New York – As we enter 2024, the artificial intelligence sector continues to evolve rapidly, offering both opportunities and challenges for investors. While 2023 saw breakout success for companies like Nvidia, other AI stocks are positioned for gains this year amid a shifting economic landscape.
Leading chipmaker Nvidia had a banner 2023, largely thanks to surging demand for its products as AI adoption accelerated globally. However, many Wall Street analysts say the AI boom still in its early innings, with some of Nvidia’s top rivals ready to make up ground in 2024.
This article will analyze several AI stocks that could outperform this year, as the AI revolution transforms industries from healthcare to transportation. We’ll also look at key factors driving growth, along with potential risks facing the sector.
The AI Investment Thesis
The bullish case for AI stocks is centered on the explosion of AI use cases across the economy. Tech giants and startups alike are leveraging AI to improve efficiency, personalize products and services, and enable new innovations.
According to a recent McKinsey report, AI could create $13 trillion in global economic value by 2030. PwC estimates it could contribute over $15 trillion to the world economy by 2030.
“AI adoption is still in the very early stages,” said Jay Klauminzer, tech analyst at RBC Capital. “Less than 10% of companies are utilizing AI technology so far. As more industries deploy AI systems over the next decade, it will rapidly transform consumer experiences and business operations.”
The pandemic accelerated AI adoption, as companies deployed more automation to offset labor shortages and improve productivity. But we’ve still only scratched the surface of AI’s potential.
As AI becomes more ubiquitous, demand for specialized AI chips and software will surge. This creates a massive growth runway for Nvidia, AMD, Microsoft and other leading AI vendors.
However, tech valuations remain volatile amid rising rates and macro uncertainty. This means AI stocks could see bigger swings in 2023, even as their long-term outlook appears strong.
“AI will be one of the most disruptive technologies over the next 20 years,” said Morgan Stanley analyst Joseph Moore. “But investors need to separate the hype from reality – it will take time for many AI applications to reach scale.”
Let’s analyze some of the top AI stocks positioned for gains in 2024 and beyond.
Nvidia – The AI Chip Leader
Nvidia (NVDA) solidified its leadership in AI chips during the pandemic, as demand for its graphics processing units (GPUs) skyrocketed. The company’s GPUs power many AI applications, from natural language processing to computer vision.
In 2023, Nvidia continued to see surging data center revenue, which includes sales of its flagship A100 and new H100 AI chip. Data center sales leapt 43% in its most recent quarter.
“Nvidia has a multi-year head start in AI hardware,” said Bank of America analyst Vivek Arya. “Its CUDA software platform has become the standard for powering AI workloads.”
The firm estimates Nvidia’s data center business could almost triple to $50 billion in annual sales by 2026. Its gaming chips also utilize AI to boost graphics.
Despite its premium valuation, Nvidia stock rallied over 60% in 2023. However, shares have pulled back over 10% in January amid a sector rotation out of high-growth names.
Nvidia won’t maintain 2023’s meteoric rise this year. However, its leading position in AI chips and computing platforms gives it an edge as more industries adopt AI. With strong secular tailwinds, Nvidia remains a smart long-term bet on AI.
Advanced Micro Devices – The Top Challenger
Advanced Micro Devices (AMD) is emerging as Nvidia’s chief rival, leveraging its edge in central processing units (CPUs). AMD’s CPU market share has surged in recent years, powering many data centers and PC/laptop markets.
In 2023, AMD continued gaining share in PCs and servers, disrupting Intel’s dominance. The company expects its data center sales to rise over 60% in 2023, though it trails Nvidia in AI chip performance.
AMD plans to challenge Nvidia more directly with two key moves in 2024:
- Releasing next-gen mi300 data center GPUs optimized for AI workloads. Early benchmarks show these chips outpace Nvidia’s A100 GPUs for some AI uses.
- Closing its acquisition of Xilinx. This $50 billion deal gives AMD new capabilities in FPGAs and adaptive SoCs used for AI acceleration.
“With Xilinx, AMD can attack Nvidia from multiple angles,” said Susquehanna analyst Christopher Rolland. “Its unified CPU/GPU/FPGA roadmap will be formidable.”
AMD stock retreated in early 2024 amid the tech downturn. But its savvy M&A, solid execution and exposure to data center/AI make it a compelling rebound play. If upcoming GPUs and Xilinx integration go smoothly, AMD could significantly eat into Nvidia’s lead this year.
Broadcom – Software & Infrastructure Play
While Nvidia and AMD battle it out in AI chips, Broadcom (AVGO) provides crucial software infrastructure and tools needed to develop and run AI applications.
The company produces a broad range of semiconductor and software products used in data centers, networking, enterprise storage, cybersecurity and industrial markets. It provides the picks and shovels that support the AI gold rush.
In November, Broadcom closed its blockbuster $61 billion acquisition of VMware, a leading provider of cloud computing and virtualization software. This deal expands Broadcom’s enterprise software capabilities as companies accelerate their digital transformations.
“The VMware deal strengthens Broadcom’s position in next-generation infrastructure,” said KeyBanc analyst John Vinh. “VMware’s platform will enable enterprises to better optimize networks, clouds and edge locations to support AI and other advanced workloads.”
Broadcom expects the VMware acquisition to drive mid-single digit revenue growth in its infrastructure software segment in fiscal 2023. Management sees AI, cloud computing, 5G networks and digital transformation fueling its long-term growth.
The stock trades at 13.5 forward earnings, reflecting its mature financial profile. But Broadcom’s enviable cash flows, dividend growth and strategic M&A make it a core AI infrastructure play.
Microsoft – Cloud Software & Services
With Azure, Microsoft (MSFT) already operates one of the largest cloud platforms optimized for AI workloads. It offers robust toolsets for developing and managing AI apps on Azure.
In 2023, Microsoft made waves by investing billions in OpenAI, the startup behind viral chatbot ChatGPT. Microsoft plans to integrate OpenAI throughout its consumer and enterprise products, potentially revolutionizing search, customer service, creative content and more.
“Microsoft’s partnership with OpenAI has incredible potential to enhance its cloud value proposition,” said Wedbush analyst Dan Ives. “Its army of Azure developers can now tap into ChatGPT and Dall-E to build the next-generation of AI apps.”
Importantly, Microsoft is democratizing access to AI through Azure OpenAI Services. This levels the playing field so companies of all sizes can leverage powerful AI capabilities like natural language processing.
Microsoft’s diversified product ecosystem, massive cloud infrastructure and ability to attract top AI talent give it an edge as AI transforms business and society. Its stock trades at a reasonable 25 forward earnings with double-digit revenue growth.
Meta Platforms – Social Media Focus
Meta Platforms (META), parent of Facebook, Instagram and WhatsApp, is laser-focused on infusing its social media platforms with cutting-edge AI technology.
In late 2022, Meta open-sourced part of its Large Language Model (LLM) project, a more powerful version of GPT-3. The company is leveraging LLMs to improve ad targeting, content recommendations, language translation and moderation on its apps.
Meta is also developing AI virtual assistants and a universal speech translator for its metaverse platform. It envisions Lifelike digital avatars capable of fluid conversations in the near future.
On the hardware side, Meta aggressively procured Nvidia’s flagship H100 GPUs as it builds out its AI infrastructure. It faces near-term ad headwinds, but CEO Mark Zuckerberg believes AI can reinvigorate user growth over the long haul.
“AI will unlock a lot of opportunities on our roadmap to help build the metaverse,” said Zuckerberg.
Meta stock trades at an attractive 15 forward earnings after plummeting 60% in 2022. Its heavy AI investments and potential to disrupt social media keep it relevant. If Meta can re-accelerate revenue growth, the stock could rebound sharply after its massive underperformance.
Intel – The CPU Comeback Kid?
Left for dead by many investors, Intel (INTC) aims to revive its fortunes in 2024 behind new CPUs optimized for AI.
Long the leader in PC and data center processors, Intel lost share to AMD in recent years due to product delays and manufacturing issues. However, the chip giant is banking on three key moves to reestablish its AI bona fides:
- Launching its 13th Gen “Raptor Lake” CPUs with built-in AI accelerators call Intel Deep Learning Boost. These processors target PC gamers, creators and AI developers.
- Releasing new Sapphire Rapids data center CPUs tailored for AI-intensive workloads like machine learning and deep learning.
- Leveraging the Tower acquisition to bolster its foundry services and produce new infrastructure-on-chip silicon for 5G networks. These chips enable high-performance edge computing critical for AI.
“We will use our manufacturing muscle to foundry the chips powering the AI ecosystem,” said Intel CEO Pat Gelsinger.
After plunging 50% in 2022, Intel stock trades at just 10 forward earnings. Its dominant PC franchise and revamped capacity investments provide upside if new CPUs gain traction. Intel appears undervalued if its AI-focused chips can start regaining market share in 2024 and beyond.
Nvidia, AMD, Microsoft and Meta Platforms belong in most long-term AI-focused portfolios. But Intel’s depressed valuation and turnaround potential makes it an intriguing value play on AI.
Snowflake – Unlocking Value From Data
Snowflake (SNOW) operates a leading cloud data platform that empowers companies to optimize their data analytics. It offers a “single source of truth” for storing, processing and analyzing data across complex environments.
This data foundation lets customers apply AI to gain valuable insights for their business – from predictive demand forecasting to sentiment analysis. Snowflake also partners closely with all major cloud providers like AWS, Google Cloud and Azure.
“Snowflake sits at the center of how enterprises access, govern and get value from their data,” explained Oppenheimer analyst Ittai Kidron. “Its cloud-agnostic platform future-proofs their analytics architecture as AI workloads become more distributed.”
In Q3 2022, Snowflake’s product revenue soared 67% to $688 million. Its efficient consumption-based pricing model helps retain customers. Though unprofitable currently, Snowflake expects to generate free cash flow next year.
The stock has fallen from a peak of $400, making for a compelling entry point. As AI drives more real-time data analytics, Snowflake enables customers to execute data-driven decisions faster. Its innovative technology and partnerships give it an edge in enterprise data management.
Amazon – The Sleeping Giant
It’s easy to overlook Amazon (AMZN) in the AI space, with the e-commerce juggernaut facing economic uncertainty and its cloud division maturing. But behind the scenes, Amazon is making big moves in AI that could pay dividends down the road.
Much of Amazon’s AI focus targets improving operational efficiency, including:
- Automating fulfillment with warehouse robots
- Optimizing logistics and delivery routes with machine learning
- Personalizing recommendations and search results for shoppers
- Improving supply chain forecasting and inventory management
However, Amazon aims to be more than a passive AI adopter. It recently launched an “AI Ready” program to provide AI/ML training to 2 million Amazon employees by 2025.
The company wants to upskill workers to handle more advanced roles as AI transforms its business and industry. This focus on inclusivity could help Amazon retain talent as the AI revolution reshapes the labor force.
Amazon Web Services remains the cash cow funding these initiatives. AWS offers robust AI services like SageMaker, Lex, Rekognition and Kendra for building intelligent apps on its cloud platform.
If Amazon sustains momentum in e-commerce and cloud, its stealthy AI investments could bear fruit down the road through new revenue streams, higher productivity and cost savings. Patience will be required, but discounting Amazon’s AI potential is a mistake.
Key Trends Driving AI Stocks
Looking ahead, several technological and economic trends will propel growth for AI stocks:
- Surging data volumes requiring automated analysis
- Maturing machine learning algorithms and models
- Improved AI silicon performance and efficiency
- Transfer learning enabling quicker development
- Multimodal AI mimicking the human experience
- Democratization making AI more accessible
- Nearly every industry seeking AI solutions
- Younger generations embracing AI-enabled apps
According to Bain & Co., enterprise AI software spending is on pace to exceed $500 billion annually by 2030. We’re still in the early phase where AI investments are focused on pilot projects and proofs-of-concept.
As more companies move AI systems into production environments at scale, software and infrastructure demand will take off.
Most experts agree we’ve only scratched the surface of AI’s potential across healthcare, manufacturing, transportation, agriculture, retail, marketing, fintech, security and more. That creates a very long growth runway for AI pure-plays.
Key Risks Facing AI Stocks
However, AI stocks face risks including:
- Extended valuations and profitability concerns for software pure-plays
- Competition from both large and startup vendors
- Talent shortages in key areas like data science and machine learning
- Potential for biased data and algorithms
- Privacy and security vulnerabilities
- Public mistrust limiting adoption of consumer AI
- AI model interpretability and explainability challenges
- Regulatory uncertainty as governments catch up
Many promising AI startups burn cash rapidly developing new models and applications. High labor costs and intense competition also create margin pressures.
Meanwhile, missteps like biased algorithms or security lapses could derail progress. And most AI systems remain “black boxes”, sparking concerns over accountability and ethics.
Markets often get carried away with technological hype-cycles. While AI will ultimately transform business and society, the road will be bumpy. Investors should temper expectations and not underestimate risks facing AI companies.
Outlook for AI Stocks
The AI revolution has clearly arrived, but we’re still in the early innings of adoption and deployment. As AI becomes further embedded into business processes and consumer technologies, demand for AI software, infrastructure and services will accelerate.
The leading AI pure-plays like Nvidia and Microsoft warrant premium valuations based on their innovative capabilities and expansive reach. However, more attractive buying opportunities may emerge in former leaders like Meta Platforms or mature players like Intel that already have scale.
Savvy investors should build diversified AI stock portfolios combining mega-cap innovators, specialized mid-caps, and cyclical value plays with turnaround potential. Staying disciplined on valuation and monitoring the competitive landscape for disruption will be critical in this fast-moving arena.
The rewards for AI’s pioneers and enablers should remain substantial over the next decade. While market turbulence lies ahead, the smartest AI investments made today could look prescient in hindsight.
