Market news & insights

Global markets are calm but alert in response to the US–Venezuela situation, with US and European equities holding near or testing record levels.

Gains in energy, defence and materials suggest selective positioning. Modest strength in gold and lower yields is indicative of hedging rather than market fear, with oil prices remaining muted.

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Quick facts

• US and European equity indices are holding near record highs despite geopolitical headlines. Volatility remains low through the trading session.
• Energy and defence stocks are leading gains, with materials stocks responding to mild gains in previous metals, reflecting selective risk positioning.
• Gold is edging higher, and government bond yields have dipped slightly, signalling mild hedging.
• Oil prices remain range-bound, suggesting no immediate supply shock is being priced in.
• Markets could be sensitive to further geopolitical developments, with any escalation a major potential risk to sentiment.

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US–Venezuela tensions escalation has prompted heightened geopolitical scrutiny across the globe, not only related to this action itself but other geopolitical longer-term implications. 

There has been a muted and measured response across global financial markets so far, with little significant negative impact evident for now. 

Some sectors have had noteworthy gains, whilst the impact on other asset classes has again been calm.

US equities 

What’s happening:

US equity markets are showing resilience, with the S&P 500 holding near recent highs and the Dow Jones Industrial Average up 1.23%, pushing into fresh record territory.

What to watch:

• If US indices continue to hold above recent breakout levels, then markets are reinforcing the view that geopolitical risk remains manageable.
• Rising volatility, if seen in the VIX index, may indicate that sentiment may be shifting from selective risk-taking to broader caution.

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European equities

What’s happening:‍

European markets are modestly higher, with the DAX trading at record levels and the FTSE 100 closing over 10,000 for the first time.

What to watch:

• For now, European indices appear to be tracking US strength, suggesting investors are viewing the event as externally contained. Similar sectors are performing well, as seen in overnight US equity performance. 
• It is unlikely that we will see any specific regional response, though tensions related to the US administration's narrative around Greenland is noteworthy.

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Specific sector moves

‍Energy stocks

What’s happening:‍

Energy stocks are leading equity gains across the US (e.g. Chevron Corp – CVX up 5.1%), and European markets, with the potential for increased influence in Venezuela of US oil companies.

What to watch:

• While energy equities outperform while oil prices remain range-bound, then markets are pricing geopolitical caution rather than immediate disruption. If this is accompanied by a rise in crude prices rise together, then it may be indicative of supply risk
  

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Defence stocks

What’s happening:‍

Defence stocks are attracting some investor interest. (E.g. Lockheed Martin – LMT up 2.92%, General Dynamics – GD up  3.54%).

What to watch:

• Continued outperformance with other sector equity drawdowns may be indicative of some escalation concerns.

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‍Materials & miners

What’s happening:‍

Materials and mining stocks are finding support alongside modest gains in precious metals and record highs in copper. The S&P Metals & Mining ETF – XME closed 3.28% up.

What to watch:

• Ongoing materials strength alongside stable growth indicators, then the current move may reflect real-asset demand rather than simply a hedging approach. If gold accelerates higher while base metals fail to follow, then investor defensive positioning may be overtaking confidence in growth.

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Crude oil

What’s happening:‍

Oil prices remain subdued, with the futures trading at $58.40, within recent ranges, despite the unfolding geopolitical situation. 

What to watch:

• Venezuelan influence on global oil production is not substantial enough on its own to create any major issues in the short term with global oil supply at high levels.
• As a result, the impact is more likely to remain muted, but any significant rises in oil price across multiple sessions may be indicative of some market concerns related to increases in geopolitical-influenced supply expectations.

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Gold

What’s happening:‍

Gold prices are currently edging higher towards all-time highs, reflecting a modest safe-haven play. The closing price for Gold futures is $4454, breaching the psychologically important $4400.

What to watch:

• If gold continues to rise gradually while equities remain firm, then the move reflects a standard hedging approach to assets rather than fear. 
• A spike in gold price alongside falling equities and rising volatility, maybe a signal that market risk may be increasing.

