The Next Alphabet

Key Concepts

• Generative AI: AI models capable of creating new content (text, images, etc.). Examples include ChatGPT, Gemini, and Firefly.
• TPUs (Tensor Processing Units): Custom-designed AI accelerator chips developed by Google.
• Magnificent 7: A group of seven large-cap US technology stocks (Alphabet/Google being one) that have driven significant market returns.
• Inference: The process of using a trained AI model to make predictions or generate outputs.
• Software as a Service (SaaS): A software distribution model where applications are hosted by a provider and made available to customers over the internet.
• Moore's Law: The observation that the number of transistors in a dense integrated circuit doubles approximately every two years. Its slowing is driving demand for specialized chip design.
• Chip Packaging: The process of assembling and connecting individual semiconductor dies into a functional chip.
• Virtual Testing: Simulating the performance of a chip design before physical fabrication.

Alphabet's 2024 Success & The AI Ecosystem

The year 2024 saw Alphabet (Google’s parent company) experience a significant stock surge, becoming a standout performer among the “Magnificent 7” tech stocks. This success is largely attributed to its advancements in Artificial Intelligence (AI). Initially, the release of ChatGPT in 2022 sparked fears that it could challenge Google’s dominance in search, causing a temporary decline in Google’s stock price. However, Google was already heavily invested in AI through its DeepMind division, working on projects like AlphaFold and developing its own Large Language Models (LLMs).

Google released Bard, its competitor to ChatGPT, within five months of ChatGPT’s launch, demonstrating it wasn’t caught unprepared. The real turning point came with the release of Gemini 3 in November, which outperformed GPT-4 on virtually all benchmarks, signaling Google’s strong position in the AI race. Simultaneously, Google announced plans to sell its custom-designed Tensor Processing Units (TPUs) to external companies, potentially starting with Meta. This is significant because Nvidia currently dominates the market for GPUs (Graphics Processing Units) used in AI computing, and a shortage of Nvidia chips exists. TPUs offer Google a cost advantage in training AI models due to their in-house production. Offering them to others could disrupt Nvidia’s dominance. Since June, Alphabet’s stock doubled, fueled by these AI developments.

Identifying Potential 2026 "Alphabet" Stocks: A Framework

Matt Wine Shank of Stanbury Research outlined a framework for identifying stocks poised for similar growth to Alphabet in 2026. He identified three key characteristics:

1. Capital: AI development is incredibly expensive, requiring billions of dollars for model training and inference. Companies with substantial existing revenue streams (like Alphabet’s advertising revenue – exceeding $100 billion in free cash flow annually) have an advantage over startups reliant on fundraising.
2. Audience: A large, established user base is invaluable. Google’s reach through Search, Gmail (over 1 billion users), YouTube, and Chrome provides a built-in audience for deploying AI-powered features. This reduces the need for extensive user acquisition efforts. Alphabet currently has 650 million Gemini users compared to ChatGPT’s 700 million, despite ChatGPT having a first-mover advantage.
3. Innovation History: A proven track record of innovation and a culture of technological advancement are crucial. Companies that have been investing in AI for years (like Google, with 20 years of experience) are better positioned to capitalize on the current AI boom.

Three Stock Picks for 2026

Based on this framework, Matt Wine Shank identified three stocks with potential for significant growth in 2026:

1. Adobe (ADBE)

Adobe, a leader in creative software (Photoshop, Illustrator), initially faced concerns that generative AI image generators (like DALL-E and Midjourney) would displace its products. However, Adobe is integrating AI into its existing suite through its Firefly app. Firefly allows users to generate images using various models (including Gemini and ChatGPT) and then seamlessly edit, refine, and share them within Adobe’s ecosystem. A key differentiator is Adobe’s focus on copyright-friendly AI image generation. Recent earnings reports show positive trends: subscriptions to Firefly doubled quarter-over-quarter, and token generation tripled. Adobe’s stock, previously down by about half, is showing signs of recovery.

2. Salesforce (CRM)

Salesforce, often described as the “OS for business” and a pioneer of the Software as a Service (SaaS) model, also faced AI-related anxieties – the fear that AI-powered coding tools would reduce the need for its CRM software. However, Salesforce is leveraging AI to enhance its platform with “Agent Force,” an AI agent designed to automate tasks and interact with customers. While the initial rollout of Agent Force faced challenges (requiring training for 15,000 sales executives), recent results indicate growing adoption, with a half-billion-dollar revenue run rate and tripling token usage. Salesforce’s established customer base and sticky business model position it well to capitalize on the integration of AI into business processes.

3. Synopsis (SNPS)

Synopsis designs the software used to create semiconductor chips. The increasing demand for chips, coupled with the slowing of Moore’s Law (the historical trend of doubling transistor density), is driving demand for custom chip design and advanced chip packaging. Synopsis benefits from this trend, with a 70% gross margin and 15% profit margin expected to increase. The company recently acquired Ansys, a company specializing in general engineering software, further expanding its capabilities. As companies like Google, Amazon, Meta, and Rivian develop their own custom chips, Synopsis is well-positioned to provide the necessary design tools.

Logical Connections & Synthesis

The presentation establishes a clear connection between Alphabet’s success and the broader AI landscape. It then provides a framework for identifying other companies poised to benefit from the AI revolution. The three stock picks – Adobe, Salesforce, and Synopsis – are presented as examples of companies that possess the key characteristics identified in the framework: substantial capital, a large audience, and a history of innovation. The analysis emphasizes that AI isn’t necessarily about replacing existing software but rather integrating into it, making products more valuable and “stickier.” The presentation concludes with a cautionary disclaimer that this is not financial advice.

The main takeaway is that identifying AI winners requires looking beyond the hype and focusing on companies with the resources, reach, and expertise to successfully integrate AI into their existing businesses and capitalize on the growing demand for AI-powered solutions. The slowing of Moore’s Law and the increasing need for custom chip design further highlight the importance of companies like Synopsis in the evolving technological landscape.