The tech industry has been excited about artificial intelligence (AI) innovations for years, but the introduction of ChatGPT for consumers has sparked much more interest among the broader public, including investors. has been submitted.
Ryan Jacob, Portfolio Manager, Jacob Internet Fund, said:
But while it’s clear that AI applications have the potential to significantly accelerate the pace of technological change and disruption in many industries, the best way to invest in the burgeoning AI industry lies in the more nuanced differences. there is.
If your client is asking you about investing in AI, here’s what you need to know to be smart about it.
Artificial Intelligence: An Overview
Artificial intelligence uses computational power to simulate human thinking to solve problems or complete tasks. ChatGPT is a form of “generative AI”, which means that it doesn’t just analyze data, it uses predictions about that data to “generate” something. In this case, we use AI to answer questions using data collected from millions of pages on the internet. You don’t actually “know” anything, but you can predict the answer to a question by understanding the relationships between words.
However, AI and deep learning models have many use cases beyond simple text-based responses. AI is part of the technology driving innovation in self-driving cars and cloud computing, and machine learning is helping everything from doctors seeking help diagnosing and planning treatment for patients to discovering cost savings in manufacturing plants. can be used for
Mike Loukas, Principal and CEO of TrueMark Investments, said: “It has now permeated so many levels of business, society, and our daily lives. I think B2B applications will become a more important part of investment portfolios as they become more useful tools for businesses.” .”
Is AI a Good Investment?
Artificial intelligence has the potential to be a good investment, but it’s important to understand that it’s a very young industry. As such, it’s difficult to say with certainty which stocks are likely to benefit most from his AI capabilities.
That said, most large tech companies have invested in AI and see their dominance in this space as key to maintaining their competitive edge. The challenge for investors, of course, is determining which companies will gain (or lose) the most as AI matures.
Why AI is hot right now
With the general availability of ChatGPT on November 30, 2022, interest in AI has increased. However, the increased interest may also reflect continued volatility in the technology market, with many investors looking for the next big innovation to drive growth in the sector.
Microsoft invested $1 billion in ChatGPT creator OpenAI in 2019 and is also investing heavily in building AI capabilities and tools into the Bing search engine. And while Bard, Google’s AI tool, got off to a more rocky start after generating erroneous answers in a demo, the search giant’s focus on his AI shows the importance of technology. showing gender.
What is the future of AI?
As more consumers and businesses transact online, there are more and more opportunities to incorporate technology into our daily lives. According to the 2022 IBM Global AI Adoption Index, approximately 44% of companies are currently working to incorporate AI into their existing applications and processes.
As artificial intelligence use cases continue to expand, the technology itself will improve as well. Today ChatGPT, Bard, and others are prone to factual errors, but developers may find ways to make the technology more trustworthy.
“ChatGPT is just one manifestation of artificial intelligence, but it has a cool element,” says Loukas. “But when you start looking at investments, you have to separate the topic from the business model.”
Which AI companies should I invest in?
Investing in AI can take many forms, some of which are direct. In addition to focusing on companies building AI, investors may consider allocations to companies that may not be AI-centric but whose business models are likely to benefit from advances in AI technology. not.
Other ways to invest in the coming AI boom include investments in adjacent industries, such as companies that specialize in cybersecurity, data processing, or chip manufacturing, said Loukas, as AI continues to grow. All three are required for
To that end, Jacob sees companies like Cloudflare, which specializes in edge computing, MongoDB, a developer database platform, and companies in the Internet of Things (IoT) space as having many advantages over pure AI companies. said that
Companies leading AI today
There aren’t many public companies devoted to artificial intelligence, but the biggest technology company investment to date is a bet on AI. Microsoft, Google, and companies like Amazon, Apple, and IBM are all working hard to improve their own AI technologies and help improve their products and services.
“Practically every major internet company is putting resources into this, and that’s where the most innovation is happening,” says Jacob. “But the question is how much their AI development will make a big difference in terms of improving returns. That’s part of the challenge.”