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Treasury yields

What’s happening:‍

Yields have eased slightly, indicating a potential selective defensive positioning in asset choice by institutional investors. (10-year Treasury yields at 4.153%, down 0.36%)

What to watch:

• If yields should fall sharply alongside equity weakness, then markets may be shifting toward a risk-off approach.

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What to watch next

• If asset-class correlations remain contained, then markets are maintaining confidence in the broader macro backdrop. 
• If tensions escalate into broader regional instability or prolonged policy responses, Sharp movements across equities, bonds, and commodities may signify a reassessment of risk.
• If geopolitical developments fail to translate into sustained price dislocation, then the current response is likely to fade.

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(All prices quoted correct as of 4.30pm NY time after market close).

January’s market action often matters more than simply marking the opening of the calendar year. Institutional positioning resets, testing of economic assumptions, and early price moves reflect how market participants interpret the first meaningful signals of the year.

While January rarely determines full-year outcomes, it frequently shapes the narratives markets carry into the first quarter (Q1).

Four critical levers: growth, labour, inflation, and policy, can provide an early indication of how markets are processing and prioritising incoming information.

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Growth: manufacturing PMIs

January’s first growth test comes from the manufacturing surveys, with markets watching whether signals from S&P Global Manufacturing PMI and ISM Manufacturing PMI tell a consistent story.

Key dates:

• ISM Manufacturing PMI: 5 January, 10:00 AM (ET)/ 6 January, 1:00 AM (AEDT)

What markets look for:

Attention often centres on new orders as a forward-looking indicator of demand, alongside prices paid for early insight into cost pressures.

Broad strength across both surveys would support the narrative that the growth momentum seen toward the end of 2025 may extend into early 2026, easing some concerns about a sharper slowdown. Weaker or conflicting readings would keep the growth outlook uncertain, rather than decisively negative.

How it tends to show up in markets:

Firmer growth signals often appear first in higher short-dated Treasury yields. Rising yields can tighten financial conditions, weigh on equity valuations, and support the USD, with spillover effects across foreign exchange (FX) and commodity markets.

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Labour: job openings and payrolls

While early-January Non-Farm Payrolls (NFP) often drive short-term volatility, JOLTS job openings may be more influential in shaping January’s policy narrative.

Key dates:

• JOLTS Job Openings: 7 January, 10:00 AM (ET)/ 8 January, 1:00 AM (AEDT)
• Non-Farm Payrolls (NFP): 9 January, 8:30 AM (ET)/ 10 January, 12:30 AM (AEDT)

What markets look for:

Markets often treat JOLTS as a clearer indicator of underlying labour demand than month-to-month hiring flows.

A continued drift lower in openings would support the view that labour demand is easing in an orderly way, reinforcing confidence that inflation pressures can continue to moderate. A rebound or stalled decline would suggest labour conditions remain firmer than expected.

Market sensitivities:

For markets, easing labour demand typically supports lower short-dated yields and a softer USD, while persistent tightness can push yields higher, strengthen the USD, and increase volatility across rate-sensitive assets.

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Inflation: PPI and CPI

Key Dates:

• PPI: 14 January, 8:30 AM (ET)/ 15 January, 12:30 AM (AEDT)
• CPI (December 2025 data): 15 January, 8:30 AM (ET)/ 16 January, 12:30 AM (AEDT)

The inflation signal can be read as a pipeline from producer prices to consumer inflation. Markets are watching whether producer-level cost pressures continue to fade or begin to re-emerge.

What markets look for:

Core PPI, particularly services-linked components, provides an early indication of cost momentum. Core CPI breadth may help determine whether inflation is continuing to cool or showing signs of persistence.

A softer pipeline would reinforce confidence that disinflation can extend into early 2026, increasing the scope for a potential March policy adjustment. Stickier CPI readings above 3% would raise questions about the durability of recent progress.

How rates and the USD often react

Market reaction tends to be led by yields. Cooling inflation pressure usually pulls short-dated yields lower and softens the USD, while persistent inflation risks can push yields higher and tighten financial conditions.

