Because of the value artificial intelligence brings to businesses across industries and especially the hype surrounding it, the technology is an excellent investment opportunity. Since every opportunity is accompanied by risk, it is important to have the right perspective when considering an investment.

Artificial Intelligence (AI) is an industrial, as well as a scientific paradigm shift with real potential to disrupt the current business status quo. The general public is thrilled by its recent developments and at the same time anxious about the possible scenarios of its application.

Enterprises are rushing to lay their hands on promising AI software to improve their productivity and enhance their revenue streams. Whereas, investors who are pooling substantial funds might still find it challenging to identify potentially successful projects, startups, and companies relying on AI.

Despite the general optimism surrounding the progress of AI, it is necessary to understand the underlying concepts and possible implications associated with this technology before investing in it. Read on to find out about the most relevant terms, techniques, and critical factors to consider when investing in AI, where the value lies for investors, and learn about the most profitable AI stocks.

Artificial intelligence technology concepts

Swedish philosopher Nick Bostrom defines artificial intelligence as a system that can answer our questions with an increasing degree of accuracy while, at the same time, act autonomously to achieve some long-term objective. In general terms, AI is the ability of computers to learn and solve new problems in a changing environment without being explicitly instructed to do so.

Artificial intelligence is a multidisciplinary field that involves technologies such as machine learning, natural language processing (NLP), Internet of Things (IoT), robotics, and Big Data.

Machine learning is a collection of methods for training AI models based on the given data to simulate real-world scenarios. These methods learn from the data and generate predictions or give answers to problems without being explicitly programmed. Some of the most popular machine learning methods are deep neural networks, genetic algorithms, support vector machines, and reinforcement learning.

Natural language processing algorithms process unstructured data from text, audio, and video sources and convert it to structured data necessary to solve problems in various applications.

Internet of Things (IoT) is the next step in the computational revolution representing the eyes and the ears of AI. Through the deployment of a large number of devices with advanced sensing capabilities, IoT generates necessary data that AI algorithms need.

Advancements in collaborative robotics and AI-based control of robots have allowed for a widespread application of robots in many real-world scenarios. AI and robotics technologies have aligned their development roadmaps as robots are the embodiment of AI and its manifestation in the physical world.

Big Data technology deals with the ways to extract and analyze information from large and complex datasets. This data is fed to deep learning AI models that operate based on multiple layers of an artificial neural network.

Artificial intelligence industry applications

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Artificial intelligence is finding applications in an increasing number of fields and is getting better at a variety of tasks, like playing chess, giving recommendations on streaming your favorite shows, or even driving cars. Besides gaming and automotive industries, AI is also being used in various sectors of business, including healthcare, education, finance, manufacturing, and law. Let’s take a look at some of its use cases in more detail.

Healthcare

Artificial intelligence aims to mimic and enhance human cognitive capabilities and is causing a major paradigm shift in healthcare. By consuming large amounts of healthcare data applying sophisticated learning algorithms, AI is capable of assisting doctors, physicians, technicians, and other healthcare professionals in devising and applying better patient treatments and performing better analysis of diagnostic data. The most successful applications of AI in healthcare are the areas of disease diagnosis, development of treatment protocol, new drug development, and personalized medicine.

Education

Most significant technological achievements in education are attributed to artificial intelligence. Some of the top AI applications in education are personalized tutoring, collaborative learning platforms, and interactive virtual reality. AI tutoring systems simulate the tutor-student scenarios by employing machine learning models to make decisions about the learning methods and pace for an individual student. Machine learning models are also used to facilitate collaborative learning by fostering adaptive group creation, helping online group communication, and assisting human tutors in achieving course objectives. AI technology plays an integral role in shaping interactive virtual reality experiences and gamified learning environments that help engage students.

Finance

Among its many applications in the financial industry, artificial intelligence has been most effective in financial fraud detection and credit scoring. Financial fraud, including credit card fraud, has a devastating economic impact. Financial institutions employ AI systems to distinguish between authentic and fraudulent financial transactions just in time to eliminate or decrease the impacts of fraud. Financial institutions seeking to manage credit risk more effectively employ AI solutions powered by quantitative models built using diverse data.

