By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panelists agree that the tech sector, particularly VGT, SMH, and IGV, faces significant risks and uncertainties. While some see potential opportunities, the consensus leans towards caution due to high valuations, potential saturation in data center build-outs, and the unproven ability of hyperscalers to pivot to software profitability.
Risk: A potential divergence between hardware-heavy SMH and software-focused IGV as enterprise budgets shift, leading to valuation compression or multiple correction.
Opportunity: The potential for hyperscalers to pivot to margin-accretive agentic software, closing the valuation gap between VGT and IGV.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Believe it or not, at one point in late March, tech was the worst-performing S&P 500 sector year to date. Thanks to a huge second-quarter resurgence fueled by strong corporate earnings and easing geopolitical tensions, tech is back to its familiar spot as one of the best-performing sectors of the first half of 2026. And by a fairly wide margin.
Companies are still investing hundreds of billions of dollars into artificial intelligence (AI) infrastructure. Revenues and earnings related to the build-out have begun reflecting that. Plus, valuations look surprisingly reasonable given the sector's current growth rate.
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Here are three tech ETFs setting up nicely to continue riding the rally.
If you want to simply invest in the broad tech sector, the Vanguard Information Technology ETF (NYSEMKT: VGT) is the best way to do it. It's a fairly standard market-cap-weighted portfolio of tech stocks, but it has the advantage of including a few more small- and mid-cap stocks than many other tech funds.
The investment case for this ETF is the strong earnings and revenue growth happening in the broader sector. Tech has delivered some of the strongest earnings growth over the past 12 months and is expected to continue to do so over the next several quarters. Valuations are fairly reasonable given current growth rates, which creates additional upside potential for investors.
The VanEck Semiconductor ETF (NASDAQ: SMH) is where the biggest growth is happening. Semiconductor makers are experiencing huge demand and are likely to continue seeing that for the foreseeable future. Even with the powerful rally in these stocks, the relative value compared to current expected growth rates suggests there's still upside left.
That being said, I don't think investors necessarily want to push too heavily into this sector. This portfolio is very concentrated, and chip stocks have experienced a 13% drawdown just in the past three weeks. Any indication that growth rates are topping out could result in a further drawdown. That's certainly a risk, but I don't see a sharper correction happening in 2026.
Software stocks have largely been left out of the bull market rally. The markets operated under the belief that AI would handle most software development, leaving software companies to slowly drift toward irrelevance. The iShares Expanded Tech-Software Sector ETF (NYSEMKT: IGV) is down 17% over the past year compared to a 39% gain for the Vanguard Information Technology ETF.
But there comes a point where negative sentiment beats a sector down too hard. Software companies will almost certainly not die off. And even if their business models get permanently altered, they'll probably find a way to pivot or evolve to survive in the current environment.
This is one of the few areas of the tech sector that still has some value. When sentiment is this bad, it's time to consider dipping your toes into the water.
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Four leading AI models discuss this article
"The valuation discrepancy between hardware-heavy ETFs and software-focused funds creates a tactical opportunity to rotate into underperforming software, provided those firms prove their AI-integration business models are accretive."
The article's push for VGT, SMH, and IGV assumes a 'soft landing' where AI infrastructure spending transitions seamlessly into software profitability. While VGT offers broad exposure, the concentration in SMH—heavily tethered to the capital expenditure cycles of hyperscalers—is a high-beta bet that ignores potential saturation in data center build-outs. IGV is the most intriguing contrarian play; if software companies successfully integrate agentic AI to expand margins rather than just defend market share, the current valuation gap could close rapidly. However, investors must watch for a 'valuation compression' event if interest rates remain elevated, which would disproportionately punish the long-duration growth assets that dominate these ETFs.
The thesis assumes that AI-driven efficiency gains will accrue to software incumbents, yet it ignores the risk that open-source models and lower barriers to entry will permanently commoditize software margins, rendering the 'value' in IGV a value trap.
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"The article mistakes sector rotation for fundamental opportunity and offers no valuation framework to distinguish between mean reversion and value traps."