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Policy: January FOMC meeting

By the time the Federal Reserve meets at the end of January, markets will have processed the early growth, labour, and inflation signals of the year.

Key Dates:

• FOMC rate decision: 29 January, 2:00 PM (ET)/ 30 January, 6:00 AM (AEDT)

What markets look for:

A policy change is unlikely this month, but how those signals are framed in the statement and press conference still matters. With January cut expectations priced well below 20%, attention is on whether expectations for a March move, currently around 50%, begin to shift.

Confidence that inflation and labour pressures are easing would typically support lower yields and a softer USD. A more cautious tone could lift yields, strengthen the USD, and tighten global financial conditions.

Putting it all together

January’s data acts as condition-setters rather than decision points. The practical takeaway lies in how markets respond as those conditions become clearer:

If growth and labour soften while inflation continues to ease, markets may lean toward a more constructive risk backdrop, with Treasury yields remaining the key guide and expectations for policy easing later in Q1 firming.

If growth holds up and inflation proves sticky, a more cautious posture may be warranted, with heightened sensitivity to Treasury yields, USD strength, and pressure on equity valuations and rate-sensitive commodities.

In 2025, the S&P 500 traded around 6,835 and was up approximately 16% year to date (YTD). Market direction remained most sensitive to Federal Reserve expectations, inflation data and the earnings outlook, with returns also shaped by mega-cap tech leadership and the broader AI narrative. The index pulled back from earlier December highs, but it has so far held above key major moving averages (MA).

Key 2025 drivers included:

• ‍Fed expectations and inflation: Inflation cooled through the year but remained sticky around 2.5% to 3%. A Fed easing bias likely supported price to earnings (P/E) multiples and “risk-on” positioning. More recently, markets appeared increasingly rate-sensitive, with the decreased likelihood of an additional rate cut until March 2026.
• ‍Earnings and guidance: Corporate earnings remained strong quarter on quarter. Recent Q3 results reportedly saw over 80% of the S&P 500 beat earnings per share (EPS) expectations. For Q4, the estimated year-over-year earnings growth rate is 8.1%, despite ongoing concerns around import tariffs and potential margin pressure.
• ‍Index leadership and breadth: Returns were heavily influenced by mega-cap tech and AI beneficiaries, even as broader market breadth appeared less consistent at points through the year.
• ‍Policy headlines and volatility: Trade and tariff headlines drove sharp moves, particularly earlier in the year. Some investors pointed to the “TACO” trade, with rapid recoveries after policy proposals were softened. Over time, similar shocks appeared to have less impact as the market became somewhat desensitised.
• ‍Valuations and sensitivity: The forward 12-month P/E ratio for the S&P 500 is 22, above the 5-year average (20.0) and above the 10-year average (18.7). That gap kept valuation sensitivity, especially in AI-linked names, firmly in focus.

Current state

The S&P 500 is about 1% below record highs hit earlier in December. That could indicate the broader uptrend remains in place, with a move back toward the recent highs one possible scenario if momentum improves. Despite the recent retracement, the index remains above all key major moving averages (MA). The latest bounce followed lower than expected CPI numbers earlier this week, alongside continued, and to some, surprising optimism about what may come next.

What to watch in January

• ‍Q4 earnings from mid-January: Results and guidance may help clarify whether valuations are being supported by forward expectations.
• ‍AI narrative and positioning: With AI-linked mega-caps carrying a large share of market capitalisation, changes in sentiment or expectations could have an outsized impact on index performance.
• ‍US jobs and CPI data: The latest US jobs report reportedly points to the highest headline unemployment rate since 2021. Cooling inflation this week may keep markets alert to shifts in rate cut timing, particularly around the March decision.

S&P 500 daily chart

Major FX pairs

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AUD/USD

AUD/USD has been choppy in 2025. Since the “redemption day” drop in April, the move has looked more like a steady grind higher than a clean upside trend.

Key levels
Recent peaks in early September and mid-December highlight resistance near 0.6625. Support has been evident around 0.6425, where price bounced over the last month.

