AI Is Finally Eating Software’s Total Market: Here’s What’s Next

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

Summary

The software industry is entering a multi-year contraction, with AI disrupting traditional SaaS business models and shrinking the overall software market. Analysts like Jeffrey Favuzza and Jeff Blazek note that while not all SaaS companies will fail, many incumbents face significant challenges, and only a "small handful" will achieve superior returns. The disruption stems from AI's ability to reduce the cost of building applications, making internal development more viable than purchasing SaaS solutions. Companies that adapt by focusing on "intent and outcome" touchpoints, such as integrating AI into existing workflow gateways like Slack, Outlook, or chat apps, are better positioned. Salesforce, SAP, and Moltbot/OpenClaw are cited as examples of companies leveraging this strategy. Leaders who fail to adopt a challenger's mindset and learn new capabilities risk obsolescence, as seen with Intel and potentially OpenAI, while Palantir's early adaptation serves as a success model.

Key takeaway

For VPs of Engineering or Data grappling with AI's impact on your software strategy, you must pivot from traditional SaaS assumptions. Focus on integrating AI into core intent and outcome touchpoints within your customers' workflows, rather than relying on standalone applications. Your teams should actively learn and adopt new AI capabilities, potentially by bringing in external experts, to adapt your operating model and capitalize on the reduced cost of building custom solutions, thereby securing your competitive position.

Key insights

AI is shrinking the software market, forcing SaaS companies to adapt or face obsolescence by focusing on intent and outcome.

Principles

• Own intent and outcome touchpoints.
• Adapt business models to lower building costs.
• Adopt a challenger's mindset for survival.

Method

Position AI applications and agent interfaces at critical points of user intent (e.g., chat apps, email clients) or outcome delivery (e.g., meeting platforms) to capture value and maintain relevance in workflows.

In practice

• Integrate AI into existing workflow gateways.
• Leverage internal data for defensible moats.
• Bring in external expertise to upskill teams.

Topics

• AI Disruption
• SaaS Business Models
• AI Monetization
• Agentic AI
• Intent-Driven Platforms

Best for: Investor, Entrepreneur, VP of Engineering/Data, Executive, CTO, AI Product Manager

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