Workday’s Last Workday? AI and the Future of Enterprise Software

2026-04-30 · Source: The a16z Show · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, extended

Summary

A conversation with a16z partner Joe Schmidt explores the future of enterprise software, using Workday as a primary case study, arguing that AI is enabling a significant re-platforming opportunity for deeply entrenched systems. Despite incumbents like Workday, ServiceNow, and Salesforce boasting high gross dollar retention (Workday has 97%), their legacy architectures often provide poor user experiences. The shift from on-premise to cloud previously created Workday's success, and now AI, particularly agent-first approaches, presents a new platform shift. This allows for "rip and replace" strategies, promising rapid deployment (30-60 days compared to 12+ months), "workbench native" customization, and agent-first interaction, alongside robust security, permissioning, and compliance. Workday's reported \$400 million in AI ARR is critically examined, suggesting it may represent "procurement innovation" rather than genuinely transformative agentic experiences.

Key takeaway

For entrepreneurs building enterprise software, the AI platform shift presents an unprecedented opportunity to "rip and replace" deeply entrenched legacy systems. You should focus on developing AI-native solutions that offer rapid deployment (30-60 days), "workbench native" customization, and agent-first interactions to deliver a fundamentally superior employee experience. This approach can overcome the historical stickiness of incumbents like Workday, attracting enterprise buyers ready for transformative change.

Key insights

AI-native agents are fundamentally re-platforming entrenched enterprise software, enabling "rip and replace" of legacy systems.

Principles

• Platform shifts redefine enterprise software categories.
• Entrenched systems are vulnerable to AI re-platforming.
• Poor user experience creates opportunity for disruption.

Method

Build AI-native enterprise systems with rapid deployment (30-60 days), "workbench native" customization, and agent-first interaction. Prioritize critical security, permissioning, and compliance from inception.

In practice

• Design agent-first interactions for workflows.
• Target 30-60 day deployment for new systems.
• Prioritize employee experience in core software.

Topics

• AI Agents
• Enterprise Software
• SaaS Re-platforming
• Workday
• HR Technology
• User Experience

Best for: CTO, VP of Engineering/Data, Executive, Investor, Entrepreneur, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by The a16z Show.