The rise of artificial intelligence (AI) has the potential to be one of the most significant developments in human history. Today's machines are already getting better at interpreting data, recognizing patterns, and finding more efficient ways to carry out tasks. And leading tech companies are hard at work on new breakthroughs that could dwarf what's been accomplished so far.
There are tremendous incentives for achieving and maintaining a leadership position in the field, and investors who back its top players stand to see huge rewards over the long term. Before getting into individual stocks that have the potential to be winners in artificial intelligence, it's worth establishing some concepts and trends in order to better understand why AI has such big potential. That will put you in position to identify and understand investment opportunities in the space.
What is artificial intelligence?
Artificial intelligence involves the use of algorithms that guide machine behavior to solve problems in a way that is smart or humanlike. Within the broader category of AI, there are also a range of specialized sub-categories.
- Machine learning
Machine learning is a branch of AI focused around the idea that computer algorithms can recognize patterns and "learn," continuing to improve the more data they are fed. Whereas the broader term "artificial intelligence" refers to systems that can produce smart results in a variety of situations, "machine learning" refers to systems that can infer from experience and adapt.
- Neural networks
Neural networks are algorithms of many densely interconnected processing nodes that have been inspired by the human brain. They are defined initially without any specific operating rules, instead inferring rules and connections through pattern recognition.
- Deep learning
Deep learning is a subcategory of machine learning that uses neural networks to analyze a set of data along a wide variety of different dimensions, identifying patterns, and stacking these patterns on top of one another to create categories that can be used for classification. For example, a deep learning AI may be able to look at a collection of photographs without being given additional guiding data and identify people as being a distinct category from their environment or faces as a distinct part of a person.
How big is the AI opportunity?
While there's no universally standardized means of measuring the value of the AI market or its potential, there are plenty of estimates suggesting that huge value will be created directly and unlocked indirectly with the technology. A report from PricewaterhouseCoopers (PwC) estimates that artificial-intelligence technology will lead to improvements in labor productivity, product value, and consumption that go on to create $15.7 trillion in global annual gross domestic product (GDP) by 2030.
For comparison, the U.S. is the world's largest economy and posted an annual GDP of roughly $20.5 trillion in 2018, according to the International Monetary Fund. Meanwhile, China had a GDP of roughly $13.4 trillion for the year.
Admittedly, the PwC forecast takes into account some of the farthest-reaching impacts of AI, so it's also advisable to look at projections that are narrower in focus. A report from MarketsandMarkets estimates that the sales generated from hardware, software, and services directly related to AI categories including machine learning, natural language processing, context-aware computing, and machine vision will rise from $21.46 billion in 2018 to $190.61 billion in 2025 -- representing a compound annual growth rate of 36.6%.
Estimates can be used to get a rough idea of what the future of the broader AI market or its subsections might look like, but individual projections and figures are probably less important than the overall picture painted by the range of estimates suggesting huge growth potential in the space. The AI revolution is already underway. Its progression will likely continue to accelerate and have increasing impact. Leading businesses in the space stand to see massive rewards if they establish and maintain success in the field.
Why is machine learning such a big deal?
The functionality of computers has historically relied on the pre-defined instructions fed to them. Machines depend on instructions, or algorithms, in order to function. Lines of code are given to a device or application, and, in turn, the machine executes the functions strictly defined by that code. This still describes most of the computing systems that are in use today, but there are examples of machine-learning technology already in use.
Here's a quote from machine-learning researcher Pedro Domingos' acclaimed book on artificial intelligence The Master Algorithm that could help put the differences between traditional computing and machine learning into perspective:
Computers aren't supposed to be creative; they're supposed to do what you tell them to. If what you tell them to do is be creative, you get machine learning. A learning algorithm is like a master craftsman: every one of its productions is different and exquisitely tailored to the customer's needs. But instead of turning stone into masonry or gold into jewelry, learners turn data into algorithms. And the more data they have, the more intricate the algorithms can be.
