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AI will add $19.9 trillion to the global economy through 2030 – a remarkable 3.5% of global GDP.

The investment world has taken notice. Companies mentioned artificial intelligence almost 10,000 times during earnings calls in 2023. The numbers paint an impressive picture: Microsoft plans to invest $100 billion in data centers, while Goldman Sachs predicts global AI investments will reach $200 billion by 2025.

New investors might feel overwhelmed when trying to tap into these opportunities. The good news is that several investment options exist – from buying stocks directly to choosing ETFs, mutual funds, or investing in companies that build AI infrastructure.

This piece will show you practical steps to begin investing in AI technology in 2024. You’ll learn how to position yourself to benefit from this technological revolution.

What Makes AI a Unique Investment Opportunity

AI sits at the vanguard of technological development. It will reshape economies and industries in ways unseen since the internet emerged. The technology’s power to transform society matches the revolutionary changes brought by steam engines and electricity in earlier times.

The transformative potential of artificial intelligence

AI brings more than just automation to the table. This powerful general-purpose technology meets several crucial benchmarks. It works throughout the economy and keeps getting better. The technology stimulates innovation in connected fields and substantially improves productivity.

AI stands out as an investment chance because it’s versatile and accessible. Earlier technologies often worked in limited ways. Generative AI creates new, human-like output in fields of all types. Ground applications of this technology reach far and wide. Every industry and business function can tap into AI’s potential.

Numbers tell an amazing story—AI could add $2.6 trillion to $4.4 trillion yearly from just 63 analyzed use cases. These figures match or exceed the UK’s entire GDP in 2021 ($3.1 trillion).

Generative AI pushes artificial intelligence’s total effect up by 15% to 40% beyond older AI technologies. This multiplier creates substantial investment chances throughout the AI ecosystem.

AI’s economic effect across industries

Not all sectors will benefit equally from AI’s economic advantages. Banks, tech companies, and life sciences should see the biggest effects as a percentage of their revenues. Banks alone could gain $200-340 billion more each year by implementing generative AI.

Retail and consumer packaged goods could see even bigger gains at $400-660 billion yearly. These sectors might see productivity rise by 1.2% to 2.0% of annual revenues.

Four key areas make up about 75% of AI’s total potential value:

1. Customer operations – Revolutionizing customer experience and agent productivity
2. Marketing and sales – Enabling personalization at scale
3. Software engineering – Accelerating development cycles
4. Research and development – Improving innovation capabilities

Supporting industries benefit too. Data centers will need more than twice the electricity by 2026 compared to 2022. This creates investment chances in utilities and infrastructure providers.

Growth projections through 2030

AI market growth looks remarkable. Starting at $184 billion in 2024, global AI markets should reach $826 billion by 2030. Some experts think it might hit $1.339 trillion by 2030, growing yearly at 35.7%.

Looking at the bigger picture, AI might add up to $15.7 trillion to the global economy by 2030—more than China and India’s current combined output. About $6.6 trillion should come from better productivity, while $9.1 trillion might result from consumption effects.

Different regions will gain differently. China (26% GDP boost) and North America (14.5% boost) lead the pack. These regions might capture almost 70% of the global economic effect, worth about $10.7 trillion.

AI adoption still sits in its early stages, which excites investors. Despite all the buzz, only 5% of U.S. businesses (9% of jobs) use AI beyond basic applications in their products and services. Information and professional service companies use AI twice as much as others.

Low adoption rates point to huge growth potential. McKinsey’s Global Survey shows companies using AI in at least one business function jumped from 55% in 2023 to 72% in 2024. Generative AI saw even bigger increases.

Smart investors learn about these growth projections. They help spot promising market segments as this tech revolution unfolds.

Direct Stock Investments in AI Companies

Stock investments provide the most direct path to tap into the full potential of the artificial intelligence revolution. Stanford University’s analysis shows global corporate AI technology investments reached $934.20 billion from 2013 to 2022. These numbers demonstrate the big opportunities available in this field.

Pure-play AI stocks to think about

AI company investments fall into two main categories: pure-play AI companies focused solely on artificial intelligence and larger tech companies with substantial AI divisions.

Pure-play AI stocks give investors concentrated exposure to artificial intelligence technologies. Revenue for these companies flows mainly from AI-related products and services. Their stocks might show more volatility, but they offer greater growth potential to investors who can handle higher risk.

Nvidia leads the pack as a pure-play AI investment. The company dominates the GPU market needed for training and deploying AI models, with about 90% of data center GPU market share. This market position helps Nvidia benefit from the AI boom, as its data center operations now generate most of its revenue.

