Consider it the conclusion of the initial phase of the AI Boom.
Since the middle of March, several prominent artificial intelligence startups have been under financial strain. Inflection AI, which secured $1.5 billion in funding but generated minimal revenue, has shut down its original operations.
Stability AI has laid off staff and parted ways with its CEO. Meanwhile, Anthropic has been rushing to bridge the approximately $1.8 billion gap between its modest earnings and substantial expenses.
It’s becoming evident in Silicon Valley that the AI revolution will come with a hefty price tag. Tech firms that have staked their futures on it are scrambling to find ways to narrow the chasm between their expenses and the anticipated profits.
This predicament is especially pressing for a cluster of high-profile startups that have raised tens of billions of dollars for the advancement of generative AI, the technology behind chatbots like ChatGPT.
Some of them are realizing that directly competing with industry giants such as Google, Microsoft, and Meta will require billions of dollars — and even that may not suffice.
“You can already see the signs,” remarked Ali Ghodsi, CEO of Databricks, a data warehouse and analysis company that collaborates with AI startups. “No matter how impressive your work is — does it have commercial viability?”
While substantial funds have been squandered in previous tech booms, the cost of constructing AI systems has astounded seasoned tech industry professionals. Unlike the iPhone, which initiated the last technological transition and cost a few hundred million dollars to develop due to its reliance on existing components , generative AI models cost billions to create and maintain.
The advanced chips they require are expensive and in short supply. Moreover, each query of an AI system is far pricier than a simple Google search.
According to PitchBook, which tracks the industry, investors have injected $330 billion into approximately 26,000 AI and machine-learning startups over the past three years. This amount surpasses by two-thirds the funding provided to 20,350 AI companies from 2018 to 2020.
The challenges confronting many newer AI companies sharply contrast with the early business outcomes at OpenAI, which is backed by $13 billion from Microsoft. The attention garnered by its ChatGPT system has enabled the company to establish a business charging $20 per month for its premium chatbot and offering a platform for businesses to develop their AI services using the underlying technology of its chatbot, known as a large language model.
OpenAI generated approximately $1.6 billion in revenue over the past year, but the company’s expenditure remains unclear, as per two individuals familiar with its business.
OpenAI did not respond to requests for comment.
However, even OpenAI has encountered difficulties in expanding its sales. Businesses are cautious about the potential inaccuracies of AI systems. The technology has also grappled with concerns regarding potential copyright infringement in the data supporting the models.
(OpenAI and Microsoft were sued by The New York Times in December for copyright infringement related to news content associated with AI systems.)
Many investors point to Microsoft’s rapid revenue growth as evidence of the business potential of AI In its most recent quarter, Microsoft reported an estimated $1 billion in AI services sales in cloud computing, a notable increase from virtually zero a year earlier, according to Brad Reback , an analyst at the investment bank Stifel.
offline, Meta does not anticipate earning profits from its AI products for several years, even as it ramps up its infrastructure spending by as much as $10 billion this year alone. “We’re investing to stay at the leading edge of this,” remarked Mark Zuckerberg, Meta’s CEO, in a call with analysts last week. “And we’re doing that while also scaling the product before it becomes profitable.”
AI startups have been grappling with the disparity between spending and sales. Anthropic, which has garnered over $7 billion in funding with support from Amazon and Google, is spending approximately $2 billion annually but is only bringing in around $150 million to $200 million in revenue, according to two individuals familiar with the company’s finances who requested anonymity due to the confidential nature of the figures.
Similar to OpenAI, Anthropic has turned to established partnerships with tech giants. Its CEO, Dario Amodei, has been pursuing clients on Wall Street, and the company recently announced its collaboration with Accenture, the global consulting firm, to develop custom chatbots and AI systems for businesses and government entities.
Sally Aldous, a spokesperson for Anthropic, stated that thousands of businesses are utilizing the company’s technology and that millions of consumers are using its publicly available chatbot, Claude.
Stability AI, a company specializing in image generation, recently announced that its CEO, Emad Mostaque, had stepped down. This came shortly after three researchers from the original five-person team also resigned.
A reliable source familiar with the company’s operations indicated that Stability AI was projected to achieve approximately $60 million in sales this year, while incurring costs of around $96 million for its image generation system, which has been available to customers since 2022.
