Big Tech Q&A: What investors are asking after earnings

Key points:

• AI momentum is real but uneven: Big Tech remains the backbone of the AI cycle, yet leadership is splitting between those monetising AI now and those still building capacity.
• Profits are high, valuations higher: Backlogs and earnings justify holding exposure; however, in our view, elevated valuations also increase the risk of a pull-back if growth expectations are not met, so investors should carefully weigh potential downside before adjusting positions.
• Stay invested, stay selective: While AI tailwinds remain strong, elevated valuations and execution risks mean returns could be more volatile, making diversification and clear risk limits truly essential.

After another round of blockbuster results from Big Tech, the same two questions are echoing across portfolios:

• Those who’ve ridden the rally from early 2023 are sitting on substantial gains and wondering if it’s time to lock in profits.
• Those still on the sidelines are feeling the pull of FOMO, questioning if they’ve missed the best entry point.

Both are fair concerns. The AI boom has pushed the “Magnificent” names to new highs, but under the surface, their stories have begun to diverge between companies monetising AI today and those still investing for tomorrow.

This Q&A unpacks what’s really changed after earnings, what’s priced in, and how investors can think about trimming, rotating, or holding their positions as Big Tech enters its next phase.

Q. All five giants beat expectations, so why did markets react so differently?

Because the numbers tell only part of the story. While all five companies — Microsoft, Amazon, Google, Apple, and Meta — benefited from AI momentum, they are at very different stages of turning that excitement into earnings.

Some firms are already generating substantial cash flow from AI-related businesses, while others are still scaling up or absorbing heavy infrastructure costs.

• Microsoft and Amazon are delivering cash-backed growth in cloud and AI services.
• Alphabet (Google) is translating AI adoption into new customers but still scaling profitability.
• Meta is spending heavily to build AI capacity, which clouds its near-term cash flow.
• Apple continues to deliver stable, service-led compounding, but its AI strategy is intentionally slower and more contained.

The divergence is healthy: it means Big Tech is no longer a single trade, but a set of distinct investment stories. That means investors finally have room to be selective by trimming exposure where valuations are full, or adding where visibility is strengthening.

Q. What exactly is an “AI backlog”, and why does it matter?

An AI backlog (or Remaining Performance Obligation, RPO) represents the value of cloud and AI service contracts already signed but not yet delivered. It’s a strong indicator of future revenue visibility, showing how much demand is already secured, regardless of short-term market swings.


Source: Company reports, Saxo. Data as of 3 Nov 2025. Past performance is not indicative of future results. Figures in USD unless stated otherwise.

A rising backlog signals that customers are locking in multi-year AI and cloud contracts.

Microsoft’s surge shows accelerating enterprise adoption, while Google’s steady climb reflects new workloads tied to AI training and data analytics. Amazon’s backlog growth, though more modest, underscores the depth and renewal strength of its client base.

For long-term investors, backlog matters more than quarterly beats — it tells you who already has future growth in the bag.

Q. Who’s spending the most on AI infrastructure, and how big is the gap?

AI investment has become a capital-intensive race. These are the latest annual spending plans based on company guidance and disclosures:


 Source: Company reports, Bloomberg, Saxo. Data as of 3 Nov 2025. Past performance is not indicative of future results. Figures in USD unless stated otherwise.

These numbers show where the balance lies:

Meta and Alphabet are leading the spending cycle, Microsoft and Amazon expanding capacity in lockstep with monetisation, and Apple remains disciplined, investing selectively within its ecosystem.

High capex isn’t a red flag, but it does raise volatility. For investors sitting on gains, it’s a cue to trim size, not conviction.

Q. Which companies are already monetising AI, and who’s still laying the groundwork?

While everyone is investing, the financial pay-off varies sharply. Monetisation separates today’s compounding from tomorrow’s potential.

 
Source: Company reports, Saxo. Data as of 3 Nov 2025. Past performance is not indicative of future results.

The early payoff is concentrated in just two names: Microsoft and Amazon.

• Microsoft is seeing Azure revenue accelerate, Copilot integration boost enterprise stickiness, and backlog growth confirm pricing power.
• Amazon’s AWS remains the most profitable of the three, funding broader group innovation.
• Google is gaining share, but profitability still lags.
• Meta’s investments are pre-emptive — training models and building data centres well ahead of monetisation.
• Apple, meanwhile, monetises indirectly, through ecosystem loyalty and higher-margin services.

The key distinction: some are monetising AI today, others are building for tomorrow.

Q. How do the cloud businesses of Microsoft, Amazon, and Google actually differ?

Each company dominates a different layer of the cloud stack — and understanding those differences helps explain their performance and prospects.

• Microsoft Azure sits deepest in the enterprise ecosystem. It integrates cloud with Office, GitHub, and AI tools like Copilot. Its +40% growth and $392B backlog show how sticky corporate contracts are becoming. Azure is where AI meets productivity.
• Amazon Web Services (AWS) remains the scale and profit leader. With $33B in quarterly revenue and $11B operating income, AWS funds much of Amazon’s innovation elsewhere. But its growth is slower (+20%) as enterprise customers optimise existing workloads before expanding again.
• Google Cloud is the challenger, growing +34% year-on-year with a $155B backlog. It is winning share among developers and AI-native businesses thanks to Tensor Processing Units (TPUs) and data analytics tools. Profitability is improving fast, and that’s what could drive re-rating from here.