Machine learning revolves around accumulating data that can be fed into an algorithm in order to detect patterns and make inferences that will shape the evolution of a new algorithm. A machine or algorithm that is able to improve itself when presented with new data has the potential to continue evolving and become increasingly efficient at a rapid rate. As such, the companies that establish early leadership in artificial intelligence have the potential to quickly establish advantages that will be difficult for competitors to overcome.
Today's uses hint at tomorrow's potential
From the news stories showing up in your social media feeds to the pages returned by a search engine query, the results are typically tailored according to your previous queries and net activity. AI algorithms are already shaping experiences at the consumer level. When you interact with these systems, you are teaching machines things about you -- who you like to talk to, what you want to see, and other dimensions. The quality of your user experience hinges largely on how well a given algorithm has identified relevant data about you and adapted its responses.
Top AI trends to watch
Uses for AI extend far beyond search engines and social media platforms. Advancements in AI-powered technology could have huge implications for the healthcare field, with the potential for algorithms to dramatically expedite analysis of patient histories and, in some cases, offer predictive diagnoses.
Artificial intelligence has the capacity to dramatically improve human quality of life by recognizing the patterns in data that are most valuable, and the companies at the top of the AI technology hierarchy stand to deliver tremendous stock performance if they can turn that opportunity into reality. Paying attention to big trends in the AI space can help investors estimate where the market might wind up and have you better positioned to select winners in the space. Investors should keep an eye on the tech trends detailed below and have an understanding of which companies are leading them.
Governments partnering with companies to secure leadership in AI
Artificial intelligence's incredible potential means that world governments have crucial interests in securing an edge over geopolitical rivals in the space, and advanced AI will be very important for cybersecurity at both the corporate and governmental levels. This dynamic is driving increased collaboration between technology leaders and government agencies, and it's also causing countries to be more protective of their technology assets and data.
Tensions created by the new technological arms race are evident in the trade war between the U.S. and China, with the desire to secure leadership in crucial fields like AI and 5G internet representing a fundamental backdrop for the disputes between the two countries. The significance of the global competition for supremacy in artificial intelligence will likely foster close relationships between governments and leading companies in the space. Collaborations between private businesses and state entities will have a big impact on the progression of AI-dependent fields like the Internet of Things and cybersecurity.
The data boom's role in powering the progression of artificial intelligence
Valuable data is the key to building and improving artificial intelligence systems. Data can be thought of as the collection of materials for building artificial intelligence systems, while AI is the specified machine that you are trying to build. Not every bit of material will be useful, and huge portions of it may not be, but having more high-quality material at your disposal stands to greatly increase the quality of your machine.
Research firm IDC estimates that the total size of all the world's digital data will have seen a tenfold increase from 2017 to 2025. As mobile computing technology becomes increasingly ubiquitous across the globe, more and more high-definition video is uploaded to the net, and the prevalence of machine-to-machine communication increases, there will be an explosion of new data that can be fed into AI systems to improve algorithms.
Machine-vision advancements driving big technological leaps
AI-powered machine-vision technology is at the heart of a wide range of important technology projects including facial recognition, autonomous vehicles, and robotics-driven manufacturing. The vast majority of new data created over the next decade will come from videos and images, and that bodes well for advancements in these fields.
High-quality cameras and other forms of visual-sensor technology are becoming more widely available thanks to technological improvements and declining costs. Improved hardware for collecting and processing visual data will pave the way for more powerful algorithms that can make better sense of the physical world and generate insights that inform more-advanced, machine-driven reactions.
Important metrics for evaluating AI stocks
Having a qualitative understanding of artificial intelligence and the potential improvements and market opportunities it could create will put you on track to find quality investments in the space, but it's also important to have some quantitative tools at your disposal. Even great companies can be bad investments if you buy their stocks at too high a price, and having an understanding of the following performance and valuation metrics will put you in a better position to select AI stocks with strong return potential.