Investors specializing in AI noted that Stability AI’s financial position appears stronger compared to language-model manufacturers like Anthropic, as the development of image generation systems is less costly. However, there is also less demand for paying for images, making the sales outlook more uncertain .
Stability AI has been functioning without the backing of a major tech company. Following a $101 million investment from venture capitalists in 2022, the company required additional funding last autumn but struggled to demonstrate its ability to sell its technology to businesses, according to two former employees who preferred not to be named publicly.
Although the company secured a $50 million investment from Intel late last year, it continued to face financial pressure. As the startup expanded, its sales strategy evolved, while simultaneously incurring monthly costs amounting to millions for computing.
According to an investor who chose to remain anonymous on the matter, some investors urged the resignation of Mr. Mostaque. Following his departure, Stability AI underwent layoffs and restructured its business to ensure a “more sustainable path,” as per a company memo reviewed by The New York Times.
Stability AI declined to provide a comment, and Mr. Mostaque also declined to discuss his departure.
Inflection AI, a chatbot startup founded by three AI experts, had raised $1.5 billion from prominent tech companies. However, almost a year after introducing its AI personal assistant, the company had generated minimal revenue, as per an investor.
The New York Times reviewed a letter from Inflection addressed to investors, indicating that additional fundraising was not the most beneficial use of their money, particularly within the current competitive AI market. In late March, the company pivoted from its original business and largely merged into Microsoft, the world’s most valuable public company.
Microsoft also participated in funding Inflection AI. The company’s CEO, Mustafa Suleyman, gained prominence as one of the founders of DeepMind, an influential artificial intelligence lab acquired by Google in 2014.
Mr. Suleyman, along with Karén Simonyan, a key DeepMind researcher, and Reid Hoffman, a prominent Silicon Valley venture capitalist involved in the founding of OpenAI and serving on Microsoft’s board, established Inflection AI.
Both Microsoft and Inflection AI declined to provide a comment.
Inflection AI was staffed with talented AI researchers who had previously worked at companies such as Google and OpenAI. However, nearly a year after launching its AI personal assistant, the company’s revenue was described by an investor as “de minimis,” effectively negligible. Without continuous substantial fundraising, it would be challenging for the company to enhance its technologies and compete with chatbots from companies like Google and OpenAI.
Microsoft is now absorbing most of Inflection AI’s staff, including Mr. Suleyman and Dr. Simonyan, in a deal costing Microsoft over $650 million. Unlike Inflection AI, Microsoft has the resources to adopt a long-term approach. The company has announced plans for the staff to establish an AI lab in London, focusing on the types of systems that start-ups are striving to advance.
Middle Eastern funds are investing billions of dollars into leading AI start-ups.
Sovereign wealth funds from the Middle East are emerging as significant supporters of prominent artificial intelligence companies in Silicon Valley.
Oil-rich nations such as Saudi Arabia, United Arab Emirates, Kuwait, and Qatar are seeking to diversify their economies and are turning to technology investments as a safeguard. Over the past year, funding for AI companies from Middle Eastern sovereign funds has increased fivefold , according to data from Pitchbook.
According to sources familiar with the matter, MGX, a new AI fund from the United Arab Emirates, was among the investors seeking to participate in OpenAI’s recent fundraising round. The valuation of OpenAI in this round is expected to reach $150 billion, as indicated by the sources, who requested anonymity due to the confidential nature of the discussions.
While few venture funds possess the financial capacity to compete with the multibillion-dollar investments from companies like Microsoft and Amazon, these sovereign funds face no difficulty in providing substantial funding for AI deals.
These funds invest on behalf of their governments, which have benefited from the recent increase in energy prices. It is projected that the total wealth of the Gulf Cooperation Council (GCC) countries will rise from $2.7 trillion to $3.5 trillion by 2026, according to Goldman Sachs.
The PIF, which stands for the Saudi Public Investment Fund, has exceeded $925 billion and has been actively investing as part of Crown Prince Mohammed bin Salman’s “Vision 2030” initiative. The PIF has made investments in companies such as Uber, and has also made significant expenditures in the LIV golf league and professional soccer.
Mubadala, a fund from the UAE, manages over $302 billion, while the Abu Dhabi Investment Authority manages $1 trillion. The Qatar Investment Authority has $475 billion under management, and Kuwait’s fund has exceeded $800 billion.