What is supporting the bounce
That support test coincided with stronger than expected jobs and inflation data, lifting expectations that the Reserve Bank of Australia (RBA) may raise rates during 2026 rather than cut again. The latest pullback looks contained so far, with buying interest already visible and price still above key longer-term moving averages.

What could drive a breakout
The pair remains range-bound, but the tilt is still constructive. If Chinese data stays firm, metals prices hold up, and the central bank outlook remains relatively hawkish, a break above resistance could gain more traction.

AUD/USD daily chart

EUR/USD

After early 2025 euro strength, EUR/USD has mostly consolidated since June in a roughly 270 pip range. This month tested 1.18 resistance, reaching highs not seen since September.

What price is doing now
The recent pullback still lacks strong downside conviction. Some technical analysts refer to the 1.17 area as a near-term reference level.

What could come next
If price holds 1.17 and buyers step back in, another push toward 1.18 is possible. One view is that the European Central Bank (ECB) could be less inclined to ease in 2026, which could be consistent with a firmer EUR/USD scenario. Broader analyst commentary also suggests the euro may stall rather than collapse against the US dollar, although outcomes remain data and policy dependent.

EUR/USD daily chart

USD/JPY

Year-to-date picture
USD/JPY is close to flat overall for the year. After US dollar weakness in Q1, the pair reversed higher and now sits just below resistance near 158.

Rates remain the main driver
Rate differentials still favour the US dollar. The Bank of Japan (BOJ) held steady for much of the period despite expectations it might act, and the recent rate increase was modest. Policy has only moved marginally away from zero.

What could shift the balance
Rate differentials remain a key influence. Without a clearer shift in BOJ policy, the JPY may find it difficult to sustain a rebound. Some market commentators cite 154.20 as a chart reference level.

USD/JPY daily chart

Markets have bounced back strongly this week. The S&P 500 is now just 1.5% from record highs, and the Nasdaq is recovering well following its pullback.

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Rate Cut Expectations

The main driver behind this rally was a shift in Federal Reserve rate cut expectations. Markets are currently pricing in a quarter-point rate cut for December, with only a 25% chance of another reduction in January. This week's economic data will be crucial in shaping expectations going into 2026.

Key Economic Data This Week

Several important data releases are scheduled for this week.  The PCE inflation data — the Fed's preferred inflation measure — for September will finally be released on Friday and could have the biggest impact on December and January rate decisions. The ADP jobs report and weekly jobless claims will also be released, while the non-farm payrolls report has been delayed again.

Global Manufacturing Snapshot

Today also kicks off a busy week of manufacturing data releases. Global PMI numbers are due across the board, including figures from the Eurozone, UK, Germany, and the US this evening. These reports will provide a critical snapshot of global economic health and could help reveal the impact of the US trade tariffs.

Gold Breaks Higher

Gold made a significant move on Friday, breaching the key $4,200 level after consolidating last week. The precious metal has followed through today, and the $4,400 level now looks achievable if buying pressure continues.

Bitcoin Under Pressure

Bitcoin has given up last week's modest gains and seen substantial selling pressure. A significant drop of about $4,000 occurred during Asian trading this morning — a notable decline for an Asia session. The key level to watch is $84,000, with potential support at $80,000 (the lowest level since March).

Market Insights

‍Watch Mike Smith's analysis of the week ahead in markets.

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Key Economic Events

‍Stay up to date with the key economic events for the week.

The decision to scale (increase the traded lot size of a specific EA) should be based on statistical evidence that indicates your EA has the potential to perform to certain expectations. 

Equal weight should be given to the decision to scale, as to the initial decision to deploy an EA. This guide provides an indicative approach on how to put together and action your scaling plan.

Before You Start Your Scaling Plan

Important: this should be an individual plan that is consistent with your personal trading objectives, your EA portfolio, and your personal financial situation (including account size).

We are going to use a starting lot of 0.10 per trade in the examples in this document —you want to adjust this based on your own risk tolerance.