When you buy stock in a company, you're buying a share of that company's business and assets. That means that the amount of profit that a company is generating will tend to be one of the most important factors in determining the performance of your investment. Earnings growth is a comparison of the amount of profit generated across two reporting periods, and it's calculated by taking the amount that earnings have increased from one period to another and then dividing that value by the earnings from the starting point of your comparison.
Sometimes investments in big projects like AI will mean that a company's earnings growth slows or even slips into the negative, but you'll generally want to see that a stock's earnings are on an upward trajectory. The faster a company is growing its earnings, the faster it will have generated enough profit to equal and exceed the price at which you purchased shares, and successful AI projects should eventually turn into a substantial earnings-growth catalyst.
Sales growth is calculated by selecting two equivalent periods of time, determining how much sales have increased between the periods, and then dividing the amount of the increase by the sales figure at the starting point of your comparison. For example, if a company recorded $1 billion in revenue in 2018 and $1.5 billion in 2019, you would subtract $1 billion from $1.5 billion to get an increase figure of $500 million. You would then divide the $500 million figure by $1 billion to get 0.5 -- or a 50% growth rate.
Companies won't always break out specific sales figures for their artificial-intelligence projects. In many cases, the fruits of AI initiatives will be incorporated across multiple business segments of the business. Still, it's a good idea to keep track of sales momentum when you are making investments in the AI space.
If a company does break out specific figures for an AI-focused segment of the business, that's something worth paying attention to while also evaluating the overall sales trends at the business. If it doesn't break out AI-specific sales data, evaluating overall revenue momentum should still provide a valuable indicator about the demand for the company's products
Price-to-earnings ratio (P/E)
The P/E ratio is one of the most helpful and widely used tools for analyzing stock valuations. It's calculated by taking a company's share price and dividing it by its earnings across a twelve-month period. The P/E value can be thought of as a representation of how many years of earnings at that level would be needed to generate profits that added up to the share price at the time that you bought the stock.
Investors can compare a stock's P/E ratio to other companies within the same industry, the average P/E value of that industry, or against the broader market. A lower P/E value can indicate that a stock is undervalued, but you should also evaluate the rate at which a stock's earnings are increasing because this also determines how quickly your stock will match and exceed the price at which you bought shares.
Price-to-earnings-growth ratio (PEG)
Companies that are growing faster will tend to have higher P/E ratios because investors are willing to pay more for a stock if they have the expectation that the profits it's generating will continue increasing at a rapid pace. The PEG ratio measures the relationship between a company's price-to-earnings multiple and its earnings growth rate, and it's calculated by dividing the P/E ratio by the percentage rate at which earnings have increased (or are expected to increase) over a twelve-month period.
A PEG ratio that is lower than one can indicate that a stock is being undervalued by the market because it suggests that the rate of earnings growth is not fully reflected in the company's share price. However, investors also have to keep in mind that earnings can be irregular, and investments in initiatives like AI can mean that businesses see a reduction in near-term earnings in order to create the potential for greater profits over the long term.
Price-to-sales (P/S) ratio
Some artificial-intelligence stocks won't be regularly profitable, or they might be posting such small profits as to make the P/E ratio relatively unreliable as a valuation tool. In these instances, it can be helpful to measure a company's valuation in relation to the amount of revenue that it is generating.
The P/S ratio is calculated by dividing a company's share price by its sales per share across an annual period. The P/S ratio can also be calculated by dividing the company's market capitalization by its total sales over an annual period.
Companies leading the charge in AI
As the PricewaterhouseCoopers target for $15.7 trillion in global economic value being generated from the effects of artificial intelligence in 2030 suggests, there are no shortage of businesses that stand to benefit from the advancement of AI technology. As with the internet, the far-reaching effects of AI mean that nearly every industry under the sun will be affected in some manner. However, the big winners might be a fairly concentrated group.
Developing AI technology is capital and resource intensive, and the evolution of advanced deep-learning system hinges on access to massive troves of fresh data. As a result, the companies at the forefront of this revolutionary tech push tend to be tech giants with deep pockets and pre-existing business positions that have helped springboard their artificial-intelligence ventures.