Earlier this week, MGX, based in Abu Dhabi, formed a partnership for AI infrastructure with BlackRock, Microsoft, and Global Infrastructure Partners, with the goal of raising up to $100 billion for data centers and other infrastructure investments.
MGX was established as a specialized AI fund in March, with Mubadala from Abu Dhabi and AI firm G42 as its founding partners.
Mubadala from the UAE has also invested in Anthropic, a rival of OpenAI, and is one of the most active venture investors, having completed eight AI deals in the past four years, according to Pitchbook. Anthropic declined to accept funding from the Saudis in its last funding round, citing national security, as reported by CNBC.
Saudi Arabia’s PIF is currently in discussions to establish a $40 billion partnership with the US venture capital firm Andreessen Horowitz. It has also launched a dedicated AI fund called the Saudi Company for Artificial Intelligence, or SCAI.
Despite this, the kingdom’s human rights record remains a concern for some Western partners and start-ups. The most notable recent case was the alleged killing of Washington Post journalist Jamal Khashoggi in 2018, an incident that prompted international backlash in the business community.
It’s not just the Middle East that is pouring money into this space. The French sovereign fund Bpifrance has completed 161 AI and machine learning deals in the past four years, while Temasek from Singapore has completed 47, according to Pitchbook. GIC, another fund backed by Singapore, has completed 24 deals.
The influx of cash has some Silicon Valley investors worried backed about a “SoftBank effect,” referring to Masayoshi Son’s Vision Fund. SoftBank notably Uber and WeWork, driving the companies to soaring valuations before their public debuts. WeWork filed for bankruptcy last year after being valued at $47 billion by SoftBank in 2019.
For the US, having sovereign wealth funds invest in American companies, rather than in global adversaries like China, has been a geopolitical priority. Jared Cohen of Goldman Sachs Global Institute stated that there is a disproportionate amount of capital coming from nations such as Saudi Arabia and the UAE, with a willingness to deploy it globally. He described them as “geopolitical swing states.”
Over the past eighteen months, there’s a good chance that you’ve heard plenty about how the AI revolution could add $15 trillion to the global GDP and revolutionize our lives. The world’s leading tech companies are engaged in an arms race to dominate in this new era.
“AI will, probably, most likely, lead to the end of the world, but in the meantime, there’ll be great companies,” declared Sam Altman, co-founder and CEO of OpenAI, in June 2015.
OpenAI, led by Sam Altman, is the prime example of generative AI (GenAI), a technology wave that began nearly two years ago with the launch of ChatGPT.
Its rapid rise generated hype and fear unlike any other recent technology, prompting Big Tech to invest billions in data centers and computing hardware for building AI infrastructure.
“GenAI already has the intelligence of a college student, but it will likely put a polymath in every pocket within a few years,” noted Alkesh Shah, Managing Director at Bank of America.
Since its establishment nine years ago, OpenAI, an AI research backed organization by Microsoft and employing 1,500 individuals, has raised over $11.3 billion and was valued at around $80 billion in February this year. It is reportedly in discussions to raise a new round of funds at a valuation of $150 billion.
As a result, investors have injected tens of billions of dollars into both startups and publicly traded companies to capitalize on the third major technology cycle of the past five decades. This led to a significant increase in the stock prices of most businesses involved in AI over the past year.
Consider the case of Nvidia, one of the biggest winners. In June, the chip vendor surpassed the $3 trillion mark to become the most valued company listed in the US. The shares of the ‘magnificent seven’ group of US tech behemoths also reached record levels.
The exuberance on Wall Street lasted for a year, but last month saw a sharp decline in Nvidia stocks. Major tech companies also experienced significant stock drops, resulting in over $1 trillion in losses.
According to Aswath Damodaran, a finance professor at NYU Stern School of Business, Nvidia’s performance in the last three quarters has set unrealistic expectations for the company. He believes that further slowdown is imminent due to scaling pushing revenue growth down and increased competition decreasing operating margins .
Speculative excitement has given way to concerns about whether companies can effectively profit from their large investments in AI infrastructure. Recent underwhelming earnings reports from tech leaders like Meta, Microsoft, and Google have added to investor worries.
