5 Best AI Stocks to Buy Today
Company (Ticker) | 12 Week Price Change | Forward PE | Price | Proj EPS Growth (1 Year) | Projected Sales Growth (1Y) |
---|---|---|---|---|---|
Micron Technology (MU) | 80.68% | 12.20 | $198.47 | 100.01% | 42.51% |
Meta Platforms (META) | 4.75% | 26.03 | $733.41 | 18.07% | 19.13% |
Lam Research (LRCX) | 46.59% | 32.05 | $141.25 | 9.30% | 9.21% |
Amazon.com (AMZN) | -3.89% | 32.52 | $217.95 | 23.48% | 11.10% |
ServiceNow (NOW) | -5.21% | 55.98 | $935.65 | 20.82% | 19.77% |
*Updated on October 22, 2025.
Stock #1
Micron Technology (MU)
$198.47 USD -3.82 (-1.89%)
3-Year Stock Price Performance

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- Zacks Rank
- Strong Buy 1
- Style Scores
B Value A Growth D Momentum A VGM
- Market Cap: $227.06B (Large Cap)
- Projected EPS Growth:100.00%
- Last Quarter EPS Growth:65.32%
- Last EPS Surprise:5.94%
- Next EPS Report date:Dec. 17, 2025
Our Take:
Micron is a leading memory supplier whose high-bandwidth Dynamic Random Access Memory (DRAM) and advanced SSDs are increasingly critical inputs to AI training and inference, from the data center to the edge. The stock’s Zacks Rank #1 (Strong Buy) reflects brisk estimate revisions, while its Style Score of A for Growth and VGM score of A underscore positive earnings momentum at a reasonable valuation. A score of C for Momentum suggests near-term volatility but not a broken trend.
Fundamentally, Micron has begun shipping next-gen HBM samples and is scaling HBM3E for NVIDIA platforms, positioning it to capture outsized AI spend as model sizes rise. Its roadmap highlights power-efficient HBM and LPDDR for AI accelerators, reinforcing unit and mix tailwinds as deployments broaden.
The Price, Consensus & EPS Surprise chart shows price recovering to highs as 2026–2027 EPS estimates climb, a constructive setup that validates the Rank and Growth score. Pullbacks have coincided with rising out-year consensus lines, suggesting dips remain supported by estimate momentum.
Stock #2
Meta Platforms (META)
$733.41 USD +0.14 (0.02%)
3-Year Stock Price Performance

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- Zacks Rank
Strong Buy 1
- Style Scores
D Value C Growth B Momentum C VGM
- Market Cap: $1,842.08B (Large Cap)
- Projected EPS Growth:18.06%
- Last Quarter EPS Growth: 11.04%
- Last EPS Surprise:22.47%
- Next EPS Report date:Oct. 29, 2025
Our Take:
Meta builds and distributes open-source Llama models and is overhauling its infrastructure, utilizing custom MTIA silicon and AI-optimized data centers to power recommendations, ads, and new assistants across its apps. Its Zacks Rank #1 signals positive estimate revisions. Both Growth and Momentum scores of B support strengthening fundamentals, while a D for Value reflects a premium for platform scale.
Meta’s strategy is gaining traction with advertisers adopting AI creative and Advantage+ tools at scale, and the company is continuing to iterate quickly on Llama releases to broaden developer reach and workloads. Together, these moves deepen engagement and monetization while spreading model costs over a vast user base.
On the chart, price has broken to new highs as the 2026–2027 consensus inflects upward, indicating estimate leadership behind the rally. The tight alignment of rising estimates and price action supports the Rank and Momentum profile.
Stock #3
Lam Research (LRCX)
$141.25 USD -3.79 (-2.61%)
3-Year Stock Price Performance

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- Zacks Rank
Buy 2
- Style Scores
D Value B Growth B Momentum C VGM
- Market Cap:$182.90B (Large Cap)
- Projected EPS Growth:9.42%
- Last Quarter EPS Growth:27.88%
- Last EPS Surprise:10.83%
- Next EPS Report date:Oct. 22, 2025
Our Take:
Lam Research supplies etch and deposition tools essential to leading-edge logic (including gate-all-around) and high-layer 3D memory, steps that scale with AI chip complexity. A Zacks Rank #2 (Buy) coupled with a Style Score of B for Momentum reflects improving orders and estimate traction through the upturn, while Value and Growth scores of D and C, respectively, suggest investors are paying up for cycle leverage.
Lam’s Akara conductor-etch platform and automation initiatives aim to maximize yield and throughput for next-gen nodes and 3D DRAM/NAND, aligning the company with secular AI demand for advanced wafers. As a fabs tool for GAA and denser memory to feed accelerators, Lam’s installed base and process leadership should benefit.
The chart shows price rebounding with steady increases in 2025–2027 EPS consensus after last cycle’s trough, consistent with a mid-cycle recovery. Estimate lines trending higher ahead of price suggest continued support for the Buy rating.
Stock #4
Amazon.com (AMZN)
$217.95 USD -4.08 (-1.84%)
3-Year Stock Price Performance

