Intel Roars Back: AI Chip Demand Ignites 22% Stock Surge and Blowout Forecast

Key Takeaways

• Stock soars: Intel shares jumped more than 22% in Friday’s premarket trading after the chipmaker delivered a blockbuster earnings beat and upbeat guidance.
• Guidance crushes estimates: Intel forecasts Q2 2026 EPS of $0.20 (vs. $0.09 consensus) and revenue between $13.8 billion and $14.8 billion (vs. $13.04 billion expected).
• Q1 blowout: Revenue climbed 7% year-over-year to $13.6 billion, topping the $12.41 billion estimate, while EPS of $0.29 trounced the $0.02 consensus.
• AI engine firing: Data center and AI segment revenue surged 22% year-over-year to $5.1 billion, underscoring strong demand for Intel’s server chips.
• Tesla deal landed: Elon Musk confirmed Tesla will use Intel’s next-generation 14A process to manufacture chips for its Austin-based “Terafab” AI complex — a breakthrough for Intel’s foundry ambitions.
• Google partnership deepens: Intel and Alphabet unveiled a multiyear collaboration to expand Xeon processor deployment and co-develop custom AI infrastructure chips.
• Analyst upgrades: Stifel raised its price target on Intel to $75 from $65, citing the chipmaker’s dramatic earnings beat.

Intel Corp. on Thursday forecast second-quarter revenue and profit that sailed well above Wall Street’s expectations, powered by robust demand for its server chips used in artificial-intelligence data centers. The semiconductor veteran also unveiled first-quarter results that handily outpaced analyst projections.

Shares rocketed more than 22% higher in Friday’s premarket session on the back of the announcement.

Intel guided to second-quarter 2026 earnings per share of $0.20, more than double the $0.09 consensus forecast. The company also projected Q2 revenue in the range of $13.8 billion to $14.8 billion, well ahead of the $13.04 billion analysts had penciled in.

From Troubled Giant to AI Contender

Years of strategic missteps had left the once-dominant chipmaker scrambling to establish a meaningful presence in the explosive artificial intelligence market. Chief Executive Lip-Bu Tan countered with an ambitious turnaround blueprint, shoring up Intel’s balance sheet through divestitures and workforce reductions.

Tan has also reeled in significant investments and built strategic alliances with the U.S. government, SoftBank Group Corp. (TYO:9984), and NVIDIA Corporation (NASDAQ:NVDA), equipping Intel with both the capital and partnerships needed to ramp up its manufacturing footprint and rebuild investor faith in the company’s long-term trajectory.

First-Quarter Fireworks

Intel’s first-quarter revenue climbed 7% to $13.6 billion, up from $12.7 billion a year earlier and comfortably beating the $12.41 billion analysts had expected.

The standout performer was Intel’s data center and AI segment, which posted revenue of $5.1 billion — a 22% jump from the same period last year.

Earnings per share came in at $0.29, a striking $0.27 ahead of the $0.02 analyst consensus.

Tesla Deal Marks Foundry Milestone

Earlier in the week, Tesla Chief Executive Elon Musk announced on Wednesday that the electric vehicle maker plans to tap Intel’s next-generation 14A manufacturing process to produce chips at its Terafab project, an advanced AI chip complex Musk has envisioned for Austin, Texas.

The agreement would represent Intel’s first marquee customer for its cutting-edge technology and a pivotal win for the company’s contract manufacturing business, which has long struggled to challenge industry leader Taiwan Semiconductor Manufacturing (NYSE:TSM).

Analyst Enthusiasm Builds

Stifel analysts lifted their price target on Intel to $75 from $65, citing the chipmaker’s ability to “significantly beat expectations.”

Google Alliance Expands

Intel and Alphabet Inc. Class A (NASDAQ:GOOGL) recently unveiled a multiyear partnership centered on the continued rollout of Intel Xeon processors across Google’s workload-optimized instances, including the latest Intel Xeon 6 chips powering C4 and N4 instances. The collaboration also encompasses the co-development of custom ASIC infrastructure processing units (IPUs) engineered to enhance utilization, cut complexity, and scale AI workloads more efficiently.