Artificial intelligence (AI) is everywhere in the business world these days. There are plenty of companies using AI, just as there are investors looking to capitalize on the opportunities with the new technology.
Anyone who's used ChatGPT or other new AI applications knows that there are many opportunities to leverage artificial intelligence. AI systems can communicate with customers, replace human labor, process large amounts of data, and solve difficult problems.
In this article, we'll explore how companies are taking advantage of AI and the wide variety of ways they're doing so.
Artificial Intelligence
| Name and ticker | Market cap | Dividend yield | Industry |
|---|---|---|---|
| Amazon (NASDAQ:AMZN) | $2.5 trillion | 0.00% | Multiline Retail |
| Meta Platforms (NASDAQ:META) | $1.6 trillion | 0.34% | Interactive Media and Services |
| Tesla (NASDAQ:TSLA) | $1.5 trillion | 0.00% | Automobiles |
| Upstart (NASDAQ:UPST) | $4.5 billion | 0.00% | Consumer Finance |
| Netflix (NASDAQ:NFLX) | $404.6 billion | 0.00% | Entertainment |
| Alphabet (NASDAQ:GOOGL) | $4.1 trillion | 0.25% | Interactive Media and Services |
| JPMorgan Chase (NYSE:JPM) | $838.1 billion | 1.88% | Banks |
| Boeing (NYSE:BA) | $190.0 billion | 0.00% | Aerospace and Defense |
| Johnson & Johnson (NYSE:JNJ) | $526.6 billion | 2.35% | Pharmaceuticals |
| ExxonMobil (NYSE:XOM) | $549.1 billion | 3.07% | Oil, Gas and Consumable Fuels |
Ten companies leveraging AI
1. Amazon
NASDAQ: AMZN
Key Data Points
Few companies are involved in as many industries as Amazon (AMZN -2.47%), including e-commerce, cloud computing, logistics, voice-activated technology, and even autonomous vehicles. It shouldn't come as a surprise that Amazon is also using AI in a wide range of ways.
For example, Amazon uses artificial intelligence to analyze images and videos to improve product listings and recommendations. It uses AI to make its supply chain more efficient as well, including forecasting demand, optimizing inventory levels, and routing orders efficiently. It's making voice assistant Alexa more conversational, having recently released Alexa+, and it's even aiming to use autonomous mobility robots in its warehouses.
Amazon Go, its chain of cashier-less "Just Walk Out" stores, is a good example of real-world AI. The stores use computer vision and deep learning algorithms to automatically charge customers based on what they take.
E-commerce
2. Meta Platforms
NASDAQ: META
Key Data Points
Another tech giant that has long been harnessing the power of AI is Meta Platforms (META -2.47%), best known as a social media titan through its ownership of Facebook, Instagram, and WhatsApp.
The company uses AI for recommendation algorithms. When you go on Facebook or Instagram, the accounts it suggests that you follow or the stories it chooses to show you are based on AI.
Similarly, it uses AI to recognize content like nudity or hate speech. More recently, the company has applied AI to features like chatbots, virtual assistants, and real-time translation.
CEO Mark Zuckerberg also laid out a compelling vision for generative AI, which can handle entire ad campaigns, including creative, starting with just a budget and objective. While Meta has yet to implement that, it shows the potential of the technology and the company's ambitious plans.
The company is also harnessing the power of AI in smart devices like glasses, in a partnership with Ray-Ban, and its Meta Quest VR headset.
Meta AI, the company's chatbot, is also among the most-used AI chatbots in the world.
3. Tesla
NASDAQ: TSLA
Key Data Points
4. Upstart
NASDAQ: UPST
Key Data Points
5. Netflix
NASDAQ: NFLX
Key Data Points
Machine Learning
6. Alphabet
NASDAQ: GOOGL
Key Data Points
7. JPMorgan Chase
NYSE: JPM
Key Data Points
8. Boeing
NYSE: BA
Key Data Points
9. Johnson & Johnson
NYSE: JNJ
Key Data Points
10. ExxonMobil
NYSE: XOM
Key Data Points
Key applications of AI
There are a lot of ways that companies are using AI. Let's review some of the major ones.
- Machine learning: Machine learning is behind everything from recommendation algorithms to image recognition. It's a core function of autonomous vehicles.
- Autonomous vehicles: Autonomous vehicles have the potential to be the most disruptive form of AI. If the technology goes mainstream, it would mean a transformation in transportation and could lead to millions of drivers losing their jobs.
- Robotics: Robotics is another cornerstone application of AI. While you might think of Tesla's Optimus as a prime example of AI in robotics, there are also more basic robots, such as the ones Amazon uses to move packages around its warehouses.
- Fraud detection: For banks and other financial companies, fraud detection plays a significant role in how they use AI. AI is skilled at picking up and identifying patterns that are often the sign of fraud.
- Generative AI: The technology that kicked off the AI boom is also among the most disruptive forms of AI. Generative AI is mostly thought of as online chatbots like ChatGPT, but it includes image generation, video generation, and other forms of generated content.
- Agentic AI: Agentic AI may be the next step beyond generative AI, involving using AI agents to perform tasks, often through chatbots, without human assistance.
What's next for AI?
As you can see from the list above, the biggest companies in the world are turning to artificial intelligence to cut costs and work more efficiently, but they're not alone.
AI is being embraced across the business world by small and medium-sized businesses as well, since its benefits can help businesses of any size.
Staying competitive is crucial in any industry, which means that companies are likely to look for more ways to take advantage of AI. Its ability to cut costs and solve problems that humans can't swiftly solve can give these companies a competitive advantage.
Given that hundreds of billions of dollars are being poured into AI annually, we're likely to see AI advance rapidly and become a greater part of day-to-day business in the coming years.
AI is becoming a bigger part of software, and investors should expect to see AI agents play a greater role in software, allowing businesses to gain insights more efficiently and quickly.
In physical AI, we're likely to see advances in areas like autonomous vehicles and robotics, and AVs can go mainstream one day.
Challenges of utilizing AI in the business world
While AI is valuable in a number of ways, it can also present challenges for businesses.
- AI is expensive: We're still in the expansion or "land grab" phase of AI, with companies rapidly opening data centers and spending billions of dollars to do so. That means both hardware and software companies are going to have to pay for the AI capabilities that are currently being built out.
- Privacy concerns: There is a long history of AI raising privacy issues. For instance, Amazon's facial recognition tool, Rekognition, was the focus of much controversy when it rolled out to police.
- Workforce disruption: AI is already changing the workforce as entry-level coding jobs are becoming much harder to find, a sign that work is being replaced by AI. We'll likely see the new technology disrupt other jobs in the coming years.
- Misinformation: Generative AI tools like ChatGPT and Google's AI Overviews are known for "hallucinating" at times, or making up facts. It's important for AI users to double-check information from chatbots with verifiable sources.
Related investing topics
How many companies use AI?
AI adoption is growing rapidly, and the launch of ChatGPT in November 2022 was a pivotal moment, showing how powerful AI had become. According to research from Stanford University, 78% of organizations surveyed were using AI in 2024, up from 55% in 2023.
Still, many companies have not deployed it across the business. Almost two-thirds of respondents to a McKinsey survey said they had yet to scale it, meaning they were still in the experimentation and piloting phase.
AI is still relatively new. At this stage, businesses seem to know that it's important, but don't quite know how to leverage it. A Massachusetts Institute of Technology (MIT) report said that 95% of generative AI pilots are failing, showing that there's still a gap between available technologies like AI agents and how they're being implemented.
FAQ
About the Author
