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New Evidence Forces AI Reality Check: Pilots Fail, Entry-Level Jobs Fall, Agents Prove Vulnerable

Investors are pressuring software stocks as studies highlight execution gaps and security risks that are delaying broad productivity gains.

Salesforce headquarters in San Francisco, California.
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Shares of software giant Salesforce are down 26% this year, making it the second-worst performing stock in the Dow.
A photo taken on January 2, 2025 shows the letters AI for Artificial Intelligence on a laptop screen (R) next to the logo of the Chat AI application on a smartphone screen in Frankfurt am Main, western Germany. (Photo by Kirill KUDRYAVTSEV / AFP) (Photo by KIRILL KUDRYAVTSEV/AFP via Getty Images)

Overview

  • An MIT NANDA report finds roughly 95% of corporate generative‑AI pilots fail to produce measurable P&L impact, with only about 5% showing rapid revenue acceleration, citing poor enterprise integration and budgets skewed to sales and marketing over higher‑ROI back‑office automation.
  • Using ADP payroll data through mid‑2025, Stanford researchers link generative‑AI adoption to a 16% employment drop for workers aged 22–25 in vulnerable sectors such as customer service and software development, while more experienced workers are largely insulated and wages have not notably fallen.
  • Security tests by Gray Swan AI against 22 mainstream agents ran 1.8 million prompt‑injection attempts and logged around 60,000 successful compromises enabling unauthorized data access, illicit transactions, and compliance bypasses, prompting CISOs to confine agents to controlled environments as PwC reports eight in ten firms now use agentic AI.
  • Software valuations have slumped as investors reassess business models under the "AI is eating software" narrative, with Salesforce down 26% year‑to‑date, Adobe off 19%, and Atlassian down 30%, even as some analysts argue incumbents can adapt and monetize AI.
  • Macro strategists note no clear AI‑driven surge in aggregate productivity yet, reinforcing calls for executive‑led strategies, tighter guardrails, and targeted deployments rather than broad, siloed pilots.