Arup Roy, VP distinguished analyst and Gartner Fellow, notes that while AI is revolutionary, investors are now questioning its sustainability, leading to a loss of its appeal.
AI capital expenditure is projected to reach $1 trillion in the coming months, driven by the need for powerful operating systems and accelerator technologies for training large language models (LLMs). This has tech giants to aggressively invest in data centers and graphic processing units ( GPUs ).
Despite these investments, there is a significant gap in demonstrating the value of AI to end-users, as companies struggle to show revenue growth from AI. David Cahn, partner at Sequoia Capital, argues that AI companies need to generate annual revenues of around $600 billion to cover their AI infrastructure costs.
According to an analysis by The Information, OpenAI is spending approximately $700,000 per day to operate ChatGPT and is on track to incur a $5 billion loss. The company’s hardware is operating close to full capacity, with the majority of its servers dedicated to ChatGPT.
Potential regulatory disruptions related to data collection for privacy, safety, and ethics could disrupt growth plans. Additionally, there is less pricing power for GPU data centers compared to building physical infrastructure, as new players enter the market.
David Cahn warns that if his forecast materializes, it will primarily harm investors, while founders and company builders focusing on AI are likely to benefit from lower costs and knowledge gained during this experimental period.
Most major tech players have announced plans to increase spending as they position themselves for a future driven by AI. Microsoft plans to exceed last year’s $56 billion in capital expenditure, Meta raised its full-year guidance by $2 billion, and Google estimates its quarterly capex spending to be at or above $12 billion.
Alphabet CEO, Sundar Pichai, emphasized the greater risk of under-investing in AI, stating that not investing to be at the forefront has significant downsides. Meanwhile, Meta CEO Mark Zuckerberg justified the company’s aggressive investment in AI, citing the risk of falling behind in the most important technology for the next decade.
Sanjay Nath, Managing Partner at Blume Ventures, observes that a one-size-fits-all approach is not suitable for AI and companies need to choose the best model for each use case. He notes that larger tech incumbents are rapidly investing in training models to stay ahead in the rapidly evolving landscape.
Bank of America believes that the AI hype cycle has reached a phase of disillusionment, where investors tend to overestimate short-term tech disruptions and underestimate long-term impacts. The analysts expect a relatively short time gap between AI infrastructure investment and monetization due to the strong foundation model operating systems currently in place.
“We advise investors not to underestimate the potential cost savings and revenue generation of GenAI before it is even used,” Shah emphasizes.
While industry leaders do not anticipate immediate growth in revenue and profit, they are confident that the latest core models and GenAI applications will enhance operational efficiency and productivity, boosting the economy.
“We have numerous instances of established businesses purchasing AI-centric workflow products,” Nath remarks. “The adoption of AI is certainly a significant reality.”
Microsoft’s Chief Financial Officer Amy Hood recently rescued investors that the company’s investments in data centers will facilitate the monetization of its AI technology for at least 15 years and beyond.
Meta’s Chief Financial Officer Susan Li assured investors that returns from GenAI may take a long time to materialize. “We do not anticipate our GenAI products to significantly drive revenue in 2024,” Li informed analysts. “However, we do expect that they will create new revenue opportunities over time, enabling us to achieve a substantial return on our investment.”
This presents a challenge for investors in publicly traded companies who typically expect returns within a shorter timeframe compared to venture capital investors, who usually have a longer investment horizon of around 10-15 years.
Nevertheless, most agree that the current rate of capital expenditure on AI is unsustainable, and one or more of the tech giants may need to scale back investments by early next year to allow revenue growth to catch up.
Despite the recent decline in tech stocks, experts dismiss any parallels between the current AI surge and the late-90s dotcom bubble.
“Srikanth Velamakanni, co-founder, group CEO, and executive vice chairman of Fractal, asserts that AI will have a much greater and more transformative impact than the dotcom revolution or any other technological revolution we have seen.”
While both cycles saw tech company valuations reach unrealistic levels driven by hope and excitement rather than a clearly defined profitable revenue stream, there are differences.
Crucially, today’s tech leaders are highly profitable and have proven business models that will not collapse even if their AI initiatives fail. They possess strong competitive advantages in the form of proprietary data and a large user base.
