Key Takeaways

Most people think AI and quantum computing are essentially the same thing, which is futuristic technology that's hyped in headlines and driving significant stock market gains. It's certainly doing the last part, but you'd be wrong to confuse these technologies otherwise.

AI is a software capability that learns from data to automate or assist decisions, while quantum computing is hardware built on principles of quantum physics, designed to crunch calculations that would take traditional computers millennia to solve.12

What AI Actually Is

AI refers to algorithms, including machine learning, neural networks, and large language models (LLMs), that find patterns in big data to make predictions, classify information, or make recommendations based on those patterns.2

This includes popular applications like ChatGPT, product recommendations, fraud alerts, and self-driving features already widely available today. These systems run on traditional computers, using common hardware like CPUs and GPUs.

What Quantum Computing Actually Is

Instead of the 0s and 1s used in binary code, quantum computing is based on qubits (short for “quantum bits”), which can represent many possible states at once. This theoretically allows quantum machines to process vast numbers of potential solutions in parallel.1

If this were to occur, these computers would be orders of magnitude more powerful for specific tasks than even the most advanced supercomputers, such as simulating complex molecules or searching through massive search spaces. Meanwhile, as powerful quantum computers threaten to break current encryption, computer scientists are already working on post-quantum cryptography to ensure data security in the long term.3

Quantum devices are still limited and prone to errors today. But the long-term potential is enormous. Indeed, quantum computers are making progress, with qubit processors now able to vastly outperform classical systems—but still on very narrow, benchmark tasks. The promise is that quantum machines would eventually replace traditional computers, ushering in a new post-digital age.

Where the Two Meet

The intersection of quantum and AI is likely to take two parallel paths:4

• The first is the eventual use of quantum hardware to speed up or augment certain AI tasks, allowing models to consider far more options at once, search solution spaces faster, and tune themselves more quickly.
• The second would see current AI methods deployed to help build and control quantum systems—keeping these delicate machines stable, automatically adjusting settings, spotting glitches early, and generally helping the hardware function for longer stretches.

The quantum acceleration of AI tasks could lead to possible breakthroughs in medicine and biotech, materials science, weather modeling, finance, and logistics. These possibilities may be speculative, but early proofs of concept have been promising.5

Quantum Computing Explained: Definition, Uses, and Leading Examples

AI is already everywhere. You can chat with it in plain language, businesses use it automate some everyday tasks, and consumers allow it to personalize their experiences for many things online. Quantum computing is less visible—but could be at least as transformative. It could one day power breakthroughs in medicine, materials, green energy, and ultra-secure encryption.

Key Takeaways

In recent years, the so-called “Magnificent Seven”—Apple, Microsoft, Alphabet (Google), Amazon, Nvidia, Meta Platforms, and Tesla—have powered much of the market’s gains. What’s behind their outsized performance isn’t just hype—it’s a layered business model built on artificial intelligence, cloud computing, advertising, and recurring services.

Below, we break down the core growth engines that keep these companies at the top.

How AI Became the New Growth Story

Companies, including Nvidia, Microsoft, Alphabet, and Meta, are rapidly commercializing AI to strengthen every aspect of their businesses. For example, Nvidia’s data-center segment saw revenue climb dramatically, driven by demand for generative AI workloads and advanced computing infrastructure. As of Q3 2025, Nvidia saw record data center revenue of $51.2 billion, up 25% from Q2 2025 and up 66% from just one year ago.1

Meanwhile, Microsoft continues integrating AI throughout its Azure cloud platform and productivity tools, while Alphabet uses AI to optimize search relevance.23 Meta relies on AI for recommendation systems and more accurate ad targeting—improvements that have contributed directly to revenue growth.4

These companies benefit from foundational AI investments that scale across multiple products and services, allowing them to monetize the technology repeatedly.

Cloud Computing’s Steady Revenue Power

Cloud infrastructure remains a critical growth engine for Amazon, Microsoft, and Alphabet. Here are some key data points to explain further:

• Amazon Web Services (AWS) produced roughly $33 billion in revenue as of Q3 2025, representing a 20% year-over-year increase.5
• Microsoft’s Intelligent Cloud division—which includes Azure—generated roughly $30.9 billion in revenue as of Q3 2025, an increase of 40% year-over-year, beating expectations due to strong demand.6
• Meanwhile, Google Cloud services reported around $15.2 billion in revenue for Q3 2025, reflecting expanding adoption of AI-enhanced cloud tools.3

Across all three companies, cloud platforms are providing recurring, high-margin revenue tied to enterprise workloads, AI services, and data-heavy applications—making them foundational to long-term growth.

Ads Are Still Big Business

Digital advertising remains central to Alphabet, Meta, and Amazon. According to an April 2025 report from the Interactive Advertising Bureau (IAB), U.S. digital ad market spend overall was about $258.6 billion in 2024, a 15% year-over-year increase and the highest level seen since 2021.7

Alphabet and Meta continue to dominate global digital ad share thanks to their massive user bases and sophisticated AI-driven targeting tools.8 Meanwhile, Amazon has become one of the largest digital ad platforms that continues to grow at a double-digit pace by harnessing the power of AI and automation—Q3 2025 advertising revenue reached $17.7 billion, up 24% year-over-year.9

AI-enhanced ad systems help businesses measure performance, optimize campaigns, and increase conversions—reinforcing revenue strength for these three companies.

