 40 years, the Fed is now poised to pivot.
Inflation has cooled significantly from its 9% high in 2022, currently measuring 2.9% – much closer to the Federal Reserve’s 2% target.
August’s Consumer Price Index (CPI) data did show headline CPI rose 0.4% on the month, faster than the 0.3% median economist forecast and double the pace of July. But core CPI rose 0.3% month-over-month, coming in as expected.
Importantly, the index’s 0.13% rise in core goods prices reflects a substantial slowdown for the category. It was the smallest increase since March, suggesting past tariffs are no longer a major driver of inflation.
Meanwhile, unemployment is on the rise. Initial jobless claims rose by 27,000 to 263,000 for the week ending Sept. 6 – the highest level in almost four years.
Financial conditions have tightened just enough to give Fed Board Chair Powell & Co. cover…
Especially considering all the pressure from the Trump administration, the new Fed governors, the mortgage fraud case against the central bank’s Lisa Cook…
It all points to one thing: rate cuts.
Why Lower Interest Rates Funnel Liquidity Straight Into AI
The first is likely to be a 25-basis-point cut coming later this month, with more to follow over the next 12 to 18 months. All told, the market is expecting at least five cuts into the end of 2026.
Those lower policy rates will result in cheaper corporate bonds, bank loans, and overall capital, helping to stimulate the U.S. economy.
Now, here’s why this matters so much right now…
When the cost of capital falls, companies ask themselves, “Where can we deploy new dollars for the highest ROI?” In 1995, it was supply chain buildouts. In ’98, it was the internet. 2009 was all about cloud infrastructure.
Today, there’s no debate. C-suite surveys and boardroom chatter all point to the same thing: AI is priority No. 1.
Every extra dollar freed up by falling rates has a high probability of flowing directly into AI initiatives. Just think about the tidal wave that’s building:
- Hyperscalers’ – i.e. Microsoft (MSFT), Alphabet (GOOGL), Amazon (AMZN), and Meta (META) – capital expenditure (capex) are running at record levels. Rate cuts lower their financing costs and boost free cash flow: fuel for another round of $100 billion-plus AI buildouts.
- Enterprises are cautiously piloting AI software. Lower borrowing costs and improved liquidity confidence will nudge them from ‘pilot’ to ‘deployment.’
- Startups should see venture funding return with a vengeance. Limited partners (LPs) re-risk when the 10-year yield falls, capitalizing seed-to-Series B AI projects – and creating the next pipeline of innovation.
Liquidity feeds capex, which feeds earnings, which feeds stock prices. Reflexivity takes over. Rising stock prices make it easier to raise capital, which funds more projects – and drives more stock gains.
What It Means for Investors
The implications here are simple: the incoming rate-cut cycle will most likely accelerate the AI Boom. And investors who get positioned before this tidal wave hits should benefit disproportionately.
Here’s where we see the best opportunities.
Core AI Infrastructure Stocks: The First Beneficiaries of Rate Cuts
When capital is cheap, hyperscalers don’t hesitate. Every incremental data center means more demand for:
- Accelerators – Nvidia (NVDA), AMD (AMD): GPUs remain the choke point of the AI economy. With demand far outstripping supply, hyperscalers are on pace to spend more than $200 billion annually on AI chips and infrastructure. Rate cuts lower financing costs, allowing Microsoft, Google, Amazon, and Meta to expand orders without stressing free cash flow. Nvidia’s CUDA ecosystem and AMD’s MI300 series stand to capture that demand directly.
- Memory – Micron (MU): AI workloads require multiples more DRAM and high-bandwidth memory (HBM) than traditional cloud tasks. Micron’s HBM3E rollout is already sold out into 2025. Lower rates extend enterprise budgets, accelerating adoption cycles.
- Networking – Arista (ANET), Broadcom (AVGO), Marvell (MRVL): Training large language models requires ultra-low latency interconnects. Ethernet and custom ASIC demand surges as clusters scale from thousands to tens of thousands of GPUs. These suppliers capture that bottleneck.
- Power & Cooling – Vertiv (VRT), Eaton (ETN): A single AI data center can consume as much power as a mid-size city. Vertiv’s liquid cooling solutions and Eaton’s electrical management systems sit at the center of hyperscaler RFPs. Lower rates = more buildouts = more orders.