Manufacturing

As an integral component of Industry 4.0, artificial intelligence enables real data-driven, and flexible manufacturing models aimed at decreasing cost, increasing transparency, and reducing environmental impact. By utilizing AI in manufacturing processes, enterprises can increase market competitiveness. More intelligent software also extracts greater efficiency from robotic systems deployed on factory floors.

Law

AI-powered software tools are now capable of performing such tasks as predicting court outcomes based on the available legal data. Next to expert systems, AI is involved in extracting useful information from unstructured legal literature. Machine learning models empower lawyers by helping them work more efficiently, expand their areas of expertise, and provide more value to clients. Future AI development is set to completely transform how lawyers settle legal battles between their clients.

Types of AI companies to invest in

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Artificial intelligence has seen wide adoption by businesses across many industries, domains, and sectors. Here’s how we can classify companies that have launched their AI projects according to investment considerations.

Research (university) spin-offs

Research/University spin-offs are newly formed companies that transform research efforts into technological inventions and, eventually, profitable business models. These companies are research-oriented and tackle difficult problems. Research spin-off teams are composed of experienced innovators capable of delivering breakthroughs that advance the field. However, investing in research spin-offs is a long shot, as they are less likely to bring quick returns due to the nature of scientific research.

Data-as-a-service companies

Data-as-a-service (DaaS) companies gather specialized datasets or create new data sources by connecting previously unrelated vertical markets. These companies are usually highly profitable and not easily replicable.

Model-as-a-service companies

Model-as-a-Service companies are one of the most widespread groups, creating streams of revenue by commercializing their models. These companies offer viable products early on and have a high potential to monetize their products in the short term, but their technology needs to be further developed to extract real value. These companies usually come in three forms: narrow AI, value extractors, and enablers.

Narrow AI are companies that focus on solving a specific problem through new data, innovative algorithms, or better interfaces. Their products could be used and distributed as part of a bigger solution or a platform.

Value extractors are companies that utilize their models to extract value and insights from data. Their solutions can be either integrated into customer solutions through APIs or be delivered as full-stacks solutions.

Enabler companies enable the final users to do their analysis, allow them to make daily workflows more efficient, or unlock new opportunities by creating new applications.

Robot-as-a-service companies

Robot-as-a-Service companies create virtual or physical agents that people interact with. Virtual agents, most commonly chatbots, are low cost, easily accessible systems. Physical agents, on the other hand, are autonomous cars, drones, and industrial robots that employ AI in executing their tasks. Physical robot manufacturing companies require high capital and talented employees.

This group of companies usually faces problems due to hardware components becoming quickly obsolete and the difficulties in creating the right interactive interfaces. However, successful companies from this group are a great prospect for generating long-term profits from investment.

What you should consider when investing in AI stocks

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Investing in artificial intelligence projects is very attractive as the technology has established itself in many industries and dominates the way business is done in the majority of large enterprises. Due to the technological versatility of AI, it is not being used just by software companies but also by retail companies, financial organizations, healthcare providers, educational institutions, and supply chain companies. One of the primary ways of investing is by purchasing stocks of these companies and organizations. Below are some essential factors to consider before trying to capitalize on AI projects.

Associated risks

Data is the principal input for artificial intelligence algorithms. In some applications, collecting and utilizing data to train machine learning models may involve privacy concerns. A known example of a company struggling with this issue is DeepMind. In 2016, the company agreed to gain access to health data from the Royal Free London NHS Foundation Trust, which operates three London hospitals with around 1.6 million annual patients. This agreement led to a legal battle as it was against the Data Protection Act. These kinds of disputes may tarnish the brand’s identity and lead to significant losses for the investors as well.

The autonomous car industry entails ethical concerns from state regulatory bodies and institutions. Due to possible changes in these regulations and the complications related to maintaining compliance, investment in driverless car companies can be risky. Thorough research is necessary to understand the complex ethical dynamics of this industry.