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Apple’s Strength Is Its Ecosystem

Apple’s advantage lies in its tightly connected ecosystem of hardware, software, and services—the company’s device base recently reached 2.35 billion active devices.10 Considering the sheer volume of devices, Apple has developed a massive audience for its services, such as the Apple One and iCloud+. Services revenue reached $109 billion in the 2025 fiscal year and has become the second-largest business segment, accounting for nearly a quarter of the company’s revenue.11

Services revenue has become a key stabilizer for Apple, offsetting fluctuations in hardware cycles. This recurring income stream—combined with strong brand loyalty and premium pricing—reinforces Apple’s long-term competitive positioning.

Tesla’s Growth Levers Beyond EVs

Tesla remains the most unconventional member of the Magnificent Seven. While electric vehicles account for the company’s revenue, Tesla also invests heavily in battery storage, solar panels, and autonomous driving technology. Its strategy centers on building a diversified platform of energy and mobility services that can scale over time.12

The company continues to position its autonomous driving capabilities and energy solutions as future revenue generators, which represent long-term opportunities for the EV giant.

The Bottom Line

The Magnificent Seven’s strength comes from diversified, scalable business engines—not just consumer demand or market sentiment. AI, cloud computing, digital advertising, massive ecosystems, and forward-looking investments in mobility and energy all contribute to their growth. These companies have developed multi-layered revenue models that reinforce one another, enabling them to stay ahead of competitors and maintain their position as the most influential companies in today’s market.

KEY TAKEAWAYS

NextEra Energy is raking in new deals to power AI data centers.

America's largest energy infrastructure developer on Monday said it struck agreements with Alphabet's (GOOGL) Google and Meta Platforms (META) to meet growing demand for energy to support AI data centers.12

NextEra (NEE) said it plans to work with Google to build out energy infrastructure for data center campuses across the United States. As part of the deal, NextEra will also use Google Cloud AI to support its own "digital transformation" and deployment of AI.

Separately, NextEra said Meta signed contracts for clean energy projects meant to help the tech giant meet its clean energy goals, as well as build out data center capacity.

Financial terms of the deals were not disclosed, though the energy provider also raised the lower end of its full-year profit forecast, and boosted its outlook for 2026, according to a regulatory filing Monday.3

NextEra said it now expects adjusted earnings per share of $3.62 to $3.70 for 2025, compared to $3.45 to $3.70 previously, and 2026 EPS of $3.92 to $4.02, up from an earlier forecast of $3.63 to $4.4

Shares of NextEra slipped 3% Monday amid broader market losses, while Alphabet slid 2% and Meta lost 1%. Still, NextEra shares have added about 12% and Meta has climbed roughly 14% in 2025 so far. Alphabet shares are up close to 70% year-to-date.

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Retirement is keeping Americans up at night. Almost 7 in 10 say financial uncertainty has made them feel depressed and anxious, up 8% from 2023, according to Northwestern Mutual's 2025 Planning and Progress Study.1 Meanwhile, 51% told surveyors they'll outlive their savings.

That anxiety is pushing people to seek help, as Americans are increasingly turning to human advisors and digital tools, including robo-advisors and AI-powered planning apps, to get their retirement on track.

Americans Are Testing AI—But Not Betting Their Retirement on It

The anxiety cuts deepest for younger Americans. Among Gen Z and Millennials, about 4 in 10 say they feel depressed or anxious about their finances on at least a weekly basis—up significantly from 2023.1

There's evidence that professional help works: three-quarters (76%) of Americans with a financial advisor describe their finances as "strong," compared with just 44% without one. But only about 27% of Americans work with a traditional advisor, as fees and balance requirements put them out of reach for many.2

That gap is driving experimentation. In a 2024 Ipsos/BMO poll, about 37% of Americans said they were already using AI to help them manage their money, most commonly to learn about personal finance, build budgets, or evaluate investment ideas.3

Yet almost two‑thirds in the same survey said AI is incapable of understanding how emotions impact financial decisions—exactly the kind of subtlety that matters for decisions around retirement. In other words, people seem willing to let an algorithm run the numbers, but want a human being to double-check a financial plan and have the ability to adjust or override it.

Where Americans Turn for Trust in Financial Advice

Even as AI use expands, most Americans still trust humans over machines, especially when it comes to personal finances. In the Northwestern Mutual survey, respondents were asked who they trusted more when it came to creating a retirement plan. Most (56%) chose human advisors. Just 13% chose AI. However, most respondents said they'd prefer to work with a human advisor who also uses AI.5

Digital financial tools aren't new—robo-advisors like Betterment and Wealthfront have been around for over a decade, offering lower-cost, algorithm-driven portfolio management. What's changed is the emergence of generative AI tools like ChatGPT, which can answer open-ended questions and simulate the back-and-forth of a conversation with a human advisor.

But generative AI provides new risks. Unlike a robo-advisor that follows a set algorithm, AI chatbots can misunderstand context or give advice that sounds confident but isn't personalized to your situation. For retirement planning, where the stakes are high and mistakes compound over decades, that's a genuine concern.

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Perhaps that's why, when it came to trusted sources of financial information, 42% of households turned to their bank or credit union in the prior year. By contrast, only about 3% of households reported using general AI chatbots or robo‑advisor apps.6 A 2024 J.D. Power survey similarly reported that only 27% of bank customers trust AI for financial information and advice, even as many expect it to make everyday banking more convenient in the coming years.7

In the end, most people seem to want a mix of both, as surveys show Americans prefer a hybrid model for financial advice—AI for speed and number-crunching, plus a human advisor for judgment, trust, and personalization.3

Here's how AI and human advisors compare: