The End Of Software: Three AI Monetization Shifts Hiding in Plain Sight

2021-11-04 · Source: High ROI AI · Field: Business & Management — Corporate Strategy & Leadership, Project & Product Management, Entrepreneurship & Start-ups · Depth: Advanced, medium

Summary

Recent market activity indicates a violent repricing of enterprise software business models, driven by three interconnected paradigm shifts rather than a singular AI disruption narrative. Hyperscalers like Microsoft are rationing compute resources, prioritizing internal AI products such as Copilot over customer workloads, leading to a zero-sum allocation game and impacting Azure's theoretical growth. Concurrently, AI code generation is inverting the build-vs-buy calculus, making internal development cheaper and potentially shrinking the total addressable market for packaged software, as acknowledged by SAP's CFO. Furthermore, per-seat pricing models, exemplified by ServiceNow, are becoming a liability as AI reduces human headcount, pushing towards outcome-based pricing where vendors are accountable for results, not access. In contrast, Meta's AI investments directly enhance its ad monetization engine, driving increased advertiser willingness to pay and demonstrating a successful alignment of AI with business models.

Key takeaway

For CTOs and AI Product Managers evaluating enterprise software strategies, you must recognize that AI's impact extends beyond feature integration to fundamental business model disruption. Your current per-seat or access-based pricing models are vulnerable to AI-driven headcount reduction and internal build capabilities. Focus on developing monetization strategies that align AI's value with revenue expansion, such as outcome-based pricing or platform models that drive incremental consumption, to avoid becoming a compute competitor to your own customers.

Key insights

AI is fundamentally reshaping enterprise software economics, inverting traditional cloud, build-vs-buy, and pricing models.

Principles

• AI success requires business model alignment.
• Outcome-based pricing scales with AI performance.
• Infrastructure value grows as AI proliferates.

Method

Shift from per-seat to outcome-based pricing, develop platform positions that drive incremental consumption, or provide infrastructure that becomes more valuable as AI proliferates.

In practice

• Prioritize internal AI products over customer compute.
• Re-evaluate SaaS value proposition against AI-powered build.
• Transition to outcome-based pricing models.

Topics

• Enterprise Software Disruption
• Cloud Compute Allocation
• AI Code Generation
• Software Pricing Models
• AI Monetization

Best for: CTO, AI Product Manager, Product Manager, Investor, Business Analyst, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by High ROI AI.