Substantial risks are associated with investments in AI companies that are solving a broad scope of business problems. It is safer to invest in companies that limit their services to a specific market or target a specific type of client. Such companies have better chances of succeeding in delivering the highest quality of services and therefore are much more profitable from the investor’s point of view.

Industry Selection

Picking the artificial intelligence stocks to invest in could prove to be quite challenging. The current trends indicate that healthcare and manufacturing seem to be the most promising based on the projects launched or currently in development.

As the paradigm shifts to global health sustainability and healthcare systems move from illness management toward wellness maintenance, personalization of healthcare based on AI play a significant role. The increased availability of high-quality and comprehensive data is an essential growth factor and success driver of AI in healthcare. In particular, companies dealing with machine learning for disease diagnosis and drug discovery, natural language processing, and robotics should be among the top picks for long-term benefit investment.

AI stocks in the manufacturing industry also hold many opportunities for investment as they can capitalize on the vast amounts of data collected during the automation and develop smart maintenance, improved manufacturing processes, and human-robot collaboration.

Data volume and quality

Data is the foundation of all of the AI algorithms. As the research in mathematics and statistics is progressing, the algorithms are becoming more sophisticated and perform better than before. It is becoming more apparent that the real success of AI applications will be highly dependable on the amount and quality of collected data.

From the investor’s point of view, companies that own large and high-quality datasets will have a better chance to succeed in the market. Companies with a unique set of data are some of the best investment options as they have a higher prospect of delivering significant value to their customers. As the most comprehensive search engine, Google has access to massive datasets and can use them to produce unique AI systems. Likewise, Amazon owns data about customer’s shopping patterns and can deliver unique and profitable AI services.

Ways of investing

The most common way of investing in AI is by purchasing stocks of an AI company or a company that utilizes AI as part of their business. However, this is not the only way to invest in AI. There’s also a possibility to invest in ETFs and startups, as some of the candidates could have a much higher return on investment.

Investment in stocks of AI companies looks very similar to the traditional stock investment. Many companies use AI technology to create their products and services. The widespread adoption of AI technology will help these companies become successful, and in return, the value of their stocks will increase as well.

Most of the companies that specialize exclusively in developing AI products and services are relatively new to the market, and investing in them poses a high risk coupled with high gains. The less risky option is to invest in companies that use AI technology as a part of their business, such as Google, IBM, Amazon, and Microsoft. Companies that enable other companies to accumulate data also present valuable investment avenues.

The ETFs are investment funds traded on the stock exchanges, similar to stocks. ETFs are like a stock basket that meets a specific goal. Similarly, AI ETFs own public business shares in AI companies. ETFs investment offers certain advantages. They are easy to purchase, and there is no need to buy hundreds of different stocks to diversify one’s investment.

There is a professional management team behind the ETFs that actively trades stocks. Investors, therefore, are not involved in the cumbersome decision-making process. ETFs are also low cost and offer risk-mitigating diversification. The value of AI ETFs is likely to rise together with the widespread adoption of the technology.

As many of the AI companies have still not reached public offering, one of the ways to invest in them is through angel investing. Angel investors are the first to provide funding to a startup and get equity in the company in return. Artificial intelligence is an excellent opportunity for startups. Innovative startups employing AI technology emerge on the market every day. Once these startups succeed, they usually become very profitable, and angel investors have an excellent chance to avail return on their investments.

The best artificial intelligence stocks

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Research is critical in deciding which stocks to invest in and choosing AI stocks demands the same determination. It is essential to understand the level of involvement of the company in AI, the vision that the company has for its application, and its current commitment in terms of its development. The companies listed in this section are a good starting point when considering investing in AI stocks.

Microsoft Corporation (NASDAQ: MSFT)

Microsoft is one of the leading companies that invest heavily in AI technology. Satya Nadella, CEO of Microsoft states that they are focusing on empowering people and organizations by “democratizing access to intelligence to help solve our most pressing challenges.”

Microsoft has one of the largest corporate AI research teams, counting more than 5000 people. The company is seeking both hardware and software-based AI solutions in areas such as precision medicine and genomics, human language innovations, assistive robotics, medical imaging, and consumer-facing services (Cortana).