Alphabet's (NASDAQ:GOOG)(NASDAQ:GOOGL) position in the AI space is one of the most compelling reasons to invest in the stock. In addition to its DeepMind lab dedicated to artificial intelligence research and applications, the company has a wealth of other businesses and assets that make it likely to be a long-term leader in AI. Its Google division has long dominated the search-engine industry, and being at the center of so much internet querying and communication gives the company access to an incredible amount of valuable information.
New data is a crucial component to powering advances in machine intelligence, and being able to feed in huge amounts of information for processing is essential for creating improved algorithms. Platforms like YouTube, Gmail, and the Google Drive suite also generate lots of data that can be fed into machine-learning algorithms.
Alphabet's deep pockets, data resources, and strength in AI have also helped the company to position itself as an early leader in self-driving cars. The tech giant's Waymo subsidiary is currently the only American unit that is testing Level 4 driverless vehicles on people who are not paid testers or employees. Autonomous vehicles will be huge data generators, with some estimates suggesting that a single self-driving car would generate over two million gigabytes of data across a year's worth of average driving time.
In addition to its namesake online-retail marketplace, Amazon.com (NASDAQ:AMZN) is also the leading provider of cloud computing services. The company has used its head start in the cloud-computing space to build a commanding lead that should also work to its advantage in AI. Amazon accounted for more than 30% of the cloud infrastructure market in 2018. That level of market dominance means that an incredible amount of information is pumped through the company's data centers and gives the company access to an abundance of valuable data that can be fed to machine-learning algorithms
Amazon has also emerged as an early leader in smart speakers and voice-command based operating systems.The company's Echo hardware and Alexa voice assistant are category leaders in areas of business that will continue to generate troves of valuable data, and its decision to make the Alexa system available to all of its cloud customers opens up huge new data sources. Amazon is also developing its own chips for use in its Alexa-powered devices and AWS data centers. With data access at the consumer and enterprise levels, and the company investing to build up its assets on the hardware side of things, Amazon has a bright future in artificial intelligence.
Microsoft (NASDAQ:MSFT) has a strong position in the cloud computing space with its Azure platform, a characteristic that both gives it an edge in the A.I. space and positions the company to be a major beneficiary of machine-learning advancements.
The Azure platform trails behind Amazon Web Services in terms of market share, but Microsoft still enjoys a favorable position in data centers and cloud computing. Additionally, its leadership role in the enterprise software space and moves to transition Office and other software suites to cloud-based services could give the company access to types of information that its competitors might have difficulty getting. Advances in AI features should help improve the value of Microsoft's Azure-based services.
Cloud computing will play a substantial role in the advancement of artificial intelligence technology, but semiconductors, processors, and other computing hardware will still play an important role in powering AI and datacenters. NVIDIA (NASDAQ:NVDA) is a leader in graphics processing units (GPUs) that help power AI applications and is seeing big growth for processors used by leading cloud-services providers like Amazon and Microsoft.
As such, it's already established itself as an important role in the self-driving car space. NVIDIA's chips are also playing a big role in current applications of AI within the healthcare space, with the company partnered with General Electric to provide hardware for the GE Healthcare initiative.
Facebook's (NASDAQ:FB) services reach over 2 billion monthly active users. With that kind of reach and engagement, the company is tasked with sifting through massive amounts of data and making sure that each of its users see the content that is most relevant to their interests. The tech company already employs machine-learning algorithms to tailor content distribution to user tastes in an effort to deliver enjoyable experiences across its social media platforms, and it will increasingly lean on AI in order to moderate content on its platform.
Like other, primarily software-driven tech giants with leadership ambitions in the machine-learning space, Facebook is now designing its own custom AI-focused chips in a move to lessen its dependence on third-party chipmakers and make sure that it's working with hardware specifically built for its needs.