- Servers & Integrators – Dell (DELL), Supermicro (SMCI): These firms stitch together GPU clusters into deployable racks. Supermicro is already growing triple digits by capitalizing on its nimbleness. Cheaper capital fuels the next wave of hyperscale orders, directly boosting backlog and margins.
These are the ‘first movers.’ They feel the benefit within quarters of the first cut.
Software Platforms: Capturing the Secondary Wave of Investment
Once enterprises loosen budgets, the software layer benefits:
- Palantir (PLTR): Already positioned as the “operating system for AI,” Palantir is scaling deployments across government and commercial clients. Lower rates accelerate customer willingness to move from pilots to enterprise-wide rollouts.
- ServiceNow (NOW): Its AI copilots are embedding into workflows across HR, IT, and customer support. As CIOs free up budget from falling financing costs, they’ll prioritize productivity tools with demonstrable ROI.
- Datadog (DDOG), Elastic (ESTC), CrowdStrike (CRWD): Observability, search, and cybersecurity are all being transformed by AI. Rate-driven capex unlocks the ability for enterprises to not just experiment but standardize these tools across entire organizations.
This is the six- to 12-month lag effect: enterprises wait for macro clarity, then deploy capital at scale.
Physical AI and Robotics: A Longer-Term Play Supercharged by Fed Cuts
Cheaper money means moonshot robotics projects suddenly make financial sense.
- Tesla (TSLA): Optimus humanoid robots move closer to commercial viability when financing costs fall, as deployment is heavily capex-driven.
- Boston Dynamics and warehouse automation players: Robotics-as-a-service models thrive when hurdle rates compress.
- Critical suppliers like MP Materials (MP), Ambarella (AMBA): Rare-earth magnets (MP) and edge vision chips (AMBA) are critical to scaling robotic and autonomous systems. As liquidity improves, funding flows downstream into the component suppliers that make physical AI possible.
This is the long-duration call: rate cuts extend investment horizons, making robotics projects with uncertain near-term payoffs much more attractive on a discounted cash-flow basis.
Will Rate Cuts Create Another Bubble – or a Durable AI Boom?
Of course, bearish skeptics may point to what happened after the Fed cut rates in 1998-99 and say, ‘not so fast.’
At that time, Long-Term Capital Management – a high-profile hedge fund that executed highly leveraged trading strategies – collapsed following Russia’s debt default. This forced the U.S. government to coordinate a $3.6-billion bailout to prevent a potential global financial crisis.
The Federal Reserve went on to cut rates after this crisis, and that subsequent liquidity helped supercharge the dot-com bubble. The Nasdaq doubled in 18 months, then imploded. Could history repeat?
Yes… but there’s one key difference here. Often, the darlings of the dot-com era were pre-profit, pre-revenue. But today’s AI leaders are cash machines.
Nvidia, Broadcom, Microsoft – these titans aren’t anywhere close to Pets.com. They’re throwing off tens of billions in free cash flow.
Of course, there will be froth. Some of 2025’s AI IPOs will look absurd. But the core of this boom is built on real earnings power. That’s a critical distinction.
The Final Word: How Federal Reserve Policy Could Reshape AI Investing
With multiple Fed rate cuts coming – starting just days from now – a flood of liquidity is headed straight for the markets. And every CFO in America knows exactly where to funnel it: AI.
This policy shift should be a supercharger for the most powerful growth theme of our generation. The monetary tide is turning, and it’ll flow straight into artificial intelligence.
Investors who catch this wave early could ride it for years.
Now here’s where the story gets even bigger.
Most headlines focus on GPUs and data centers. But the real moonshot is what happens when that same cheap capital accelerates Physical AI: robots that walk, work – and reshape trillion-dollar industries.
Tesla’s Optimus, Boston Dynamics’ humanoids, and warehouse automation are no longer ‘someday’ ideas. With hurdle rates set to fall, they’ll suddenly be fundable. And the opportunity therein is massive: robotics could penetrate everything from logistics to elder care to manufacturing, unlocking a multi-trillion-dollar total addressable market.
That’s why the smartest money isn’t just chasing Nvidia; it’s hunting the critical suppliers that turn robots into capable workers. This is where fortunes will be made in the next phase of the AI boom.