Whatever your chosen lot size start point, EA scaling should be a pre-planned incremental approach, scaling stepwise based on performance metrics you are seeing in your live trading account.

You should also have assessed the current margin usage of your EA portfolio exposure to ensure that any scaling and related increased margin requirements are appropriate to the size of your account. 

Suggested Scaling Baseline Requirements

Scaling should only be performed when your EA is performing to what you deem to be a good standard. To make this judgment, you need to set some minimum performance standards.

The past performance of your EA is not a guarantee of future performance. If market conditions change, you must remain vigilant and continue to measure performance on an ongoing basis for every live EA you have.

You need to define the key metrics that are important to you. 

Two important metrics to include are:

• The number of trades: to provide some evidence of reliability 
• The period of time: to have had exposure to at least some variation in market conditions

Example of how you may lay your metrics out in a table:

Some may choose to include proximity to original expectations of other metrics, such as minimum win rate, average profit in winning trades, and average loss in those that go against you. 

It should only be after your metrics are met that lot scaling begins on any specific EA.

Lot Size Scaling Ladder

Below is an example of a performance-based scaling plan assuming a 0.10-lot baseline.

Again, this is indicative. It provides a framework with clear review dates and an approach that illustrates incremental scaling. You must still define a regime that is right for your specific trading objectives. 

Risk Guardrails

It is vital to keep an eye on your general account risks and have limits in place that guide your EA use.

Such limits must be constant across all stages of scaling and referenced beyond the risk of a single EA, but to your portfolio as a whole.:

Per-Trade Risk (Nominal)

Trade risk for any one trade should be seen in the context of account size and the dollar risk based on the risk parameters you have set for your EA. 

Specify a maximum percentage of the account balance — a $200 loss is more impactful on a $1000 account compared to a $10,000 account. 

Stick to what is right for you in terms of your tolerable risk level based on your trading objectives and financial situation. A common suggestion is a 1-2% risk of account equity per trade. 

Total Open Exposure

Specifying maximum exposure in the number of EAs open at any time and those that use the same asset class is important for overall portfolio risk management. 

There are tools you can use to monitor exposure risk generally, as well as those that can be used to indicate single asset exposure.

Margin Usage

It is always desirable that your set exit approaches and parameter levels are what your exits are based on. It should not be because your margin usage has meant you have moved into a margin call situation. 

Specify a minimum level to adhere to and make sure that your account is sufficiently funded. If volatility or slippage rises (e.g., news events or illiquid sessions), reduce lot size temporarily.

Scaling Psychology – Managing “Big Numbers”

As lot sizes rise, your emotions may respond accordingly when you see the larger dollar amounts that your EA is generating. 

If you are used to seeing an average profit of $100 and average loss of $50, and suddenly you are seeing significantly bigger numbers, it creates an emotional challenge where you may be tempted to do a “discretionary override”. 

Although there are situations, such as major market events, overexposure in a specific asset, or VPS or account system problems, where such intervention may be considered, generally this would distort the actual performance evaluation of your EA and is not encouraged (unless it is pre-planned).

The table below presents some of the generally accepted challenges and offers suggestions on how to manage them. 

Your Plan Into Action…

In practical terms, your scaling plan should have two components:

1. The key parameters for action on your chosen key metrics
2. Specified periodic review times to make your next scaling decision

This is not a race. Having systems in place facilitates creating the opportunity that scaling brings while still mitigating the risks.

The “Magnificent Seven” technology companies are expected to invest a combined $385 billion into AI by the end of 2025.

‍Microsoft is positioning itself as the platform leader. Nvidia dominates the underlying AI infra. Google leads in research. Meta is building open-source tech. Amazon – AI agents. Apple — on-device integration. And Tesla pioneering autonomous vehicles and robots.

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With such enormous sums pouring into AI, is this a winner-take-all game?

Or will each of the Mag Seven be able to thrive in the AI future?

Microsoft: The AI Everywhere Strategy

Microsoft has made one of the biggest bets on AI out of the Mag Seven — adopting the philosophy that AI should be everywhere.

