90% Believe in AI, but Half Will Miss Targets: The Execution Gap Is Real

Why It Matters

The execution gap threatens to curb the promised revenue uplift from AI, forcing companies to resolve governance, talent, and legacy challenges before they can reap strategic benefits.

Key Takeaways

• 90% believe AI will shape future, yet many miss targets.
• Governance, legacy systems, talent, anxiety block AI scaling.
• Pilots exist, but scaling remains elusive for most firms.
• Agentic AI needs integrated data, workflows, and human collaboration.
• Execution, not ambition, decides AI leadership in market.

Pulse Analysis

The recent Strategic Leadership Dialogue highlighted a widening chasm between AI ambition and real‑world results. While nearly nine in ten tech leaders expect AI to drive productivity, revenue, and retention, more than half forecast shortfalls in meeting financial goals. This mirrors earlier waves—Internet, cloud, SaaS—where early adopters succeeded only after re‑engineering core business models. Today’s challenge is less about technology availability and more about decisive, organization‑wide execution that moves beyond isolated pilots.

Four recurring barriers impede that execution. Governance and risk constraints, especially in regulated sectors, stall deployment until compliance frameworks are solidified. Decades‑old legacy systems resist seamless integration, demanding careful orchestration rather than wholesale replacement. Talent gaps emerge when AI initiatives outpace hiring or upskilling pipelines, leaving projects understaffed. Finally, cultural anxiety—fear of job loss—dampens employee buy‑in, slowing adoption. Companies that proactively address these issues—by establishing clear AI governance, modernizing data layers, investing in cross‑functional talent, and communicating the transformative, not destructive, nature of AI—are better positioned to scale.

Agentic AI represents the next evolutionary step, coupling autonomous agents with a unified data fabric, workflow engine, and collaborative platforms like Slack. Salesforce’s Data 360 aggregates structured and unstructured information, while the System of Work aligns sales, service, and revenue processes. Agentforce enables rapid deployment of scalable agents, and Slack bridges human‑AI interaction. This integrated stack allows firms to transition from pilot projects to enterprise‑wide AI operations, turning AI from a novelty into a revenue engine. Executing this holistic approach quickly will separate early leaders from laggards in the emerging AI‑driven market.