Why cybersecurity stocks will be net beneficiaries of the AI risks

Bank of America said cybersecurity stocks should be net beneficiaries of rising AI-related risks, even as it cut price targets across the group amid software multiple compression. Zscaler's target was slashed to $175 from $335, SailPoint to $16 from $27.50, and SentinelOne to $16 from $18, reflecting slower billings growth, longer sales cycles, and tougher competition. BofA also flagged Akamai and Fastly as potential AI inferencing beneficiaries.

Analysis

The biggest second-order effect here is not simply “AI increases cyber spend,” but that it changes the mix of spend toward faster-payback, continuously updated controls while penalizing vendors that rely on long implementation cycles and quota-driven expansion. That should widen dispersion inside cybersecurity: platform consolidators with broad attach rates and low-friction deployment should hold up better than point solutions that need heavy services or long proof-of-value periods. The valuation reset also matters because it compresses the premium for any security name whose path to durable free cash flow is not obvious within the next 2-4 quarters.

Zscaler is the clearest structural loser in the near term because it sits at the intersection of slowing growth and rising platform competition, and those names tend to de-rate fastest when software multiples compress. The more subtle competitive risk is that large cloud and infrastructure vendors can bundle “good-enough” security into broader enterprise contracts, which raises customer acquisition costs and lengthens sales cycles for stand-alone vendors across the space. That creates a feedback loop: weaker growth leads to lower multiples, which makes it harder to use stock as acquisition currency and increases strategic vulnerability.

On the beneficiary side, the market is likely underestimating the leverage of content delivery and edge networks to AI inference traffic. If inference demand scales, utilization and pricing power can improve faster than consensus models assume because traffic growth is lumpy and incremental dollars can drop through with limited capex intensity once capacity is in place. The key contrarian point is that this is not a clean secular “AI beta” trade: the winners are the picks-and-shovels names with operating leverage and balance-sheet flexibility, while the market may still be overpaying for security vendors whose AI tailwind arrives alongside margin pressure and longer payback periods.

Key Decisions for Investors

• Short ZS on rallies over the next 2-6 weeks; use a defined-risk put spread rather than outright short equity. Risk/reward favors further multiple compression if billings reacceleration does not show up by the next print.
• Relative value: long AKAM / short a basket of higher-duration software-security names over 1-3 months. The thesis is that AI-inference traffic offers nearer-term monetization with better FCF visibility than subscription security names facing pricing pressure.
• Accumulate AKAM on pullbacks over the next 1-2 quarters; target a 15-20% upside window if AI traffic demand translates into utilization gains. Cut if management commentary indicates capex intensity rises faster than revenue leverage.
• Avoid or underweight SAIL and S until the market stops rewarding only near-term FCF visibility. These can work as trading bounces, but the setup is poor for multiple expansion in a compression regime.
• For aggressive accounts, pair long AKAM vs short ZS as a catalyst-neutral expression of AI winners/losers. This offers cleaner exposure to the difference between AI-driven infrastructure demand and security names still dependent on elongated enterprise sales cycles.