AI is rewriting the enterprise software business model

Key Takeaways

• The traditional enterprise software business model is being disrupted by the rise of AI and data-driven decision making
• Companies need to develop a clear AI strategy, assess their organizational readiness, and evaluate their infrastructure to succeed
• The cost of using AI-powered software is no longer predictable and is increasingly based on activity, such as AI inference, API calls, and data access
• Executives must understand the financial consequences of AI adoption and make informed decisions about governance and infrastructure

The Shift in Enterprise Software Business Model

The way companies purchase and use technology is undergoing a significant transformation. For decades, the process was straightforward: executives selected the platform, procurement negotiated the contract, and finance approved the budget. However, with the rise of AI, the value of data is breaking this traditional model. According to China Widener, vice chair for technology, media, and telecommunications at Deloitte's U.S. practice, companies that succeed in the next several years will be those that make better executive decisions about AI governance.

Challenges in AI Adoption

Widener highlights three common issues that companies face when adopting AI:

1. Lack of clear strategy: Up to 80% of companies are in the early stages of thinking about their AI strategy or haven't yet developed a clear plan.
2. Organizational readiness: Companies must determine whether their people have the right skills and whether they have embraced AI enough to deploy it at scale.
3. Infrastructure readiness: Companies must assess whether their infrastructure is ready to support AI adoption, which is changing the economics of enterprise software.

Comparison of Traditional and AI-Powered Software Costs

The Importance of AI Governance

As AI adoption becomes more widespread, executives must understand the financial consequences of their decisions. The cost of using AI-powered software is no longer predictable and can vary significantly based on usage patterns. Companies must develop a clear AI strategy, assess their organizational readiness, and evaluate their infrastructure to succeed in this new landscape.

Bottom Line

The traditional enterprise software business model is being disrupted by the rise of AI, and companies must adapt to succeed. By developing a clear AI strategy, assessing organizational readiness, and evaluating infrastructure, executives can make informed decisions about AI governance and ensure that their companies remain competitive in a rapidly changing landscape. With the right approach, companies can harness the power of AI to drive innovation and growth, while minimizing the risks and costs associated with adoption.