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- Zacks Rank
Buy 2
- Style Scores
C Value A Growth B Momentum A VGM
- Market Cap:$2,367.93B (Large Cap)
- Projected EPS Growth:23.51%
- Last Quarter EPS Growth:5.66%
- Last EPS Surprise:26.32%
- Next EPS Report date:Oct. 30, 2025
Our Take:
Amazon is embedding AI across retail and AWS, with Rufus enhancing shopping discovery, while AWS Bedrock and Q give enterprises managed access to leading foundation models and agents. A Zacks Rank #2 with Style Scores of A for Growth and Momentum and a VGM score of A points to strong estimate and price trends, with a reasonable Value grade of C.
AWS remains the core AI monetization engine, with customers building and deploying generative applications on Bedrock while benefiting from model choice, built-in guardrails, and knowledge-base integrations that can accelerate adoption and increase workload intensity.
The chart presents a strong uptrend with the 2026–2027 consensus rising, mirroring the Growth and Momentum scores. While the stock has seen brief pullbacks, estimate lines have continued to climb, indicating durable earnings visibility from AI-driven workloads.
Stock #5
ServiceNow (NOW)
$935.65 USD -5.85 (-0.62%)
3-Year Stock Price Performance

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- Zacks Rank
Buy 2
- Style Scores
F Value B Growth F Momentum D VGM
- Market Cap:$195.83B (Large Cap)
- Projected EPS Growth:20.83%
- Last Quarter EPS Growth:-4.76%
- Last EPS Surprise: 15.54%
- Next EPS Report date:Oct. 29, 2025
Our Take:
ServiceNow embeds generative AI directly into workflows via Now Assist and its domain-specific Now LLM, helping customers automate support, HR, and developer tasks with enterprise-grade controls. The Zacks Rank #2 and a Style Score of B for Growth reflect constructive revisions and product uptake, while a weaker score of F for both Value and Momentum highlights a premium multiple and choppy trading.
The platform approach, partnering with NVIDIA and supporting multiple LLMs, expands use cases while preserving data privacy and governance, which is a key requirement for large enterprises. As customers standardize on workflow automation, GenAI features become attached to existing modules, deepening adoption and upsell potential.
On the chart, consensus EPS for 2025–2027 trends steadily higher while price consolidates below prior highs. That positive estimate slope supports the Rank and Growth profile, suggesting potential for renewed leadership if execution sustains and multiples hold.
Methodology
The Zacks Rank is a proprietary stock-rating model that uses trends in earnings estimate revisions and earnings-per-share (EPS) surprises to classify stocks into five groups: #1 (Strong Buy), #2 (Buy), #3 (Hold), #4 (Sell) and #5 (Strong Sell). The Zacks Rank is calculated through four primary factors related to earnings estimates: analysts' consensus on earnings estimate revisions, the magnitude of revision change, the upside potential and estimate surprise (or the degree in which earnings per share deviated from the previous quarter).
Zacks builds the data from 3,000 analysts at over 150 different brokerage firms. The average yearly gain for Zacks Rank #1 (Strong Buy) stocks is +23.62% per year from January, 1988, through June 2, 2025.
Selections for Best AI Stocks are based on the current top ranking stocks based on Zacks Indicator Score. For this list, only companies that have average daily trading volumes of 100,000 shares or more and at least five analysts covering the stock were considered. All information is current as of market open, Oct. 22, 2025.
Guide to AI Stocks
The classification of “AI Stocks” is actually quite broad, ranging from companies that provide the essential hardware, companies that create the software to run Large Language Models, and a whole host of other industries and companies that are creating the Artificial Intelligence ecosystem. All stand to gain – or lose – depending on the fortunes of AI tech.
Types of AI Stocks
Hardware (GPUs, Chips) Stocks – NVIDIA, AMD, TSMC, Broadcom
The backbone of AI is raw computing power, and this comes primarily from specialized chips like graphics processing units (GPUs) and AI-focused accelerators. NVIDIA (NVDA) is the undisputed leader in GPUs used for training large language models.
Advanced Micro Devices (AMD) is a rising competitor, with its MI300 series targeting data center AI workloads. Taiwan Semiconductor Manufacturing Co. (TSMC) doesn’t make its own chips but manufactures advanced nodes for nearly every big tech firm—including Apple, Nvidia, and AMD—making it critical to the global AI supply chain. Broadcom (AVGO) has carved a niche in custom ASICs (application-specific integrated circuits) for hyperscale cloud providers, which value tailored chips that reduce energy use and maximize throughput.
These companies benefit from structural demand for more computing capacity, but they also face geopolitical risks such as U.S.-China export restrictions and cyclical swings in semiconductor demand.
AI Cloud & Infrastructure – Microsoft, Amazon, Alphabet
Building AI applications at scale requires massive computing infrastructure. Azure from Microsoft (MSFT) has become a leader by integrating OpenAI’s models directly into its cloud offerings, giving it a first-mover advantage in AI enterprise adoption. Amazon Web Services, a subsidiary of Amazon (AMZN) is deploying its in-house Trainium and Inferentia chips, aiming to lower costs for AI workloads while retaining dominance in cloud services. Alphabet’s (GOOG) Google Cloud is leaning heavily on its proprietary Tensor Processing Units (TPUs) and Gemini AI models to differentiate itself.
