What Are the 3 Top Artificial Intelligence (AI) Stocks to Buy Right Now?

Oracle, ServiceNow, and Atlassian all posted strong AI-driven growth despite sharp share-price declines, with Oracle cloud revenue up 44% to $8.9B and overall sales up 22% to $17.2B, ServiceNow Q1 sales up 22% to $3.8B, and Atlassian revenue up 23% to $1.6B. The article argues the sell-off has pushed forward P/E multiples to attractive levels while AI demand remains robust, including Oracle RPO up 325% and Atlassian RPO up 44%. Overall tone is constructive on long-term fundamentals, but the piece is primarily valuation commentary rather than a new catalyst.

Analysis

The market is mispricing these names as if AI adoption is a near-term substitute for enterprise software, when the more likely effect is software spend reallocation toward the vendors that sit closest to workflow, identity, and infrastructure control points. Oracle benefits from the capital-intensive layer of the AI stack, where scarcity of power, data-center capacity, and long-duration contracts can create a self-reinforcing backlog cycle; the biggest second-order beneficiary may be utilities, networking, and semiconductor equipment suppliers tied to AI buildout, even if the article does not mention them.

ServiceNow and Atlassian look like higher-quality, underappreciated “AI copilots for the enterprise” rather than victims of automation. The key contrarian point is that agentic AI increases the value of proprietary process data, approval chains, and telemetry — exactly the assets these platforms already aggregate. If AI boosts usage intensity, the upside is not just incremental seat growth but deeper module penetration and better retention, which can re-rate long-duration recurring revenue streams over the next 12-24 months.

The risk is timing, not business durability. These stocks can stay cheap for months if the rotation out of software persists or if investors punish capex-heavy AI narratives before cash conversion inflects; Oracle is the most exposed to a “spend now, monetize later” skepticism trade. Conversely, a resumption of software leadership or a few more quarters of >20% growth with stable margins could force a sharp multiple re-expansion because positioning has likely reset hard after the selloff.

Consensus is still too fixated on AI as a cannibal instead of a demand accelerator. The better framing is that AI shifts bargaining power toward platforms with proprietary workflow data and mission-critical distribution, while commoditizing generic point tools. That makes this more of a selective quality-growth recovery trade than a broad tech beta call, and it argues for owning the names with durable embedded data moats rather than chasing the highest headline AI exposure.

Key Decisions for Investors

• Go long NOW on a 6-12 month horizon; buy on any further 5-8% drawdown. Risk/reward favors 20%+ upside if the market re-rates recurring revenue quality, with downside cushioned by durable subscription growth.
• Initiate a TEAM/NOW pair trade: long TEAM, short a smaller basket of lower-quality software peers over 3-6 months. Rationale: TEAM has the bigger multiple compression and more operating leverage to AI-driven usage expansion.
• Accumulate ORCL only on weakness, preferably after the next capex print. This is a 12-18 month trade: upside comes if RPO converts into revenue without margin shock; risk is another quarter of supply-constrained spending skepticism.
• For tactical exposure, buy 6-9 month call spreads in NOW or TEAM rather than outright stock. The implied volatility reset plus depressed multiples create asymmetric upside if the rotation back into software happens, while limiting drawdown if the factor trade persists.
• Avoid chasing NVDA here; use this article as a relative-value signal in favor of enterprise software over the obvious AI hardware leaders for the next 1-2 quarters.