Through its deep partnership with OpenAI, of which it is a 49% shareholder, the company has integrated GPT-5 across its entire ecosystem.

‍Key initiatives:

• GPT-5 integration across consumer, enterprise, and developer tools through Microsoft 365 Copilot, GitHub Copilot, and Azure AI Foundry
• Azure AI Foundry for unified AI development platform with model router technology
• Copilot ecosystem spanning productivity, coding, and enterprise applications with real-time model selection
• $100 billion projected AI infrastructure spending for 2025

Microsoft’s centrepiece is Copilot, which can now detect whether a prompt requires advanced reasoning and route to GPT-5's deeper reasoning model.

This (theoretically) means high-quality AI outputs become invisible infrastructure rather than a skill users need to learn.

However, this all-in bet on OpenAI does come with some risks. It is putting all its eggs in OpenAI's basket, tying its future success to a single partnership.

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Google: The Research Strategy

Google’s approach is to fund research to build the most intelligent models possible. This research-first strategy creates a pipeline from scientific discovery to commercial products — what it hopes will give it an edge in the AI race.

‍Key initiatives:

• Over 4 million developers building with Gemini 2.5 Pro and Flash
• Ironwood TPU offering 3,600 times better performance compared to Google’s first TPU
• AI search overviews reaching 2 billion monthly users across Google Search
• DeepMind breakthroughs: AlphaEvolve for algorithm discovery, Aeneas for ancient text interpretation, AlphaQubit for quantum error detection, and AI co-scientist systems

Google’s AI research branch, DeepMind, brings together two of the world's leading AI research labs — Google Brain and DeepMind — the former having invented the Transformer architecture that underpins almost all modern large language models.

The bet is that breakthrough research in areas like quantum computing, protein folding, and mathematical reasoning will translate into a competitive advantage for Google.

Today, we're introducing AlphaEarth Foundations from @GoogleDeepMind , an AI model that functions like a virtual satellite which helps scientists make informed decisions on critical issues like food security, deforestation, and water resources. AlphaEarth Foundations provides a… pic.twitter.com/L1rk2Z5DKk

— Google AI (@GoogleAI) July 30, 2025

Meta: The Open Source Strategy

Meta has made a somewhat contrarian bet in its approach to AI: giving away their tech for free. The company's Llama 4 models, including recently released Scout and Maverick, are the first natively multi-modal open-weight models available.

‍Key initiatives:

• Llama 4 Scout and Maverick - first open-weight natively multi-modal models
• AI Studio that enables the creation of hundreds of thousands of AI characters
• $65-72 billion projected AI infrastructure spending for 2025

This open-source strategy directly challenges the closed-source big players like GPT and Claude. By making AI models freely available, Meta is essentially commoditizing what competitors are trying to monetize. Meta's bet is that if AI models become commoditized, the real value will be in the infrastructure that sits on top. Meta's social platforms and massive user base give it a natural advantage if this eventuates.

Meta's recent quarter was also "the best example to date of AI having a tangible impact on revenue and earnings growth at scale," according to tech analyst Gene Munster.

However, it hasn’t been all smooth sailing for Meta. Their most anticipated release, Llama Behemoth, has all but been scrapped due to performance issues. And Meta is now rumored to be developing a closed-source Behemoth alternative, despite their open-source mantra.

Amazon: The AI Agent Strategy

Amazon’s strategy is to build the infrastructure for AI that can take actions — booking meetings, processing orders, managing workflows, and integrating with enterprise systems.

Rather than building the best AI model, Amazon has focused its efforts on becoming the platform where all AI models live.

‍Key initiatives:

• Amazon Bedrock offering 100+ foundation models from leading AI companies,  including OpenAI models.
• $100 million additional investment in AWS Generative AI Innovation Center for agentic AI development
• Amazon Bedrock AgentCore enabling deployment and scaling of AI agents with enterprise-grade security
• $118 billion projected AI infrastructure spending for 2025

The goal is to become the “orchestrator” that lets companies mix and match the best models for different tasks.