Microsoft continues its investment efforts to help them combine their cloud technology (Azure) with AI. In this way, their business outcomes have predictable growth potential as the AI technology develops, thus making them an attractive AI stock.

Apple (NASDAQ: AAPL)

Apple has been well known for its innovations in the consumer electronics industry. Recently the company started using machine learning and other AI technologies to deliver sophisticated software features for their devices. Apple’s digital assistant Siri has been around for a while. Their latest smartphone’s hardware includes the Bionic chip, which is dedicated to performing machine learning tasks and is much faster than conventional microprocessors built into most other smartphones available on the market.

Apple is also developing powerful software packages as part of its iOS development tools for easier adoption of the technology. Apple’s research efforts in AI and the availability of the device ecosystem offers them a unique positioning in the future.

Amazon (NASDAQ: AMZN)

Amazon has been well-known for its technical innovations and disruption of online retail business. The company is very versatile and operates in the e-commerce, cloud computing, digital streaming, and artificial intelligence markets. Additionally, they recently entered the healthcare market as well. Aside from hosting the world’s largest online marketplace, Amazon dominates the market of AI personal assistants with Alexa and also leads in cloud computing service provision.

Some of Amazon’s most noted AI development achievements in these domains include personalized recommendations engine, product search queries, demand forecasting, warehouse fulfillment, and fraud detection. The company’s AWS cloud computing platform provides the infrastructure and tools to develop cloud-based enterprise-level solutions powered by advanced machine learning and natural language processing tools offered as a service.

Alphabet (NASDAQ: GOOGL)

Google’s CEO, Sundar Pichai likes to call it an “AI-first” company as they integrate AI across their whole product line, including Gmail, YouTube, Maps, Photos, Google Cloud, etc. The company also has a personal assistant that connects with more than 5000 devices at home.

Google has been setting industry standards for AI development through its TensorFlow software framework. This framework is used by companies such as Uber, eBay, Coca-Cola, and others as the foundation for their services created using machine learning models. Additionally, Google is developing autonomous vehicles technology through a business unit called Waymo. Some of the investment banks, including Morgan Stanley, see Waymo gaining a significant market value as the driverless car industry develops.

NVIDIA (NASDAQ: NVDA)

NVIDIA is one of the leading hardware providers for the artificial intelligence market. The company manufactures GPUs (Graphical Processing Units) which proved to be very effective tools for completing the complex computation required by most AI applications. GPUs enable parallel processing at high speeds suitable for both production and development environments when training machine learning algorithms. Together with the increased use of their GPUs in data centers and autonomous vehicles, NVIDIA is gaining in value as AI solutions are becoming industry standard.

Tencent Holdings (HKG: 0700)

Tencent is a Chinese IT conglomerate providing a variety of services that include social networks, music, e-commerce, mobile games, payment systems, smartphones, and multiplayer online games. The company has an in-house research lab with a focus on machine learning, speech recognition, natural language processing, and computer vision aimed at developing practical applications in the areas of content marketing, online games, social media, and cloud services.

Tencent plans to expand its AI offerings to cover a variety of industries. In the medical industry, the company is working on products that will assist doctors in the early detection and prevention of diseases. In the agriculture industry, Tencent is planning to help farmers increase crop yield and make efficient use of resources. In manufacturing, it is partnering with companies to upgrade their capabilities through AI and help businesses optimize their infrastructure and operations.

IBM (NYSE: IBM)

IBM has been at the frontier of AI developments for a long time, starting with the AI computer ‘Deep Blue’ in 1985 to the modern-day Watson which now stands at the forefront of solving various business challenges. IBM delivers a range of AI solutions to its customers. Their lifecycle management tools facilitate building, running, and managing smart apps.

The company’s solutions span across a range of industries, from healthcare where their products improve the quality of patient care, to the financial businesses where the company revolutionizes the approach to regulatory compliance. Besides that, Watson’s API offers ready-to-use natural language processing services.

According to IDC’s recent report, IBM is a market leader in AI. The company invests in both hardware and software. In 2019, they spent US$2 Billion on establishing an AI Center to build AI hardware and boost the performance of algorithms by 1000 times over the next ten years.

