AI’s Role in 2026 Market Growth: Opportunities, Risks & Top Sector Picks

The recent Fox Business interview with SWBC CIO Chris Brigati underscores a broadly bullish view: AI advances are not just a trend, but a structural force that will continue to drive market growth. The optimism is aligned with broader industry forecasts and market behaviors observed in late 2025.

Data from Reuters highlights similar themes: for example, US markets in 2026 are expected to see earnings growth north of 15% assuming continued AI investment and favorable Fed policies. Additionally, Morgan Stanley projects that full AI adoption across S&P 500 firms could generate roughly $920 billion annually in net benefits—including $490 billion from more autonomous “agentic” systems—and lead to a 24–29% increase in market capitalisation long term.

Still, these drivers are counterbalanced by notable risks. Hardware costs—especially for memory like DRAM and NAND—are affecting consumer markets negatively, as shown by IDC’s projection of a 5–9% decline in PC shipments in 2026 amid AI-driven shortages. Also, BCA Research and others warn that investor expectations may have outpaced likely outcomes: while moderate GDP gains and productivity improvements are probable, achieving profit and cash-flow targets baked into current valuations is not guaranteed.

Strategic implications for investors include:

• Sector selection: beyond just big tech, sectors like utilities, industrials, communication services, and infrastructure are likely to benefit from the AI build-out—particularly due to data centers and power demand increases.
• Value discipline: increasing scrutiny around proofs of ROI, governance, transparency, and models that move beyond narrative into measurable performance.
• Risk management: exposure to elevated valuations, hardware supply chain bottlenecks, energy constraints, and regulatory scrutiny must be actively hedged or diversified.
• Non-linear outcomes: The pace and shape of AI’s maturation may lead to inflection points—both positive and negative—where investor sentiment, policy, or technology constraints materially shift trajectories. Monitoring realized returns vs forecasted growth will be crucial.

Open questions remain:

• Can the high CapEx invested into data centers and infrastructure be justified by correlated revenue growth—and in which time frame?
• How will inflation, energy costs, and power grid constraints interact with AI’s appetite for computing and electricity?
• What regulatory, privacy, and governance frameworks will emerge to either enable or limit AI deployment, especially in sensitive industries?
• Is there a risk of corrections or “air pockets” if widely anticipated productivity gains lag or valuations become untethered from earnings?