SoundHound AI offers another compelling pure-play option with its unique risk profile. The company specializes in audio AI technology and has built a portfolio of several hundred patents over its 20-year history. Though its market cap sits at $3.50 billion, SoundHound’s customer base includes many prominent brands, and it projects 166% sales growth.

Established tech giants with AI divisions

Large technology companies offer more stable investment choices with substantial AI exposure. These industry leaders have enough resources to fund AI research and implementation throughout their product lines.

Microsoft has become a pioneering AI company through strategic moves, including a $14 billion investment in OpenAI. AI capabilities now run through its entire product line—from Bing search and Office productivity software to Azure cloud infrastructure. The company’s commitment shows in its plans to invest $80 billion in AI-enabled data centers during fiscal 2025.

Alphabet (Google’s parent company) leads AI research through its Google AI division and DeepMind subsidiary. December 2023 saw the launch of its Gemini generative AI model, which now integrates across its products.

Amazon uses AI throughout its operations—from recommendation algorithms and marketplace search to its Amazon Web Services (AWS) cloud division. The company launched Alexa+, a more advanced version of its personal assistant, in February 2024. This upgrade uses state-of-the-art AI for better conversations and capabilities.

Meta Platforms (formerly Facebook) takes a unique approach by offering its AI technology free to the public to gain market share. Reports indicate the company plans a $200 billion data center campus for future AI projects.

How to research AI company fundamentals

Smart AI company investments require thorough fundamental research. This analysis helps you understand a company’s true value, growth potential, and competitive edge.

Start by breaking down the company’s AI solution and technology capabilities. Their approach should solve real problems and offer clear advantages over competitors. For pure-play AI companies, check what percentage of their revenue comes from AI activities. Higher percentages usually indicate stronger innovation commitment.

Product-market fit assessment comes next through customer demand and retention analysis. Companies that keep customers and show strong adoption rates typically have lasting business models. The company’s financial health deserves attention too, particularly its cost structure and funding sources.

Large tech companies require a close look at their AI initiatives. SEC filings often reveal AI investment strategies. These documents can show future directions—Nvidia’s February 2024 quarterly filing mentioned autonomous driving, medical imaging, and drug discovery.

Leadership teams need AI expertise to direct the fast-changing digital world effectively. Regulatory challenges also matter as government oversight of AI technologies grows. The Federal Trade Commission now looks into partnerships between generative AI companies and cloud service providers.

Professional analysts who understand the AI space provide valuable projections. Their reports help identify promising investments that match your risk tolerance and goals.

AI remains an emerging industry. The Washington Post reports that Wall Street giants question current AI investment sustainability. Analysts expect tech companies to generate only about a third of their $60 billion annual AI model spending in equivalent revenue.

Investing Through AI-Focused ETFs

AI ETFs provide a practical way into the booming AI sector without picking individual stocks. You can get immediate exposure to various companies involved in AI development through a single investment vehicle.

Benefits of ETF investing for beginners

New AI sector investors will find several advantages with ETFs:

Instant diversification: One ETF purchase gives you exposure to many companies instead of researching individual AI stocks. This approach helps reduce specific company risks that could affect your portfolio if you owned just a few AI stocks.

Lower entry barriers: You need less capital with ETFs to achieve diversification compared to building a stock portfolio. New investors find this accessibility perfect when they start exploring AI investments.

Risk mitigation: ETFs carry less risk than holding individual stocks because they spread investments across many companies. This becomes crucial in the AI sector where picking winners can be tough during its early development stages.

Long-term growth potential: The technology sector continues to innovate across industries. AI ETFs tap into this sustained demand for AI-driven products and services.

Simplified research process: You can review a few ETFs based on their holdings, expense ratios, and performance metrics instead of analyzing dozens of companies.

Top AI ETFs by performance and holdings

Investors often choose from these popular AI-focused ETFs:

Global X Robotics & Artificial Intelligence ETF (BOTZ) focuses on companies that benefit from robotics and AI adoption, including industrial robotics, automation, and autonomous vehicles. Its $2.70 billion in net assets makes it one of the largest AI ETFs, offering great stability and liquidity.

Global X Artificial Intelligence & Technology ETF (AIQ) targets companies that benefit from AI technology development and use. The fund includes hardware providers that aid AI in big data analysis. Tencent, Alibaba, Apple, and Meta stand out among its notable holdings.

iShares Future AI & Technology ETF (ARTY) tracks U.S. and international companies that benefit from AI growth. The fund holds 50 companies exposed to generative AI, data centers, software, and AI value-added services. Super Micro Computer, Broadcom, and Nvidia lead its top holdings.