Despite the recent turmoil in the industry, such companies have also remained cash-rich, allowing small companies to invest in startups if they believe they have the intellectual property or technology that can enhance their business. Large companies also have the human capital and deep financial resources needed to scale their technology quickly.
Investors interested in mid-cap AI stocks may turn their attention to companies like C3.ai, an enterprise AI development platform. Or his BigBear.ai, an intelligence analytics company.
Electric and self-driving cars may also offer opportunities for investors to bet on AI. Companies at the intersection of these industries and AI include his SES AI, a battery manufacturer, and Argo AI, which builds the infrastructure needed for self-driving cars.
AI startups to watch
For investors without deep technical expertise, it can be difficult to distinguish between the many AI startups vying for space. Building AI is a money-intensive business, so many startups may simply go out of business or be acquired by big companies.
Additionally, many AI startups are opening their doors to private investors. About a third of generative AI investments have yet to raise equity funding, and more than half are still in series A, according to CBInsights analysis. For example, a private investor cannot buy her OpenAI shares directly.
For investors who want to stay diversified but also invest in AI, Exchange Traded Funds (ETFs) may offer a solution. Experts warn investors to take a close look at her AI-focused ETF fund to understand exactly what they’re buying. Some funds that appear to be AI-focused may resemble rebranded technology funds.
It is also important to understand how managers constructed their funds and how they evaluated potential investments. Note that while there are many of his ETFs that invest in AI, there are also a growing number of ETFs that use AI to build portfolios in other sectors.
How to start investing in AI
As with any investment, it is important that investors exercise due diligence to ensure that they have researched the company and its competitors before purchasing stock in the company. Therefore, her financial adviser should be prepared to answer questions from clients in this regard.
You don’t need a deep understanding of the technology that powers AI, but you do need a basic understanding of the business itself and how to differentiate and ultimately generate profit in a very expensive, crowded and competitive space. .
Joe Quinlan, managing director and head of market strategy at Bank of America Private Bank’s Chief Investment Office, likens the current investment climate to the early days of dot-com investing. Some young companies, such as Amazon, grew into powerhouses during that era, but subsequent bankruptcies wiped out many more.
“[There were] At the time, many companies had no revenue and had great marketing stories, but they weren’t going the other side,” says Quinlan. “We know we are on the cusp of new innovation right now, and venture capitalists are funding it. Be careful if you do.”
Quinlan said that while the pace of innovation is fast, it may not be as fast as some investors hope to generate returns.
“We are accelerating,” he explains. “But we’re talking years, not quarters.”
What should financial advisors know about investing in AI?
When talking to clients about investing in AI, it’s important to understand that while AI is a potentially transformative technology, the industry is still in its early stages. That said, the opportunities are many, especially for those looking to look beyond simple pure AI investments.
Important AI terms to know
For more AI terminology, see the Artificial Intelligence Glossary compiled by ThinkAdvisor’s sister brand, LegalTech News.
Conversational AI: Technologies that allow users to “talk” to technology by using large amounts of data, machine learning, and natural language processing to recognize text and voice input and mimic human interaction. Conversational AI acts as the artificial “brain” behind some chatbots.
Generative AI: A category of AI systems containing large-scale language models that can independently create unique and novel content in the form of text, images, audio, etc., based on previously trained data.
GPT: Generative Pre-trained Transformer; Prefix for various generations of large-scale language models from OpenAI. For example, GPT-3 is his GPT model of the 3rd generation. GPT-1 was released in June 2018. GPT-2 was released in February 2019. GPT-3 was released in June 2020. GPT-3.5 will be released in March 2022, and the underlying model has been rolled out over his year. GPT-5 was released on March 14, 2023.
Machine learning: A broad field of AI concerned with “teaching” AI systems to perform tasks, understand concepts, and solve problems in a way that mimics intelligent human behavior, and more becomes progressively more accurate as it is trained on data from
Robotic Process Automation (RPA): A type of business process automation, also known as software robotics. It enables humans to define a set of instructions to quickly and error-free perform a large number of repetitive human tasks. RPA technology is similar to AI, but it is not a form of AI.
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