“The dotcom companies did not have the level of cash flow and demand visibility that today’s top US tech companies enjoy,” points out Siddharth Srivastava, head of ETF products and fund manager at Mirae Asset (AMC). “US tech stocks are due for some correction, but the AI theme will remain strong in the next 3-5 years.”
JP Morgan research indicates that the average price-to-earnings (PE) ratio of today’s tech giants is around 34, which is not excessively high for growth stocks. In contrast, the average PE ratio of the group of listed dotcom companies was 59.
However, there is growing concern that the valuation of some AI startups may be approaching bubble territory as opportunistic players join the trend.
“Some startups have ‘.ai’ in their company names but are only capable of creating AI ‘wrappers’,” Nath warns. “We are concerned that these startups may initially succeed in raising funds but will soon struggle and ultimately fail.”
The AI landscape in India is relatively less crowded. Since 2009, investors have injected $2.6 billion into domestic startups developing AI for various purposes. This is a small fraction of the $55.8 billion invested in AI startups in the US during the same period.
The launch of ChatGPT in November 2022 made entrepreneurs realize how AI’s true power can be made accessible to millions of users worldwide.
Roy expresses some disappointment with domestic tech providers. “Most of these companies are followers, and there isn’t much innovation yet,” he complains. “Investors want to see ‘proof of value’ and are no longer swayed by just a ‘proof of concept.’”
The experienced research analyst, however, is optimistic about the progress of domestic companies in utilizing conversational AI to guide a customer’s buying journey, for example. He is also hopeful that more companies benefiting from AI will emerge. “This presents a wealth of opportunities, ” he states.
Developing cash-intensive core models from scratch for artificial general intelligence (AGI) applications requires billions of dollars in investment. “There is no chance of any Indian company being funded at that level,” laments Velamakanni. “You need vision along with capital and talent.”
Velamakanni is confident that India has the potential to establish application-focused companies using foundational models to address real-world challenges in various sectors without requiring substantial funding. He mentioned that startups in this space in India are highly competitive and have been successful in raising funds .
Fractal, founded 20 years ago, has secured $685 million from 13 investors. In January 2022, it became a unicorn after raising $360 million from TPG, achieving a revenue multiple of 7.1 times and a post-money valuation of $1 billion.
Nath, in the era of AI, advises founders within the ecosystem to reconsider their go-to-market (GTM) strategy. He emphasized that the traditional sequential approach for SaaS might not be effective anymore. With AI, the path to reaching a $100 million annual recurring revenue (ARR) business seems to be faster, requiring an evolved GTM strategy and channels.
Historically, disruptive technologies have taken 15-30 years to be widely adopted. For instance, the radio, invented in 1890, only became commercially available in 1920. similarly, the television, developed in the 1920s, was only found in homes in the 1950s . Even though email was invented in 1969, it gained popularity in 1997.
While predicting the future is uncertain, proponents believe that artificial intelligence (AI) is likely to become mainstream in the next three to five years, potentially benefiting companies investing in it. The ultimate use of AI, however, remains to be seen, and only time will reveal how “real” artificial intelligence is.
Discover how to invest in AI and take advantage of future opportunities
Artificial intelligence (AI) is no longer a concept of the future – it is a revolutionary force that is reshaping industries and our daily lives. Before considering AI investments, it is important to grasp the definition of artificial intelligence; AI technology imbues computers and technological products with human-like intelligence and problem-solving capabilities.
From virtual assistants in our homes to self-driving vehicles on our roads, AI is rapidly being integrated into numerous products and applications, dominating discussions on investments and future prospects.
The AI landscape is intricate, and news of enhanced capabilities at one company can quickly change the pace of progress for all. Identifying the best AI companies to invest in is a challenging task, even when utilizing the top online brokers and trading platforms.
Similar to how investors in the past had to discern between promising and less promising web browsers, smartphones, and app-based startups, niche players and established tech giants are now competing for AI market share and research funding.
In this article, we will explore the process of investing in AI and showcase the most promising AI stocks and funds.
How to Invest in AI
Similar to previous emerging technologies like railroads in the late 1800s or personal computers in the 1980s, there are numerous avenues for investing in AI. While some companies will achieve great success, others may falter.
The computer revolution serves as a fitting analogy for AI investing and understanding how to invest in AI. Computers laid the groundwork for automating routine and repetitive tasks, and now AI aims to build on this concept by automating tasks that previously required human intelligence.