WisdomTree Artificial Intelligence and Innovation ETF (WTAI) targets companies in AI and innovation themes across global markets.

Invesco AI and Next Gen Software ETF (IGPT) builds on the STOXX World AC NexGen Software Development Index. The fund includes about 100 global companies that generate revenue from software and AI.

How to compare AI ETF options

Your portfolio needs careful ETF evaluation based on these factors:

Holdings composition: Look at the fund’s stocks and check how many are true AI companies. More core AI businesses in a fund means better exposure to the sector’s growth.

Expense ratios: Annual fees differ between ETFs. These fees affect your long-term returns, so finding reasonably priced options matters.

Performance history: Past performance provides context but doesn’t guarantee future returns. Many AI ETFs have short track records because the sector is relatively new.

Investment strategy: Rules-based indexes cost less but offer less flexibility than active management. Each approach has its merits based on market conditions.

Geographic exposure: U.S. companies dominate some ETFs while others go global. ARTY puts 83% in domestic stocks and spreads the rest across Japan, Taiwan, and France.

Methodology: Each ETF picks holdings differently. Some use proprietary methods combining transcript analysis and sector scores, while others follow established indexes.

You might want to invest in several AI ETFs to spread risk across different AI categories and approaches. The Invesco QQQ ETF (QQQ) offers another option. It tracks the Nasdaq-100 and holds many big tech companies heavily involved in AI.

Alternative Ways to Invest in AI Technology

Beyond direct stocks and ETFs, smart investors are learning about different ways to invest in artificial intelligence. These options give unique benefits, such as getting into early-stage companies and specialized AI investments you can’t find in public markets.

AI-focused mutual funds

AI mutual funds are available as an entry point for investors who want professionals to manage their AI investments. These funds combine money from multiple investors to buy AI-related stocks, bonds, and other securities. This gives you instant diversification across the AI world.

The best part about AI mutual funds is their professional management. Fund managers utilize extensive research and market analysis to pick which AI-related securities to buy and sell. This saves you time and effort you’d spend analyzing individual companies. On top of that, it gives you diversified exposure across multiple AI stocks, which helps alleviate the risks in this faster evolving sector.

AI-based mutual funds come in three categories:

• Funds investing in companies creating new AI products or services
• Funds with portfolios containing at least 25% investments in firms heavily investing in AI research and development
• AI-managed mutual funds that use artificial intelligence to select securities

Before investing in AI mutual funds, think over their fee structures as they can affect long-term returns by a lot. Take a closer look at historical performance, but note that past results don’t guarantee future returns, especially in an emerging field like AI.

Venture capital opportunities

Venture capital has become a major force in AI funding. The year 2024 was a big deal as it means that 50.8% of global VC funding by value went to AI-focused companies—almost double its share from the same quarter in 2023. This shows growing investor confidence in AI’s potential to revolutionize.

The numbers tell an impressive story: global VC funding for AI startups reached $131.50 billion in 2024, jumping 52% from the previous year, while funding for non-AI startups dropped by about 10%. This difference shows how exceptional AI investments are growing in private markets.

North America leads the regional distribution of AI venture funding with nearly a third of deals and 60% of VC investment value going to AI startups in 2024. Europe comes in second, with about a quarter of VC funding rounds going to AI startups.

Individual investors now have several ways to get into venture capital, which traditionally needed extensive networks or substantial wealth. All the same, here are the options:

1. Online alternative investment platforms that find and select AI investment opportunities
2. Pre-IPO investing in companies like OpenAI, Anthropic, and Databricks through specialized platforms
3. Venture capital firms with lower minimum investments focused on early-stage AI companies

Many platforms have lowered their minimum investment requirements, though most still need accredited investor status.

Private equity options for accredited investors

Private equity gives accredited investors another way to invest in AI technology. These investments often let you get into companies earlier or access specialized AI applications not yet in public markets.

Private equity and venture capital-backed investments in generative AI companies more than doubled in 2023, hitting $2.18 billion compared to $1.00 billion the previous year. This happened despite the overall drop in M&A activity. The year 2024 started strong with $250.00 million in private equity-backed AI investments in just six weeks, beating the first-quarter 2023 total.

Accredited investors (those with net worth over $1 million excluding primary residence, or income above $200,000 individually or $300,000 jointly) have several options:

Platforms like Hiive and UpMarket now let accredited investors buy shares in private AI companies such as Anthropic, OpenAI, and Perplexity. These platforms connect investors with employees, VCs, or angel investors who want to sell shares.