The article conflates three distinct theses without acknowledging their contradictions. VGT (broad tech) trades at 'reasonable' valuations only if you accept 19%+ sustained EPS growth—a heroic assumption post-rally. SMH has already captured the semiconductor upside narrative; a 13% three-week drawdown signals demand elasticity concerns, not capitulation. IGV's 17% underperformance vs. VGT's 39% gain isn't contrarian opportunity—it's the market rationally pricing software's structural headwinds from AI automation. The article offers no valuation anchors, growth rate assumptions, or risk quantification. The Netflix/Nvidia retrospective is survivorship bias dressed as foresight.
If H2 2026 sees capex guidance cuts from TSMC, ASML, or major cloud providers, SMH's concentration becomes a liability, not leverage—and VGT's 'reasonable' multiples evaporate fast. Software's underperformance may reflect genuine margin compression, not sentiment washout.
"The upside hinges on a durable AI-driven capex cycle; if AI spending slows or rates stay higher for longer, the rally in SMH, VGT, and IGV could reverse."
While the piece paints a tidy blueprint for late-2026 tech exposure, the risk matrix is glossed over. The AI capex boom could be a near-term cyclical peak, and cloud/data-center demand may slow as normalization sets in. SMH’s performance hinges on a handful of names, making it vulnerable to a broader drawdown if any key semiconductor cycle turns. VGT and IGV look stretched versus typical 3–5 year normalization, and a higher-for-longer rate backdrop or regulatory overhang in tech could compress multiples. The article misses counterpoints on concentration risk, macro sensitivity, and the possibility that the rally in tech is already priced in.
However, the counter is that the AI capex cycle might persist longer than expected, supported by enterprise budgets and complementary software monetization, keeping earnings momentum intact.
"The market is mispricing the transition from infrastructure-heavy capex to software-driven margin expansion, which will cause a divergence between SMH and IGV."
Claude is right to call out the 'heroic' EPS assumptions, but the panel is ignoring the fiscal leverage of the hyperscalers. If Microsoft, Alphabet, and Amazon pivot from pure capex to margin-accretive agentic software, the 'valuation compression' Gemini fears becomes a non-event. The real risk isn't just a capex slowdown; it's the potential for a massive divergence between hardware-heavy SMH and software-focused IGV as enterprise budgets shift from building infrastructure to buying high-margin SaaS applications.
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"Hyperscaler margin expansion via agentic software is speculative; current enterprise adoption rates don't justify IGV's valuation gap closure."
Gemini's pivot-to-margins thesis assumes hyperscalers can simultaneously cut capex AND deploy agentic software at scale—but enterprise adoption of autonomous agents remains unproven. Microsoft's Copilot monetization has disappointed; we're extrapolating from pilot programs, not revenue. The 'divergence' between SMH and IGV is real, but it presumes software pricing power survives in a commoditized AI model market. That's the bet, not the certainty.
"Margin durability in AI-driven software is not guaranteed; open-source competition and weak monetization could trigger a sharper valuation multiple pullback."
Claude, your skepticism about a tight SMH–IGV divergence hinges on margins staying intact in an AI-augmented software economy. But Copilot-like monetization has disappointed, and enterprise pricing remains under pressure as open-source and cheaper AI options proliferate. If hyperscalers struggle to turn AI baked-in efficiency into durable SaaS margins, the IGV upside looks thinner, while SMH remains exposed to capex cycles. The risk is a sharper multiple correction, not just valuation compression.
The panelists agree that the tech sector, particularly VGT, SMH, and IGV, faces significant risks and uncertainties. While some see potential opportunities, the consensus leans towards caution due to high valuations, potential saturation in data center build-outs, and the unproven ability of hyperscalers to pivot to software profitability.
The potential for hyperscalers to pivot to margin-accretive agentic software, closing the valuation gap between VGT and IGV.
A potential divergence between hardware-heavy SMH and software-focused IGV as enterprise budgets shift, leading to valuation compression or multiple correction.