Amazon’s AgentCore will provide the underlying memory management, identity controls, and tool integration needed for these companies to deploy AI agents safely at scale.

This approach offers flexibility, but does carry some risks. Amazon is essentially positioning itself as the middleman for AI. If AI models become commoditized or if companies prefer direct relationships with AI providers, Amazon's systems could become redundant.

Nvidia: The Infra Strategy

Nvidia is the one selling the shovels for the AI gold rush. While others in the Mag Seven battle to build the best AI models and applications, Nvidia provides the fundamental computing infrastructure that makes all their efforts possible.

This hardware-first strategy means Nvidia wins regardless of which company ultimately dominates. As AI advances and models get larger, demand for Nvidia's chips only increases.

‍Key initiatives:

• Blackwell architecture achieving $11 billion in Q2 2025 revenue, the fastest product ramp in company history
• New chip roadmap: Blackwell Ultra (H2 2025), Vera Rubin (H2 2026), Rubin Ultra (H2 2027)
• Data center revenue reaching $35.6 billion in Q2, representing 91% of total company sales
• Manufacturing scale-up with 350 plants producing 1.5 million components for Blackwell chips

With an announced product roadmap of Blackwell Ultra (2025), Vera Rubin (2026), and Rubin Ultra (2027), Nvidia has created a system where the AI industry must continuously upgrade to Nvidia’s newest tech to stay competitive.

This also means that Nvidia, unlike the others in the Mag Seven, has almost no direct AI spending — it is the one selling, not buying.

However, Nvidia is not indestructible. The company recently halted its H20 chip production after the Chinese government effectively blocked the chip, which was intended as a workaround to U.S. export controls.

Apple: The On-Device Strategy

Apple's AI strategy is focused on privacy, integration, and user experience. Apple Intelligence, the AI system built into iOS, uses on-device processing and Private Cloud Compute to help ensure user data is protected when using AI.

‍Key initiatives:

• Apple Intelligence with multi-model on-device processing and Private Cloud Compute
• Enhanced Siri with natural language understanding and ChatGPT integration for complex queries
• Direct developer access to on-device foundation models, enabling offline AI capabilities
• $10-11 billion projected AI infrastructure spending for 2025

The drawback of this on-device approach is that it requires powerful hardware from the user's end.  Apple Intelligence can only run on devices with a minimum of 8GB RAM, creating a powerful upgrade cycle for Apple but excluding many existing users.

Tesla: The Robo Strategy

Tesla's AI strategy focuses on two moonshot applications: Full Self-Driving vehicles and humanoid robots.

This is the 'AI in the physical world' play. While others in the Mag Seven are focused on the digital side of AI, Tesla is building machines that use AI for physical operations.

‍Key initiatives:

• Plans for 5,000-10,000 Optimus robots in 2025, scaling to 50,000 in 2026
• Robotaxi service targeting availability to half the U.S. population by EOY 2025
• AI6 chip development with Samsung for unified training across vehicles, robots, and data centers
• $5 billion projected AI infrastructure spending for 2025

This play is exponentially harder to develop than digital AI, and the markets have reflected low confidence that Tesla can pull it off.

TSLA has been the worst-performing Mag Seven stock of 2025, down 18.37% in H1 2025.

However, if Tesla’s strategy is successful, it could be far more valuable than other AI plays. Robots and autonomous vehicles could perform actual labour worth trillions of dollars annually.

The $385 billion Question

The Mag Seven are starting to see real revenue come in from their AI investments. But they're pouring that money (and more) back into AI, betting that the boom is just getting started.

The platform players like Microsoft and Amazon are betting on becoming essential infrastructure. Nvidia’s play is to sell the underlying hardware to everyone. Google and Meta compete on capability and access. While Apple and Tesla target specific use cases.

The $385 billion question is which of the Magnificent Seven has bet the right way? Or will a new player rise and usurp the long-standing tech giants altogether?

‍You can access all Magnificent Seven stocks and thousands of other Share CFDs on GO Markets.