Private equity firms focus more on generative AI implementations in four main areas:

• Code generation tools to improve developer productivity
• Content generation for marketing materials
• Human engagement via bots for customer service
• Virtual knowledge workers for data analysis

Valuations in this sector can reach astronomical levels because of intense competition from strategic buyers. Some major private equity firms like Blackstone are focusing more on “derivative plays,” including investments in data center infrastructure that supports AI operations.

Note that alternative investments usually come with higher risk, longer time horizons, and lower liquidity than traditional investments. These investments should only be part of a well-diversified portfolio.

The AI Infrastructure Play: Supporting Companies

AI companies aren’t the only driving force behind the AI revolution. The critical infrastructure that makes these technologies possible plays a crucial role. Investing in companies that build and maintain this infrastructure could be a lucrative way to capture AI’s growth.

Semiconductor manufacturers

Semiconductor chips form the foundation of AI technology, with several key players dominating this essential market. TSMC (Taiwan Semiconductor Manufacturing Company) plans to expand its U.S. investment by $100 billion, which brings its total American investment to $165 billion. The company will build three new fabrication plants and two advanced packaging facilities that support AI applications.

Nvidia holds about 90% market share in data center GPUs, making it the dominant force in AI chips. Tech giants and car manufacturers use the company’s AI chips extensively. AMD has launched its third generation commercial AI mobile processors that deliver triple the performance of previous generations. Intel’s share price has risen 21.1% in 2025 as of February, partly due to rumors that TSMC might take a stake in its chip production operation.

Investors looking at emerging players should watch companies like Groq, Cerebras Systems, and SambaNova Systems. These companies are developing specialized AI accelerators that could challenge current manufacturers as AI needs grow.

Cloud computing providers

Major cloud platforms have become essential AI infrastructure providers by offering specialized hardware, software frameworks, and AI services. Google Cloud works with manufacturers like NVIDIA, Intel, and AMD to provide AI accelerators, along with its own TPU (Tensor Processing Unit) technology. The company’s Google Kubernetes Engine can support up to 15,000 nodes in a single cluster, which gives unmatched scalability for AI workloads.

Microsoft Azure has become an AI infrastructure leader through its Azure OpenAI Service and detailed security features. Users can access over 1,700 foundation models from creators like Microsoft, OpenAI, Hugging Face, Meta, and Cohere. Microsoft plans to invest around $80 billion on data center construction in 2025.

Cloud providers now use AI to power automated systems that deliver their services efficiently. These platforms handle provisioning, batching, and tuning hyperscale systems automatically, which reduces the workload for human operators.

Data center operators

AI data centers are different from traditional facilities because of high-intensity AI workloads’ extraordinary demands. These specialized centers must have advanced compute architectures, networking equipment, and better cooling capabilities. Goldman Sachs projects that AI will cause a 165% increase in data center electricity demand by 2030.

The investment potential in this space is huge. The global hyperscale data center market should grow from $320 billion in 2023 to $1.44 trillion by 2029. The spending on procurement and installation of mechanical and electrical systems for data centers will reach $250 billion by 2030.

Colocation providers offer another investment opportunity. These companies modernize existing data centers and build new ones, then lease capacity to hyperscalers who can’t keep up with demand. Companies that offer build-to-suit development services make particularly attractive partners for major tech companies.

Infrastructure-focused stocks have remained strong during market changes. MasTec’s business has grown substantially from the AI-powered data center boom as a leading provider of design, construction, and maintenance services in the wireless network space. Constellation Energy and BWX Technologies have also become key players in supporting AI infrastructure’s massive power requirements.

These infrastructure companies will remain essential to enabling continued breakthroughs as the AI revolution moves forward. This creates substantial potential returns for investors who think ahead.

Practical Steps to Start Investing in AI

You already know the different ways to invest in AI. The next step is to start making your first investment. A well-planned approach will help you guide through the AI investment world more effectively.

Setting up an investment account

You need an appropriate investment account before you can invest in artificial intelligence. Standard brokerage accounts from online platforms give you access to AI-related stocks and ETFs. The right platform should meet these important criteria:

• Research capabilities and educational resources about AI sectors
• Commission structures and fee schedules
• User-friendly interface and mobile accessibility
• Available investment options (stocks, ETFs, mutual funds)
• Customer service quality and technical support

New investors often ask “how do I invest in AI.” Traditional online brokerages like Schwab, Fidelity, or interactive brokers offer detailed platforms with educational resources. You might prefer an advisory account where investment professionals research and select suitable AI companies on your behalf.