Investors may find that certain top AI stocks have seen one-year returns in the high double digits, with NVIDIA reporting 176% growth over the past 12 months as of July 23, 2024.
Some individuals may be interested in directly investing in companies that develop AI, while others may prefer to invest in companies that are poised to benefit significantly from its widespread adoption.
Drawing from the introduction and growth of the personal computer industry, some investors successfully invested in computer manufacturers or hardware companies that produced routers and switches.
Others invested in software companies that developed computer programs, while some sought to identify companies that would benefit the most from the automation offered by computers.
Some of these investments were direct bets on computers and the actual technology, while others were more conservative, such as purchasing shares in already established companies that stood to benefit from the expansion of computer usage. The key point is that there are various methods for investing in a new technology.
There are instances where one company takes and maintains a leading position in the market, but there are also cases where an imitator can leverage the first company’s technology more effectively, leading to greater success over time. Given the difficulty of predicting the winning AI stocks in advance, holding several stocks or opting for an AI ETF could help minimize the risk of making a wrong move.
Investing in AI Stocks and ETFs
Prominent Companies in AI
While these are some of the top AI stocks, it is advisable to consider the business cycle and valuations before committing fully. Employing dollar-cost averaging in AI stock selections can serve as a hedge against market downturns.
NVIDIA (NVDA): NVIDIA Corp. is leading the AI revolution through its work in designing and developing graphics processing units (GPUs) and associated software and data center networking solutions.
Investors have taken notice: as of July 23, 2024, its share price has surged by 176% over the past 12 months and expanded by over 2,885% in the last five years.
Originally developed for the PC graphics and video gaming industries, these GPUs have become fundamental to AI, machine learning, self-driving vehicles, robotics, augmented reality, virtual reality applications, and even cryptocurrency mining systems.
Microsoft (MSFT): Microsoft is an example of an established tech company delivering on AI investment promises. Microsoft has partnered with OpenAI, the company behind ChatGPT. It has leveraged this partnership to integrate AI into its Azure cloud services, and Microsoft 365 now offers an add-on subscription for generative AI, known as Copilot.
Microsoft stated in its April 2024 earnings call that 65% of the Fortune 500 were using its Azure OpenAI service, a similar percentage to those using Copilot.
AeroVironment Inc. (AVAV): Government contracts with the US Department of Defense and US allies provide a level of support for this narrowly focused AI stock. AeroVironment Inc. supplies unmanned aircraft and tactical mission systems, along with high-altitude pseudo-satellites.
The AVAV systems offer security and surveillance without the need for a human operator or pilot in the air.
Amazon.com (AMZN): Amazon’s generative AI capabilities enhance customer experiences, boost employee productivity, foster creativity and content creation, and optimize processes. Amazon employs AI in its Alexa system and also provides machine learning and AI services to business customers.
Amazon’s cloud computing business, Amazon Web Services, provides an AI infrastructure that allows its customers to analyze data and incorporate AI into their existing systems. Amazon has also made its Amazon Q AI assistant generally available for software development and data analysis.
Taiwan Semiconductor Manufacturing (TSM): Taiwan Semiconductor Manufacturing is the world’s largest chipmaker and a global player in chip manufacturing for artificial intelligence. As AI grows, the need for robust computing chips will grow with it.
TSM is a mature company that continues to make chips for non-AI computer applications, so it may represent less risk than other pure plays on AI.
Arista Networks Inc. (ANET): Launched in 2008, Arista bridges the gap between startup and legacy tech companies. Arista is a networking equipment company that sells ethernet switches and software to data centers.
With the ethernet among the best options to power AI workloads, Arista is well-positioned to capitalize on its power to improve how we work, recreate, and learn.
Adobe Inc. (ADBE): Global workers have depended upon Adobe products for content creation, document management, digital marketing, advertising software, and services for years.
Among the older companies on our list of best AI companies to invest in, Adobe has infused most of its products and services with AI features, boosting its already impressive competitive advantage.
Recent performance has lagged behind our other best AI firms, but the company could be a bargain now. According to Morningstar, the company is significantly undervalued and holds a four-star ranking.
