For six decades, billionaire Warren Buffett has been dazzling Wall Street with his investing prowess. Though his company, Berkshire Hathaway (BRK.A -0.63%) (BRK.B -0.64%), hasn’t outperformed the benchmark S&P 500 every year since 1965, he’s nearly doubled the average annual total return of this broad-based index, including dividends, spanning 60 years.

For some investors, riding the Oracle of Omaha’s coattails and mirroring his trading activity has been a pathway to long-term riches. Historically, this has meant buying time-tested businesses in the financial or consumer staples sectors.

But you might be surprised to learn that even 95-year-old Warren Buffett, who’s set to retire at the end of the year and has, by his own admission, never been particularly tech-savvy, is invested heavily in the evolution of artificial intelligence (AI).

With AI, software and systems are given the capacity to make split-second decisions without human oversight or intervention. These systems may also have the ability to learn over time, which can make them more efficient at their assigned tasks. In Sizing the Prize, the analysts at PwC pegged this global addressable opportunity for artificial intelligence at $15.7 trillion by 2030.

While most brand-name businesses are incorporating AI solutions in some way or another (e.g., assisting with supply chain management), there are only two AI stocks in Berkshire Hathaway’s $302 billion investment portfolio whose future growth prospects are highly dependent on AI investments — and they comprise a whopping $68 billion of the invested assets Warren Buffett oversees.

Apple: $65.3 billion of invested assets

Long before artificial intelligence became the hottest thing since sliced bread on Wall Street, Apple (AAPL 1.82%) was incorporating this technology into its flagship iPhone. Predictive text and typing suggestions have been a staple in iPhone for more than a decade, and voice assistant Siri was initially introduced in early 2010. Though Apple might not be thought of as a current AI leader, it’s been a pioneer of AI applications for more than a decade.

In June 2024, Apple unveiled what it dubbed “Apple Intelligence” at the Worldwide Developers Conference. This is effectively the umbrella of Apple’s AI ambitions. It incorporates more interactive responses from Siri, as well as powers health monitoring, Face ID, and various intelligent writing and image tools. Apple Intelligence is expected to play a key role in reigniting the growth engine for iPhone and the company’s other physical devices.

As of midday on Sept. 12, Apple accounted for more than $65 billion of Berkshire Hathaway’s invested assets.

However, Buffett’s fascination with Apple goes beyond artificial intelligence. Aside from checking all the usual boxes he looks for in a long-term investment, Apple sports the greatest share repurchase program on the planet. Since initiating a buyback program in 2013, it’s repurchased over $796 billion of its own stock and reduced its outstanding share count by almost 44%. There’s no question that this aggressive buyback program has had a positive impact on its earnings per share.

Furthermore, Berkshire’s billionaire boss has a keen understanding of consumer buying habits. Apple’s customer base has demonstrated incredibly brand loyalty. While physical device sales have lagged in recent years, demand for Apple’s higher-margin subscription services has grown considerably.

Image source: Amazon.

Amazon: $2.3 billion of invested assets

The other AI stock Warren Buffett has a meaningful wager on is Amazon (AMZN -0.74%), which accounts for about $2.3 billion of Berkshire Hathaway’s invested assets.

Most people are familiar with Amazon because of its world-leading online marketplace. Though online retail sales account for a good chunk of Amazon’s revenue, the margins associated with retail sales are low. Nevertheless, I’m fairly certain Buffett can appreciate Amazon’s sustainable moat in e-commerce, even if the margins aren’t great.

Amazon’s incorporation of AI has almost everything to do with its rapidly growing cloud infrastructure platform, Amazon Web Services (AWS). Based on second-quarter estimates from Canalys, AWS corralled 32% of worldwide cloud infrastructure service spend.

AWS is allowing its users access to generative AI solutions, as well as the ability to build and train large language models. This helps businesses customize these solutions to fit their needs. The expectation is for AI to accelerate AWSs already impressive growth rate and build on its $123 billion annual sales run-rate, as of the June-ended quarter.

However, AWS isn’t the only ancillary operating segment generating big-time margins for Amazon. Subscription services and advertising services have also been growing by a steady double-digit percentage. Exclusive content deals with the National Football League (NFL) and National Basketball Association (NBA) have likely boosted Prime subscriptions and Amazon’s subscription pricing power.

Meanwhile, Amazon is attracting billons of monthly visitors between its online marketplace and its growing content/streaming library. With few social platforms offering as many eyeballs as Amazon, it’s had little trouble commanding strong ad-pricing power.

Considering how important AWS is to Amazon’s future cash flow and operating income, artificial intelligence is foundational to it success — as well as the success of Berkshire Hathaway’s investment in the company.

Three key areas for AI deployment

In this context, there are three areas where AI can help organizations bridge cultural gaps and transcend operational constraints by focusing on amplifying human qualities. The following three brief cases illustrate how AI can:

• Scale empathy in customer interactions
• Dissolve knowledge silos within organizations
• Support service delivery across linguistic and cultural boundaries

The pattern that emerges from these examples is clear: AI is at its most powerful not when it replaces humans but when it amplifies human connection.

1] Scaling empathy by bridging interpersonal divides

Many organizations build their service models to optimize cost efficiency and maximize throughput. Hitting these targets often means using strategies that consumers have come to dread: offshoring contact centers or replacing humans entirely with automated systems. Over time, this kind of approach reshapes both organizational culture and customer expectations, making empathy feel like a luxury rather than a standard. The consequences of these attitude shifts are very real: according to TCN’s 2024 survey, nearly two-thirds (63%) of Americans say they’re likely to abandon a brand after a single poor service experience – a nearly 50% increase over the past four years. At the same time, consumer expectations for empathy and responsiveness are rising. In most narratives about “the rise of the machines,” AI is the villain in these kinds of situations, responsible for accelerating the move away from empathy and connection. Yet the truth is that, when AI is implemented thoughtfully, it can help bridge this gap by supporting warmer and more personalized customer experiences.

Here are two live examples of how AI can boost rather than dilute feelings of empathy and connection.

• AI-powered contact center platforms like Genesys provide agents with on-screen hints about customer tone, journey stage, and emotional context as a call unfolds, then suggest phrasing for responses. On the surface, this is a technical solution to improve efficiency and global staffing flexibility. But its deeper value lies in its ability to help humans tailor responses to provide personalized customer engagement, thus scaling the emotional intelligence embedded in their customer interactions.
• AI can be unexpectedly effective at scaling empathy even in high-stakes settings like healthcare. The shift towards a “digital front door” for healthcare encounters in the US presents physicians with an enormous challenge: tens of thousands of patient messages arriving via Electronic Health Record inboxes every day. Many require responses that not only contain medically accurate information but that are also emotionally nuanced. A recent study from NYU found that AI-generated responses to patient messages were rated as more empathetic than those written by physicians, scoring higher on warmth, tone, and relational language. While not always as clinically precise, the AI replies were more likely to convey positivity and build connections. This suggests a powerful new role for generative tools. Instead of impersonal templated responses or terse replies from overburdened healthcare providers, AI can deliver personalized responses, relieving cognitive load on doctors while reinforcing a culture of compassion.