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Recent earnings from major technology companies suggest the artificial intelligence (AI) narrative is evolving. What once centred on innovation and potential is now defined by execution, scale, and cost.
Meta, Microsoft, Tesla, and IBM are all investing heavily in AI, but their results show very different paths through the same cycle. Together, they offer a clearer picture of where AI stands today and what markets are beginning to prioritise.
From Experimentation to Industrialisation
The common thread across these earnings is the shift from testing AI capabilities to deploying them at scale. This transition comes with a price tag.
Capital expenditure (CapEX) is no longer optional. Infrastructure, data centres, and specialised chips have become the cost of staying competitive.
The S&P 500 crossed 7,000 points for the first time in January 2026, propelled by AI-driven investor optimism and expectations of strong tech earnings. Tech stocks now constitute nearly half of the index’s weight.
Markets are no longer impressed by ambition alone. They want evidence that AI can generate revenue, protect margins, or reshape long-term strategy.
Meta and Microsoft: Growth Comes at a Cost
Meta stock results highlight how AI can already enhance core businesses. The company reported Q4 revenue of $59.9 billion, up 24% year on year, with earnings per share of $8.88, comfortably beating expectations.
AI-driven improvements lifted ad impressions by 18%, reinforcing the effectiveness of its machine learning models in monetising attention.
The cost of that progress is rising. Meta lifted its 2026 CapEX guidance to between $115 billion and $135 billion, representing roughly a 73% increase from the midpoint of its 2025 outlook.
While Reality Labs continued to post a $6.0 billion quarterly loss, investors largely looked past it, focusing instead on AI-driven gains in the core advertising engine.
Microsoft delivered similarly strong top-line growth, with quarterly revenue of $81.3 billion, up 17% year-on-year. Microsoft Cloud revenue surpassed $50 billion for the first time in a single quarter, growing 26%, underlining the company’s scale advantage in enterprise AI adoption.
However, management acknowledged that sustained AI investment is beginning to weigh on profitability.
Operating margins are expected to dip slightly next quarter as spending remains elevated and the revenue mix shifts, illustrating the trade-off between leadership and near-term financial pressure.
Tesla: Repositioning Through AI
Tesla’s earnings offered a different perspective on AI investment. The company posted Q4 revenue of $24.9 billion, with adjusted earnings per share of $0.50, beating expectations despite a 16% drop in vehicle deliveries.
Margins improved rather than deteriorated. Total gross margin rose to 20.1%, the highest level in two years, driven by operational efficiency and regional mix rather than volume growth.
Tesla’s energy division emerged as a key bright spot, with revenue reaching $12.8 billion, up 26.6% year-on-year.
Rather than chasing near-term vehicle growth, Tesla continues to frame AI and robotics as its long-term pivot. Management confirmed plans to expand robotaxi operations in 2026 and redirected $2 billion of investment toward its AI venture, xAI.
CapEx for 2026 is expected to exceed $20 billion, largely to support AI infrastructure and autonomous platforms.
IBM: The Quiet Beneficiary
IBM stood out byshowing AI demand that is already translating into revenue. The company reported Q4 revenue of $19.7 billion, up 12% year-on-year, prompting shares to rise 8% in after-hours trading.
More importantly, IBM’s AI book of business now exceeds $12.5 billion, offering clear evidence that enterprise clients are moving beyond experimentation and into implementation. Infrastructure revenue rose 21%, driven by the next-generation mainframe cycle, while software revenue grew 14%, reinforcing the scalability of its AI-enabled offerings.
Looking ahead, IBM guided for 5% or higher revenue growth in 2026, alongside an additional $1 billion in free cash flow, positioning the company as a disciplined beneficiary of the AI cycle rather than a capital-intensive outlier.
The AI Investment Landscape
Firms such as IBM and Meta stock have benefitted from clearer paths to monetisation, while others face closer scrutiny as spending accelerates ahead of visible revenue returns.
Despite these concerns, momentum across the AI hardware ecosystem remains a powerful signal. The underlying demand environment continues to expand, suggesting that the sector’s ceiling is still rising rather than closing in.
Nvidia announced a $2 billion investment in CoreWeave to expand AI data centre capacity, making it the second-largest shareholder in the firm and accelerating AI build-out.
Although Nvidia does not report until later in the quarter, its recent trajectory reinforces this view. The company is moving faster than the market expected to defend its dominant market share, already marketing its next-generation Vera Rubin platform to maintain distance from competitors.
Beyond Big Tech, Nvidia is also broadening its customer base by securing sovereign AI infrastructure deals across regions such as Saudi Arabia, South Korea, and Taiwan.
This shift matters. It suggests that AI demand is no longer confined to corporate investment cycles. Instead, it is becoming embedded in national infrastructure planning, raising the potential floor for long-term demand across the sector.
Key Implications and What Markets May Focus on Next
As earnings season continues, investor attention is narrowing. Capital intensity, margin discipline, and revenue quality are becoming as important as headline growth.
Companies guiding higher CapExwithout corresponding acceleration in cloud, software, or subscription income may face scepticism, even when results exceed expectations. Meanwhile, earnings driven by scalable, high-margin software integration continue to attract more durable market support.
As AI investment matures, the distinction between costly ambition and profitable execution is becoming clearer.