Best AI ETFs
Investing in professionally managed ETFs or mutual funds that hold shares in AI companies allows you to leave it to a fund’s professional managers to research and pick suitable AI companies. Through an ETF, you own a share of a portfolio of multiple AI stocks within a single investment.
iShares Exponential Technologies ETF (XT): XT is a large capitalization fund that includes 186 US and global stocks trying to disrupt the industry. With $3.4 billion in assets, XT hones in on the power of AI to automate, analyze, and create new ideas The fund spans the tech, healthcare, industrial, and financial sectors.
Defiance Machine Learning & Quantum Computing ETF (QTUM): This index AI fund brings artificial intelligence and machine learning to a range of industries. The fund replicates the BlueStar Quantum Computing and Machine Learning Index (BQTUM), which tracks 71 global stocks with multi- market capitalization.
The Defiance Machine Learning & Quantum Computing ETF captures returns of the companies at the forefront of next-gen disruptive technology and machine learning.
ROBO Global Robotics & Automation Index ETF (ROBO): This ETF invests in companies focused on robotics, automation, and AI, including growth and blend stocks of all market capitalizations.
How to Search for AI Investments
Buying individual AI stocks is more work for the investor. Given the multiple ways to invest in AI, the first step is to read about the industry to understand the various aspects of artificial intelligence.
Within the AI universe, there are pure plays and more conservative plays, and you’ll have to decide the type of exposure you want in this market sector. Once you have an idea of the parts of the AI market you want to invest in, you can perform traditional investment computational—both fundamental and technical.
Earnings forecasts: Earnings are a great way to judge a company’s performance, and AI companies with consistent and growing earnings should be looked at favorably. Many AI companies will be viewed as growth stocks, so earnings growth will be an important criterion for many investors.
Earnings releases tend to move AI stocks up or down sharply.
Annual reports: These reports provide important details about the company’s activities and future growth plans. The financial statements allow you to review the company’s debt-to-equity and other accounting ratios, which are used to make financial decisions about stocks.
Relative performance vs. the market: Relative performance is how an individual stock performs compared with an index or another stock. For newer AI companies, it’s best to compare their relative performance with similar companies.
Growth analysis: This deals with a company’s growth over time. You’ll examine earnings, market share, and other metrics to determine the company’s strength and prospects.
Analyst projections: Analyses and reports can be especially worthwhile if you’re new to the AI space. This volatile market has constant and new technological developments, and company prospects change much more quickly than in more mature industries.
Therefore, it’s good to gain the perspective of professional researchers who understand the overall AI space and the prospects of individual stocks relative to competitors.
Frequently Asked Questions (FAQs)
Is It Possible for Investors to Profit from AI?
AI is rapidly expanding, and the technology behind it seems ready to advance further and meet expectations for broader adoption across various businesses and real-world applications.
Similar to any technology demanding significant capital investment, AI presents numerous opportunities for investors to earn money, but new technologies also come with risks.
You’ll need to find the most suitable way to get involved without taking on too much risk. Options include more speculative direct AI investments in individual companies or ETFs and mutual funds that provide a portfolio of multiple companies in the AI space.
You can also consider investing in companies that are poised to grow their revenues as AI becomes more widely adopted across the economy.
How Can You Participate in AI Art Investment?
One of the most popular applications of generative AI is creating images. Users can describe an image they want to create, and an AI program can generate an image that matches that description—most of the time.
These AI programs utilize the user’s description along with images available globally to create the requested artwork for the user.
AI-generated artwork has been used by people of all ages and backgrounds. Once you’ve created AI art, you can sell it and/or purchase from others on AI art marketplaces. AI art can be collected as giclee prints, digital downloads, NFTs, and other formats.
It can be traded on certain crypto platforms and specific AI art websites. However, the profit and investment potential for AI art is still in its early stages and cannot be accurately determined.
How Can You Invest in AI Startups?
Startup companies are often founded in new and promising fields, such as AI and machine learning. These are typically companies that have been funded initially by venture capital investors and then taken public to capitalize on their initial investment and to raise more capital as the business expands its operations and begins offering its products to a wider customer base.
Many startup investments are only accessible to large accredited investors. Other platforms allow the public to invest small amounts in promising new ventures. You’ll need to sift through the offerings to find the AI startup companies.