Creating an AI investment budget

The amount you invest in AI needs careful thought. AI represents a high-risk sector with substantial ups and downs, yet it has the power to revolutionize industries.

Studies show you should only put a small portion of your portfolio in AI stocks. Look at your overall financial health, including emergency savings and retirement planning, before you put money into AI investments.

Your risk tolerance and financial goals should shape your budget. Expert advice suggests starting with modest investments—around $20,000 for your first AI exposure. This lets you “cut your teeth, test what works for your business, increase employee AI fluency, and lay the groundwork for future investments”.

Making your first AI investment purchase

Detailed research becomes vital as you look at specific investments. You should understand artificial intelligence’s various aspects and find segments that match your investment goals.

Pick what suits you best:

• Pure-play AI companies directly developing AI technologies
• Tech companies with proven track records implementing AI solutions
• Infrastructure providers supporting AI development
• Diversified exposure through ETFs or mutual funds

AI markets often see sharp price swings after earnings releases. Look closely at company financial statements, earnings growth trends, and competitive positioning before buying. Professional analyzes help greatly in this fast-changing field where “company prospects change much more quickly than in more mature industries”.

Note that AI investing success depends on continuous learning to understand both the potential and limitations of AI-based products. These practical steps will give you more confidence as you start investing in AI.

Common Mistakes Beginners Make When Investing in AI

The surge in artificial intelligence has new investors rushing into the space without proper preparation. Learning what not to do can be as valuable as knowing the best practices in the AI investment world.

Chasing Trends Without Clear Objectives

Most investors head over to AI without defining their goals. They start a journey without a map. This scattered approach wastes resources and effort. Harvard Business Review reports that AI projects fail at about 80% – twice the rate of corporate IT project failures from ten years ago.

Overestimating AI Capabilities and Returns

AI technology shows great promise but isn’t magical. New investors often misunderstand its limits and expect too much too soon. Research shows that 60% of companies don’t see substantial returns on their AI investments. This creates an unfavorable cost-to-benefit ratio. The gap between expectations and reality often leads investors to abandon promising long-term positions too early.

Neglecting Due Diligence

The buzz around AI tempts investors to skip basic research. Tech media site CNET discovered that 41 of its 77 AI-generated articles had factual errors in 2023. This shows why investors must research thoroughly before putting money into any AI company.

Key overlooked factors include:

• Fee structures that eat away at returns over time
• Ethical implications and regulatory requirements affecting company values
• Data quality problems that hurt AI system performance

Succumbing to Emotional Decision-Making

Market swings often push beginners into making snap decisions. They drop their investment strategy during market panic or excessive optimism. Success in AI investing demands a steady viewpoint through hype cycles and market corrections.

Only when we are willing to spot these pitfalls can we approach AI investing with confidence and discipline. This awareness substantially improves your chances of long-term success in this dynamic yet challenging sector.

FAQs

Q1. How can a beginner start investing in AI stocks?
To begin investing in AI stocks, open a brokerage account with a reputable online platform. Research different AI sectors and companies to determine your investment focus. Consider starting with AI-focused ETFs for diversification before moving to individual stocks. Set a budget, keeping in mind that AI is a high-risk sector, and only invest what you can afford to lose.

Q2. What are some promising AI stocks to consider in 2024?
While individual stock performance can vary, some AI stocks gaining attention include Nvidia for its dominance in AI chips, Microsoft for its strategic AI investments, and Alphabet (Google) for its advanced AI research. Other companies to watch are AMD for AI processors and Palantir for data analytics. Always conduct thorough research before investing in any stock.

Q3. How can I invest in AI without picking individual stocks?
For those preferring a more diversified approach, AI-focused ETFs offer exposure to multiple AI companies through a single investment. Popular options include the Global X Robotics & Artificial Intelligence ETF (BOTZ) and the iShares Robotics and Artificial Intelligence Multisector ETF (IRBO). These funds provide instant diversification across various AI-related companies.

Q4. What are some common mistakes to avoid when investing in AI?
Common pitfalls include chasing trends without clear objectives, overestimating AI capabilities and returns, neglecting due diligence on companies and technologies, and making emotional decisions based on short-term market fluctuations. It’s crucial to maintain a long-term perspective and thoroughly research before investing.

Q5. Are there alternative ways to invest in AI beyond stocks and ETFs?
Yes, alternative investment options include AI-focused mutual funds, which offer professional management of AI-related securities. For accredited investors, venture capital and private equity opportunities provide access to early-stage AI companies. Additionally, investing in companies supporting AI infrastructure, such as semiconductor manufacturers and cloud computing providers, offers indirect exposure to the AI sector.