As IBM's (NYSE:IBM) legacy mainframe and service businesses lose steam, the company is looking to a new set of growth businesses to offset the declines and position the company for future growth. Artificial intelligence looks to play an important role across these growth initiatives, and Big Blue's $34 billion acquisition of open-source software services company RedHat was likely carried out to jump-start its position hybrid-cloud services and reposition the business to better compete against leading high-tech rivals.
IBM doesn't have assets that generate data at the consumer level like Google, Amazon, and Facebook, but the company has an entrenched position in enterprise services and has been aggressive with its investments to stake out a leadership position in AI. IBM's Watson is already creating value in the the healthcare industry, and the company is making big investments to further develop its cognitive-health business and other AI applications. Artifiicial intelligence is also bolstering the company's security features and services. Enterprise security solutions are a core part of Big Blue's future, and advanced machine-learning algorithms look to be essential to defending against the cybersecurity threats of tomorrow.
Baidu (NASDAQ:BIDU) is sometimes referred to as the "Google of China" because it owns and operates the country's leading search engine. This keystone position in China's internet and data industry endows Baidu with significant advantages in the race to develop more advanced artificial intelligence. Similar to American tech leaders like Alphabet and Amazon, Baidu has its own voice-based operating system and is rolling out compatible hardware including lines of smart speakers, smart lighting, and other devices for the connected home.
Baidu is making a big push into self-driving cars as well and is working on machine vision and machine learning technologies that it expects will pave the way for advanced autonomous-navigation features. The company has built a network of partnerships that should help cement its leadership position in the space and enjoys strong support from the Chinese government in the development of AI technologies.
Alibaba (NYSE:BABA) owns and operates Tmall and Taobao, online sales platforms that make the company China's undisputed e-commerce leader. It also operates the country's leading cloud services platform. That puts it in a position that's somewhat comparable to Amazon. It's worth noting that Alibaba's cloud computing platform is a much smaller component of its overall business, as with Amazon, access to the combination of valuable data sources like large-scale e-commerce and cloud computing .
Alibaba uses machine-learning algorithms on its online-retail platforms to adapt product suggestions and search results based on user behavior and looks to be making progress on a range of important AI fronts. The company's reading algorithm beat the average human score on a reading-comprehension test put together by Stanford University. Alibaba's recently released smart speaker is seeing strong early adoption and has the potential to be a major boon for the company's e-commerce and data initiatives, and the company is also working on smart car and smart city technologies that could strengthen its artificial-intelligence platform.
With a leading position in China's social media space and expertise in interactive entertainment that could have underappreciated crossover applications for machine learning, Tencent Holdings (OTC:TCEHY) has the potential to be a big winner in AI. The company's WeChat messaging platform counts roughly a billion monthly active users and stands as China's most-used social media platform. While messaging is WeChat's central feature, the app has evolved to become an all-in-one service for socializing, keeping up with news, shopping online, and accessing online gaming portals.
Tencent Holdings is also the world's largest video game publisher thanks to hugely popular franchises like League of Legends, Honor of Kings, and Fortnite. That might not seem immediately relevant, but games can generate large amounts of valuable data, and companies in the gaming software industry have experience with artificial intelligence systems that can be translated to other applications.
Tencent is also making a push to be a bigger player in cloud services and is rolling out AI features to support that fast-growing part of its business. So, across its varied product offerings, the company has businesses which should provide its AI projects with valuable data, and the Chinese multimedia giant stands to benefit as it uses machine learning to bolster its social-media advertising, cloud services, and other ventures.
The AI revolution is just getting started
As AI technology continues to evolve, the number of use cases and the impact across industries will only grow. The exact progression of the artificial-intelligence market is difficult to predict because it's uncharted territory and involves a huge number of variables, but the tech is already creating value and paving the way for new innovations and is still in a nascent state relative to its potential.
For those looking to invest in tech companies, the continued evolution and deployment of machine-learning algorithms presents a potentially huge growth catalyst and stands a good chance of being this century's most important tech trend.