While investing in startups can be risky, the rewards for investing in a successful startup company can be substantial. Examples of successful startup companies include Apple, Amazon, and Microsoft.
Is It Possible to Directly Invest in AI?
Certainly, you can directly invest in AI and machine learning by investing in individual stocks or in ETFs or mutual funds that focus on AI stocks.
Conservative investors seeking AI stocks to buy might consider established companies that are benefiting from AI processes, while aggressive investors can search for investments in direct AI companies. For AI investment ideas, check out the best AI stocks. This list is updated monthly.
The Bottom Line
Investing in AI in 2024 presents compelling opportunities for your portfolio. The technology continues to permeate the media, healthcare, automotive, finance, and other sectors.
However, you’ll have to navigate challenges that could include potential legal and regulatory changes, supply shortages, and the broader political and ethical considerations concerning the widespread deployment of AI systems and the ecological effects of powering them.
Similar to investing in the new internet and computing industries decades ago, the winners and losers can change rapidly.
Staying informed and selectively investing in companies prioritizing robust business models will be crucial for those looking to capitalize on the AI boom while mitigating risks.
AI stocks have experienced significant growth in 2024. NVIDIA, in particular, has attracted a lot of attention due to its substantial increase in value. In June 2024, it briefly surpassed Apple and Microsoft to become the world’s most valuable company.
However, there have been recent speculations that the excitement around AI might be exaggerated, or that geopolitical issues could hinder semiconductor development crucial to AI’s success. NVIDIA’s time at the top was short-lived, and by late July, its market cap had dropped below $3 trillion, falling behind Apple and Microsoft once again.
For those who believe in the long-term potential of AI, price pullbacks could be seen as buying opportunities, according to some analysts.
7 top-performing AI stocks
Here are the seven best-performing stocks in the Indxx Global Robotics & Artificial Intelligence Thematic Index, ranked by one-year returns. This list is updated on a weekly basis.
SoundHound AI Inc. (SOUN)
SoundHound AI develops voice-based AI products, such as a voice assistant for restaurants that enables customers to place orders, inquire about operating hours, and make reservations.
Apart from the food service sector, SoundHound creates products for the automotive and hospitality industries. The company has an impressive client roster, including Hyundai, Pandora, KrispyKreme, White Castle, Toast, and Square.
NVIDIA Corp (NVDA)
NVIDIA initially focused on 3D graphics for multimedia and gaming companies in 1993. The company also began developing AI applications as early as 2012. Today, NVIDIA remains at the forefront of AI and is engaged in the development of software, chips, and AI-related services.
Procept BioRobotics Corp (PRCT)
Procept BioRobotics designs medical robotics solutions for urology. The company offers two robotics systems: Aquablation therapy, which provides an alternative to surgery, and AquaBeam, a heat-free robotic therapy for treating symptoms related to benign prostatic hyperplasia.
What are AI stocks?
AI stocks are shares of companies involved in the artificial intelligence sector. The applications for AI are diverse, resulting in a wide range of AI stocks: Some companies create voice recognition software, while others develop pilotless aircraft.
According to Haydar Haba, the founder of Andra Capital, a venture capital firm that invests in AI companies, there are numerous publicly traded companies with substantial AI interests poised to benefit from the industry’s growth.
AI stocks typically fall into one of two categories: established technology companies that have invested in or partnered with AI developers, and smaller, experimental companies entirely focused on AI development.
Shares of small AI developers may appear to be the most “direct” investments in AI, but Michael Brenner, a research analyst covering AI for FBB Capital Partners, suggests that they might not necessarily be the best AI investments.
“Large language models require a significant amount of data and substantial capital to develop,” Brenner states.
Brenner highlights that small companies may innovate and create new models independently, but eventually, they will need to collaborate with a larger company possessing more infrastructure to run those models on a commercial scale.
“We are currently sticking with more of the mega-cap tech companies,” Brenner notes, referring to FBB Capital Partners’ AI portfolio.
How to invest in AI stocks
If you’re new to stock trading and interested in investing in AI stocks, the first step is to open a brokerage account.
Following this, you will need to determine the type of AI stock exposure you desire. Individual AI stocks have the potential for high returns but requiring assuming significant risk, upfront investment, and research efforts.
Another option is to invest in AI stocks through pooled exchange-traded funds that focus on AI.