Investing in these players is less about speculative growth and more about diversified tech giants whose AI investments bolster an already profitable core business.
Enterprise AI Software & Analytics – Palantir, C3.ai, Adobe, Snowflake
AI isn’t just about hardware; software platforms are where businesses actually apply machine intelligence. Palantir (PLTR) powers decision-making for defense and large corporations with its Foundry and Gotham platforms. C3.ai (AI) focuses specifically on AI-driven applications across industries like energy, finance, and manufacturing. Adobe (ADBE) has integrated AI across its creative suite (e.g., Firefly in Photoshop), while Snowflake (SNOW) has added AI-enabled analytics to its cloud data warehousing business.
These stocks tend to have higher growth potential but also higher risk, as adoption timelines and customer budgets can vary widely.
Cybersecurity AI – CrowdStrike
The rise of AI also heightens cyber risks. CrowdStrike (CRWD) leads in AI-powered threat detection, using machine learning to flag suspicious behavior across millions of endpoints in real time. With ransomware and nation-state attacks increasing, demand for AI-driven security remains strong. Cybersecurity names often benefit from recurring revenue models, which may help smooth out volatility compared to hardware peers.
Benefits and Risks of AI Stocks
Benefits:
- Secular Growth: AI adoption is still in early innings, with enterprise use cases expanding rapidly.
- Diversified Exposure: Investors can target infrastructure, software, or services depending on risk tolerance.
- First-Mover Advantage: Leaders like NVIDIA and Microsoft are shaping the ecosystem, creating strong economic moats.
Risks:
- Valuations: Many AI leaders are priced for perfection, leaving little margin of safety.
- Hype Cycle: Investor enthusiasm may outrun near-term fundamentals, creating bubble risk.
- Regulation: Governments are exploring AI rules around privacy, bias, and national security, which could reshape business models.
- Competition: Barriers to entry are high, but fast innovation means today’s leader can quickly lose ground.
How to Choose AI Stocks
When evaluating AI stocks, consider:
- Revenue Mix: How much of the company’s growth is truly driven by AI vs. traditional segments?
- Moat & Differentiation: Does the company control unique technology (like NVIDIA’s CUDA software ecosystem)?
- Customer Adoption: Look for companies with recurring contracts or wide adoption across industries.
- Financial Health: Strong balance sheets matter in a capital-intensive industry.
- Valuation Metrics: Compare price-to-earnings (P/E) ratio, price-to-sales (P/S) ratio, and forward growth projections to industry peers.
How to Invest in AI Stocks
There are multiple entry points depending on your goals:
- Direct Stock Picks: Best if you want concentrated exposure to specific company leaders or disruptors.
- AI Exchange-Traded Funds (ETFs): ETFs such as Global X Robotics & Artificial Intelligence ETF (BOTZ) or iShares Robotics and AI ETF (IRBO) provide diversification by investing in a broad range of companies in the AI space.
- Broad Tech ETFs: Like Invesco QQQ (QQQ) or Vanguard Information Technology ETF (VGT), offering AI exposure as part of a bigger tech basket.
- Dollar-Cost Averaging (DCA): A strategy to smooth price volatility by buying at regular intervals AI stocks or funds.
- Long-Term Holds: Since AI is a multi-decade trend, investors who can weather short-term swings may see the best results.
AI Stocks Alternatives
If you want exposure to AI without betting on a single stock:
- ETFs: Offer diversification and reduce single-company risk.
- Private Markets: Startups in robotics, generative AI, and enterprise AI could offer upside, though access is limited to accredited investors, which face income or licensing limitations (such as a net worth of $1 million, excluding primary residence, plus a high annual income – $300,000 if married.
- Picks-and-Shovels Plays: Companies supplying infrastructure, like power management (e.g., Eaton) or data center REITs (e.g., Equinix), benefit indirectly from AI growth.
Strategies for AI Stocks Moving Forward
- Barbell Approach: Combine stable mega-caps (Microsoft, Nvidia) with speculative names (Quantum Computing Inc., Credo) for balanced exposure.
- Rebalancing: Trim positions after strong rallies to lock in gains and redeploy into underweighted sectors.
- Monitor Earnings: Focus on whether AI adoption translates into sustainable revenue growth.
- Look Beyond the U.S.: Consider emerging AI leaders in Europe and Asia for diversification.
- Stay Agile: AI is evolving rapidly; reassess holdings every quarter as new winners emerge.
Frequently Asked Questions About AI Stocks
Are AI stocks overvalued?
Many AI leaders are priced at steep multiples compared to the broader market. That doesn’t mean all are bubbles, but investors should separate hype from earnings-driven growth.
What is the forecast for AI stocks?
Most analysts expect AI demand to expand through at least the next decade, with data center spending, AI-as-a-service, and AI-enabled enterprise tools driving revenue.
What metrics best signal AI efficacy?
- Growth in AI-specific revenue lines.
- Gross margin improvements tied to AI.
- Customer retention and expansion.
- Evidence of scale: Contracts, partnerships, recurring revenue.