Software Bulls Regain Momentum as AI Trade Moves Beyond Chips

Author’s Note and Disclaimer:

Zion Zhao Real Estate | 88844623 | 狮家社小赵 | wa.me/6588844623 |  https://linktr.ee/zionzhao

This post is for general information, education, and market literacy only. It does not constitute financial, investment, trading, legal, tax, accounting, or other professional advice, and is not an offer, solicitation, recommendation, or endorsement. Views expressed are personal, general in nature, and subject to change without notice. While reasonable care is taken, no representation or warranty is given as to accuracy, completeness, or reliability. Readers should conduct independent due diligence and seek professional advice. To the fullest extent permitted by law, no liability is accepted for any loss arising from reliance on this material. 

AI Rally Broadens as Wall Street Reprices Software Winners

Software is not dead. It is being repriced, reclassified, and re-understood.

The latest market sentiment and discussion within my trading peers captures a market moving from first-stage AI euphoria into second-stage AI discrimination. The first stage rewarded the obvious infrastructure winners: Nvidia, Dell, Micron, data centres, AI servers, high-bandwidth memory, and compute providers. The second stage is more intellectually demanding. Investors are now asking a sharper question: which companies merely talk about AI, and which companies can convert AI into pricing power, workflow control, customer retention, operating leverage, and durable earnings?

The most important takeaway is that AI will not destroy all software. It will divide software into winners and casualties. Narrow point solutions with weak switching costs, limited proprietary data, and low workflow dependency are vulnerable to AI agents and automation. However, enterprise-grade platforms such as Salesforce, ServiceNow, Snowflake, MongoDB, Microsoft, and Shopify are much harder to replace because they sit inside mission-critical systems, procurement workflows, compliance processes, audit trails, customer data environments, and enterprise operating infrastructure.

That is why the “SaaS is back” thesis should not be dismissed as a one-day relief rally. Salesforce continues to generate double-digit revenue growth while building AI-related revenue streams through Agentforce and Data Cloud. ServiceNow remains deeply embedded in enterprise workflow automation. Snowflake and MongoDB continue to benefit from the growing strategic importance of data architecture in an AI economy (Salesforce, 2026; ServiceNow, 2026; Snowflake, 2026; MongoDB, 2026). The market is slowly realizing that AI does not automatically kill software. In many cases, AI may strengthen the platforms that already own the data, integrations, governance layer, and customer trust.

The same logic extends beyond traditional SaaS. Reddit and Shopify are not merely internet stocks. Reddit owns high-intent community conversations, authentic consumer behaviour, and valuable human-generated data. Shopify is a commerce operating system for merchants, with AI potentially strengthening storefront creation, customer service, product discovery, inventory management, and marketing automation. Uber, meanwhile, should not be viewed only through the autonomous vehicle risk lens. Its deeper value lies in demand aggregation, payments, routing, reputation systems, and marketplace liquidity. Autonomous vehicles may become a supply source inside Uber’s network rather than a simple existential threat.

Meta deserves particular attention. It is still one of the world’s most powerful advertising machines, but it is also evolving into an AI infrastructure, messaging, subscription, creator-tool, and possibly compute-monetisation platform. If Meta overbuilds AI infrastructure, excess compute could theoretically become a strategic asset rather than a wasted expense. Microsoft is similarly underappreciated in parts of the market. It combines cloud infrastructure, enterprise software, security, developer tools, productivity software, and AI distribution in one ecosystem. In a market that rewards AI monetisation, Microsoft remains one of the strongest structural platforms.

However, the bull case requires discipline. The podcast’s phrase “invest then investigate” is useful only if interpreted responsibly. A small starter position can force deeper research. It should not become an excuse for reckless buying, social media chasing, leverage, or blind speculation. Behavioural finance research has repeatedly shown that overconfidence and excessive trading can damage investor outcomes (Barber & Odean, 2000). In a momentum-driven market, price action can validate a trade temporarily, but only earnings, cash flow, competitive advantage, and execution can validate a long-term investment thesis.

AI infrastructure remains the clearest engine of this cycle, but even there, discipline matters. Nvidia’s growth confirms the scale of AI demand, while Dell and Micron show that the buildout is spreading across servers and memory. Yet infrastructure markets can still be cyclical. Memory prices, capex schedules, customer concentration, power constraints, and supply responses must be watched carefully. A great secular trend does not remove valuation risk.

Crypto should be treated with the same analytical discipline. Bitcoin may function as a scarce digital store-of-value asset, while Ethereum may have stronger direct utility through stablecoins, tokenisation, and smart contracts. But both remain volatile, policy-sensitive, and highly sentiment-driven. Regulation can create catalysts, but it cannot eliminate risk.

My broader message is clear: the bulls remain in control, but leadership is broadening. The AI trade is moving from chips to platforms, from compute to workflow, from hype to monetisation, and from speculative storytelling to earnings scrutiny. The next winners will not be companies that simply attach “AI” to a slide deck. They will be companies that own distribution, data, infrastructure, compliance, customer relationships, and economic capture.

This is not financial advice. It is a reminder that in this market, the smartest investors are not chasing every exciting story. They are identifying which stories can become cash flow, which cash flows can become durable earnings, and which earnings deserve premium valuations.

References

Barber, B. M., & Odean, T. (2000). Trading is hazardous to your wealth: The common stock investment performance of individual investors. The Journal of Finance, 55(2), 773–806.

MongoDB. (2026). First quarter fiscal 2027 financial results. MongoDB Investor Relations.

Salesforce. (2026). First quarter fiscal 2027 results. Salesforce Investor Relations.

ServiceNow. (2026). First quarter 2026 financial results. ServiceNow Investor Relations.

Snowflake. (2026). First quarter fiscal 2027 financial results. Snowflake Investor Relations.

Software Stocks Reawaken as AI Boom Enters Its Second Act

Software is not dead; it is being repriced. AI will punish weak point solutions but strengthen platforms owning data, workflows, compliance and distribution. The bull market is broadening from chips to enterprise software, infrastructure, commerce and crypto, but disciplined investors must separate durable earnings power from social media momentum risk.

AI is not only reshaping technology stocks. It is reshaping capital flows, business confidence, employment patterns, rental demand and long-term property investment strategy. When software, AI infrastructure, data centres, fintech, digital assets and enterprise platforms attract global capital, cities with strong governance, connectivity and talent ecosystems benefit. Singapore is one of them.

For buyers, this matters because property selection is no longer just about location. It is about future economic relevance, MRT connectivity, tenant depth, school access, lifestyle demand and long-term resilience. For sellers, market timing, positioning and pricing strategy are critical when liquidity, interest rates and investor sentiment shift. For landlords, understanding where professionals, expatriates, tech workers and business owners want to live can directly affect rental performance. For investors, the lesson is clear: do not chase hype. Focus on fundamentals, cash flow, policy, asset quality and exit strategy.

As a Singapore real estate agent with a strong understanding of property, macroeconomics, markets and investment psychology, I help clients connect global trends with practical property decisions in Singapore. Whether you are buying, selling, renting or investing, I provide objective analysis, clear strategy and disciplined guidance tailored to your goals.

In a market driven by AI, capital rotation and changing wealth flows, the best property decisions are not made by emotion. They are made by insight.

Contact me for a professional consultation on your Singapore property plans.

Like, save, collect and subscribe to my social media channels for more property insights, market commentary and investment perspectives.