The artificial intelligence market is rapidly evolving, and top Wall Street analysts are already looking for the next breakout star beyond the usual industry giants. Dan Ives, a prominent managing director at Wedbush Securities, recently identified Anthropic as the “tip of the sphere” in what he calls the second wave of the artificial intelligence investment theme. According to Ives, while the initial phase of the AI boom focused heavily on hardware providers like Nvidia, we are now entering a period where software-led innovation and model-based performance will dictate which companies generate the most long-term shareholder value.
Ives suggests that the market has transitioned from the “build-out” phase, where companies spent over $1 billion to acquire chips and data center capacity, to the “application” phase. In this new reality, the value lies in who can build the most efficient, safe, and powerful large language models. Anthropic, the company behind the Claude AI chatbot, has successfully positioned itself as the enterprise-focused alternative to OpenAI. Their recent push into high-impact security and complex code-analysis tools has caught the attention of major institutional investors who are looking for more than just a consumer-facing chatbot.
The “tip of the sphere” analogy is particularly significant. Ives argues that just as the spear point is the first part of the weapon to hit its target, Anthropic is currently the leading edge of AI software adoption. The company’s focus on ethical AI and robust safety guardrails has made it a preferred partner for firms in the legal, financial, and cybersecurity sectors. These industries simply cannot afford the “hallucinations” that often plague other AI models. By solving the trust problem, Anthropic has effectively cleared a path for massive enterprise spending that its competitors have yet to capture.
Investors should pay close attention to this shift. For the past two years, almost every dollar flowing into the AI sector went straight to the hardware manufacturers. Now, we are seeing a rotation. As the supply of high-end graphics processing units stabilizes, the market is beginning to demand proof of software-driven revenue. If a company can integrate its AI models into enterprise workflows—such as automating complex legal research or performing real-time security audits—that software becomes “sticky.” Companies are far less likely to cancel an AI subscription that saves their staff hundreds of hours of manual labor per month.
The growth potential for a company like Anthropic is staggering when you look at the total addressable market. Every single “knowledge worker” globally is a potential customer for advanced AI agents. If Anthropic can capture even a small 1.5% to 2% share of this global enterprise market, it could result in billions of dollars in recurring annual revenue. This transition from experimental software to mission-critical infrastructure is what keeps analysts like Ives so bullish on the startup’s future, even as they compete against well-funded incumbents.
However, the road ahead is not without significant obstacles. The costs associated with training frontier-level models remain incredibly high. OpenAI, for instance, has projected massive spending plans, and Anthropic faces the same economic reality. Running a world-class AI lab requires tens of thousands of specialized processors and an army of the world’s best engineers. For these startups to survive, they need to continue raising capital while simultaneously proving to their shareholders that they can move toward a profitable business model.
Ives also pointed out that we are currently seeing a “gold rush” for talent. The best AI researchers are now among the most highly paid employees in the entire tech industry. Companies are willing to offer multi-million dollar compensation packages to secure the talent necessary to keep their models competitive. This talent war is a hidden cost of the AI boom, but it is one that top-tier firms like Anthropic have successfully navigated so far. They have managed to pull in top researchers by offering a mission-driven culture focused on safety, which resonates deeply with many scientists in the field.
The broader market will likely see more mergers and acquisitions as larger tech firms try to buy their way into this “second wave.” We have already seen recent examples of tech giants paying $1 billion or more to secure the licensing rights for specialized AI software. If Anthropic continues to lead the way, it may eventually become a prime target for acquisition, though the company has signaled that it intends to remain independent for the foreseeable future. This independence is a key part of the “trust” story they tell their enterprise clients.
Looking toward the remainder of 2026, the strategy for investors is clear: follow the software. The easy money in the AI hardware trade may have already been made, but the real profit lies in the companies that can solve the most difficult problems for global corporations. If Dan Ives is correct, Anthropic has moved into the front row of the AI trade, shifting the focus from simply “how fast” a model can talk to how effectively it can solve real-world problems.
Ultimately, the “tip of the sphere” is where the most pressure is applied. Anthropic is operating in that high-pressure zone, dealing with both the scrutiny of regulators and the intense demand from corporate clients. If the company maintains its current pace of development, it will likely be one of the most talked-about companies during the next major earnings season. For now, the market is clearly betting that safe, enterprise-grade AI is the next big growth story that will drive the technology sector forward.
