# BofA: $1.5T AI Buildout Makes Chip Dip a Buy

> Source: [https://icharles.com/articles/bofa-chip-stocks-ai-buildout-1-5-trillion](https://icharles.com/articles/bofa-chip-stocks-ai-buildout-1-5-trillion) (canonical)
> Author: iCharles News — iCharles, https://icharles.com
> Published: 2026-07-08

## TL;DR

Bank of America analyst Vivek Arya says the 11% Q3 pullback in the PHLX Semiconductor Index is a seasonal "summer reset," not a structural break. Global cloud and AI infrastructure spending is still on track to approach $1.5 trillion by 2027, up 40–50% year over year. Arya reiterated a Buy on Micron Technology with a $1,550 price target and named seven chip stocks positioned to lead when AI capex visibility improves in the second half of 2026.

## What did Bank of America say about the chip stock selloff?

Bank of America analyst Vivek Arya called the current chip stock pullback a "summer reset" — not a structural break in AI demand. In a July 6 report, Arya noted the PHLX Semiconductor Index had dropped 11% since the start of Q3, after surging 88% in Q2. He said this matches historical seasonal weakness for the period and expects a rebound in the fall.

"History suggests periods of consolidation are often followed by renewed momentum as investors regain confidence in the next leg of earnings and capex growth," Arya said, [according to Benzinga](https://www.benzinga.com/markets/tech/26/07/60284519/chip-stocks-bear-trap-1-5-trillion-ai-buildout).

## How big is the AI infrastructure buildout?

Global cloud and AI infrastructure spending is projected to approach **$1.5 trillion by 2027**, up 40% to 50% from current levels. Arya attributed this growth to persistent demand for compute, accelerated AI agent deployment, and structural supply-side constraints.

This scale of [AI capex spending](/articles/ai-capex-surpasses-defense-budget-2027) is the foundation of Arya's thesis. He argues that hyperscalers remain focused on maximizing AI utilization — not cutting infrastructure budgets — which keeps chip demand robust.

## Which 7 stocks does BofA expect to lead?

As 2027 spending visibility improves in the second half of 2026, Arya expects market leadership to rotate back to companies tied directly to AI capital expenditures. Here are the seven names he highlighted:

| Stock | Ticker | Segment |
|---|---|---|
| Advanced Micro Devices | AMD | Compute |
| Applied Materials | AMAT | Semiconductor equipment |
| Lam Research | LRCX | Semiconductor equipment |
| Micron Technology | MU | Memory |
| MACOM Technology Solutions | MTSI | Optics |
| Credo Technology Group | CRDO | Networking |
| Marvell Technology | MRVL | Networking |

## Why is Micron BofA's top pick?

Arya singled out Micron as one of the market's biggest AI mispricings. Memory now accounts for roughly **35% to 40% of AI cloud capital spending** — two to three times higher than historical levels. Yet memory stocks still trade at around 10x forward P/E, which Arya considers severely undervalued.

The reason for the discount: investors fear memory pricing will revert to its traditional boom-and-bust cycle. Bank of America disagrees. Memory is moving "from a cyclical commodity to a strategic AI enabler," Arya said, [per Bitget's coverage of the report](https://www.bitget.com/amp/news/detail/12560605492769).

Arya believes long-term supply agreements between memory suppliers and hyperscale customers are making pricing more durable and revenue more predictable. That structural shift, he argues, justifies higher valuation multiples over time.

Bank of America reiterated its Buy rating on Micron and kept a **$1,550 price target**, implying roughly 59% upside from current levels.

## Does the rise of Chinese AI models threaten chip demand?

Arya addressed this directly. Chinese open-weight models — including DeepSeek, Kimi, Qwen, and GLM — have rapidly closed the gap with US frontier labs. As of July 4 third-party benchmark rankings, US models from Anthropic and OpenAI still lead, but Chinese models hold 8 of the top 16 spots. The highest-ranked Chinese model is GLM 5.2 from Zhipu (Z.ai), an open-weight model with 750 billion parameters and a one-million-token context window.

Arya's view: cheaper AI models pressure software profit margins, but they expand AI adoption. More deployment means more demand for compute, memory, networking, and power infrastructure. "The bigger risk is to model economics, not semiconductor demand," the report stated.

This dynamic connects to broader trends we track at iCharles — [Meta's cloud AI](/articles/meta-cloud-ai-compute-coreweave) buildout and [OpenAI's revenue targets](/articles/openai-100b-ad-revenue-2030) both assume inference costs keep falling while infrastructure demand keeps climbing.

Arya also noted that Nvidia is actively participating in open-source community building. This extends Nvidia's hardware ecosystem reach to small and mid-scale AI adopters who lack direct access to frontier labs.

## What does the seasonal pattern suggest?

The PHLX Semiconductor Index — tracked by the iShares Semiconductor ETF (SOXX) — historically shows weakness in Q3. The 11% pullback after an 88% Q2 surge fits that pattern. Arya's call is that the dip is temporary, and that leadership will rotate back to AI capex-linked names as 2027 spending plans become clearer in H2 2026.

Here's what we know so far: the report's core argument rests on the idea that AI infrastructure demand is structurally different from prior chip cycles — and that memory, in particular, is being mispriced by a market still applying old commodity frameworks.

For builders and founders watching [AI infrastructure spending](/articles/ai-capex-surpasses-defense-budget-2027) trends, the BofA thesis points to one concrete milestone: improved visibility into 2027 hyperscaler capex plans, expected to emerge in the second half of 2026.

## Frequently asked questions

**What is Bank of America's price target for Micron Technology in 2026?**

Bank of America analyst Vivek Arya reiterated a Buy rating on Micron Technology (MU) with a price target of $1,550. That target implies roughly 59% upside from Micron's price at the time of the July 6 report. Arya called Micron the top pick in the semiconductor sector and described it as one of the market's biggest AI mispricings.

**Why did chip stocks fall in Q3 2026?**

The PHLX Semiconductor Index dropped 11% since the start of Q3 2026, after surging 88% in Q2. Bank of America analyst Vivek Arya attributed the pullback to historical seasonal weakness in this period. He called it a "summer reset" and said it does not reflect a structural deterioration in AI demand or a change in hyperscaler spending plans.

**How much will global AI infrastructure spending reach by 2027?**

Bank of America projects global cloud and AI infrastructure spending will approach $1.5 trillion by 2027, up 40% to 50% from current levels. The growth is driven by persistent demand for compute, accelerated AI agent deployment, and structural supply-side constraints. Analyst Vivek Arya said hyperscalers remain focused on maximizing AI utilization rather than cutting capital expenditures.

**What share of AI cloud spending goes to memory chips?**

Memory currently accounts for roughly 35% to 40% of AI cloud capital expenditures, which is two to three times higher than historical levels. Despite this, memory stocks trade at around 10x forward P/E. Bank of America argues the market is undervaluing memory because investors still expect pricing to revert to traditional boom-and-bust cycles, which the bank believes is the wrong framework.

**Do Chinese open-source AI models reduce demand for semiconductors?**

Bank of America says no. While Chinese open-weight models like DeepSeek, Kimi, Qwen, and GLM are competing with lower inference costs and closing the gap with US frontier labs, cheaper AI expands use cases and deployment. The report states the greater risk is to AI model economics, not semiconductor demand, since broader AI usage requires more compute, memory, networking, and power infrastructure.