In our view (forward-looking opinion), Microsoft is likely to offer relatively greater earnings visibility, Amazon stronger current profitability, and Google potential valuation upside.

Q. Where do Apple and Meta fit into all this?

In our opinion, Apple remains a 'quiet compounder'.  We believe its services revenue, which just hit a record high, could offset hardware slowdowns. The ecosystem is its moat, and the steady buyback program (over $110B in 2024 alone) rewards patience. Its AI rollout, through “Apple Intelligence,” will likely strengthen rather than disrupt existing products.

Meta is a different kind of story. It’s profitable, yes — but it’s entering a heavy investment cycle. The company’s AI push into recommendation engines and infrastructure will take time to monetize. Long-term believers see it as the next phase of digital engagement; skeptics see a risk of overspending.

Both companies offer stability of brand and user base, but with different time horizons: Apple for consistency, Meta for optionality.

Q. Could AI threaten Google’s ad business?

It could. Google’s AI Overviews summarize search results for users, reducing the need to click through — which may lower ad impressions and publisher traffic. So far, Google’s ad revenue continues to grow, but investors are watching whether AI cannibalizes the very cash engine funding its future.

This risk explains why Alphabet’s stock, while cheaper, also trades with a “show-me” discount. It must prove AI is additive, not erosive, to its core business.

Q. How do valuations compare today?

Source: Bloomberg, Saxo. Data as of 3 Nov 2025. Past performance is not indicative of future results.
 
Valuations tell a nuanced story.

• Amazon trades at a notable discount to its five-year average, suggesting its profitability and cash generation may not yet be fully appreciated.
• Meta is roughly in line with its historical average — reasonably valued if it can sustain earnings while investing in AI.
• Microsoft commands a slight premium, reflecting investors’ confidence in its execution and Azure visibility.
• Alphabet trades above its average, pricing in continued growth and margin expansion.
• Apple’s premium reflects stability and the enduring strength of its ecosystem rather than growth expectations.

In short: Microsoft and Apple trade on trust; Alphabet and Amazon on potential; Meta on skepticism.

Q. What are the biggest risks now?

• Microsoft: Power and chip constraints, margin compression
• Amazon: Slower enterprise cloud growth, competition on pricing
• Google: Search monetization risk, regulatory pressure
• Apple: China exposure, slower product cycle, AI lag
• Meta: High AI capex, regulatory scrutiny

Q. Should I take profits or reposition?

After such large gains, this is a sensible question, not a sign of doubt. Below are some considerations for investors. This information is provided for general discussion only and does not constitute investment advice. Investors should assess their individual circumstances or consult a qualified advisor. 

• If you’ve built strong profits: you may consider rebalancing rather than exiting. This could be done by trimming exposure in richly valued names, while keeping core holdings where visibility is the strongest and redeploying a portion into cash or dividend assets to smooth volatility.
• If you joined late or feel underexposed: short-term pullbacks could be opportunities, especially where valuations remain below historical averages, and AI monetisation is still in early innings.
• If you’re balanced: pairing one growth compounder with one AI growth lever could offer offer a diversified way to stay in the theme without concentration risk.

The key is position management, not prediction by staying exposed to AI’s long-term compounding while managing near-term exuberance.

Q. Did I miss the rally?

Much of the easy upside has already been captured. The next leg is about earnings delivery, not multiple expansion.

• For late entrants: the entry point may not be cheap, but structural drivers (AI adoption, cloud growth, energy transition) remain intact. Focus on staggered entry and accumulation on weakness rather than chasing peaks.
• For existing holders: gains can keep compounding if you own the right segments — such as the cash flow visibility in Microsoft and Amazon, or catch-up potential in Google.
• For cautious investors: thematic ETFs or baskets offer diversified exposure without single-stock timing risk.

The AI trade has shifted from “fear of missing out” to “fear of missing earnings.” There’s still opportunity, but now it rewards patience over speed.

Q. What are the key metrics to watch next quarter?

• Backlog conversion – how much of that booked revenue turns into cash.
• Capex discipline – whether spending stabilises as infrastructure scales.
• AI monetisation – revenue contribution from Copilot, Vertex, and AWS AI workloads.
• Power and chip supply – constraints that could delay delivery.

Those numbers will reveal who’s turning AI from narrative into compounding.

Q. So where does this leave investors now?

Each company has a distinct role to play in a balanced, long-term portfolio:

Final thought

Big Tech is entering its second act of the AI cycle — less hype, more execution.

The easy money from multiple expansion has been made; the next phase belongs to disciplined holders who manage exposure, not just conviction.

Their fundamentals are diverging — and that’s good news for investors who can distinguish between growth that earns its cost and growth that still needs to prove itself.

Microsoft and Amazon could remain the clearest cash engines, Alphabet and Meta may offer selective opportunity, and Apple could continue to anchor stability.

Whether you’re protecting profits or catching up, the right move isn’t all-in or all-out — it’s staying intentionally invested in the parts of Big Tech that still have earnings power ahead of them.