Alibaba Group (NYSE: BABA)

Alibaba is one of the most solid Chinese AI stocks. Alibaba’s success story is very similar to Amazon’s. The company leverages its large e-commerce user bases to develop innovative systems for better personalization and logistics. Similar to Amazon’s Alexa, Alibaba has its own virtual assistant. The company also has a US$1.15 billion commitment to invest in the smart speaker market.

Alibaba has investments in both hardware and software. Their chip, Hanguang 800, is showing promising outcomes in AI model development. Alibaba offers AI integrated cloud services, similar to its US counterparts Azure and AWS, with an investment commitment of US$28 billion in the next three years.

Baidu (NASDAQ: BIDU)

Just like Google, Baidu started as a search engine company. After initial success, the company extended its offerings that leverage AI to help them personalize search experience and improve the impact of online ads. Next to nurturing their own systems, the company has created several AI platforms for other companies as well.

One example is DuerOS, a comprehensive solution that allows users to command and converse with their devices using natural language. Baidu also invests in self-driving cars. Their platform Apollo powers more than 100 autonomous vehicle types across 17 cities in China.

Baidu has partnered with Huawei to develop an open mobile AI platform to support the development of AI-powered smartphones and with Qualcomm to optimize its DuerOS for IoT devices and smartphones. Besides these, Baidu has expanded its AI services to many different industries, and they invest in AI businesses through Baidu Ventures.

Salesforce (NYSE: CRM)

Salesforce is a software company that helps businesses organize and handle sales operations and customer relationships. The company processes large amounts of data from day-to-day transactions and involves AI to offer tailored services to its customers.

Salesforce’s AI platform, Einstein, incorporates machine learning, natural language processing, computer vision, and speech recognition components to build custom predictions and recommendations, embed predictive insights into mobile apps, and streamline workflows. Recently, Salesforce acquired Tableau data analytics company for US$15.7 billion, intending to provide data visualization for business intelligence applications.

Promising AI stocks to keep an eye on

Aside from household names and industry leaders, there are also a few promising companies that have smaller projects or use AI technologies to provide clients with a higher quality of service and offer special features. We’ve rounded up a short list of these below.

Twilio offers a communication platform that can be utilized for implementing voice, messaging, and video conference functionality. They’ve also included AI tools within their packages that allow building, training, and deploying AI-powered bots for contact centers.

Splunk offers monitoring and analytics solutions that use AI for observability and extracting insights across services, applications, and infrastructure.

Yext is a top data provider with more than 150 services integrated by operators like Google, Apple, Amazon, Microsoft, Facebook, and Tencent. Yext also enables accurate real-time searches with context-added data. The company manages over 185 million platform facts about their customers.

Netflix is a top-rated video content provider. They invest heavily in further developing their AI-powered content recommendation engine.

Alteryx has built one of the top platforms for data that offers an easy way to build models for people who do not have data science backgrounds. The platform uses AI to build AI. The vision of Alteryx is to allow for the so-called “citizen data scientist.”

Conclusion

Artificial intelligence powers many industrial applications which have now become essential in our everyday life activities, including for business executives. Text-based search and video content recommendations, weather prediction, analyzing customer shopping behavior, extracting insight from unstructured data, and making forecasts for financial markets are all AI features that turn the page to a new chapter of business innovation. These are the types of projects that are currently worth investing in.

Investment in AI stocks is a long-term strategy. These stocks will result in capital gains and stability as AI development companies contribute to the expansion of the emerging technology’s applicability. The key factors to consider when investing in AI are the associated risks (privacy, ethics, etc.), the current top-performing industries, and the quality of datasets that are used for AI training. The possible ways to invest in AI are diverse, including acquiring stocks of AI companies, purchasing stocks in ETFs, and angel investing in startups.

 

Disclaimer

This article represents the authors’ own opinions and does not imply financial advice. Any content published by PixelPlex should not be taken as a guide to action.
PixelPlex strongly recommends consulting a qualified investment advisor and/or conducting your own independent research before making financial decisions.

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