AI to strengthen enterprise software firms, not replace them: Goldman Sachs

In a recent report by Goldman Sachs, the outlook for enterprise software firms in the age of artificial intelligence (AI) has been notably optimistic. Rather than facing obsolescence, these companies are expected to strengthen their position as AI adoption enhances the value of enterprise data systems and the contextual intelligence that is built around them. The report challenges the prevailing notion that AI agents might replace enterprise software vendors, asserting instead that the foundational systems of record are crucial for the functioning of AI applications.

The Role of Systems of Record

Goldman Sachs emphasizes that systems of record, which are the databases and software that store and manage an organization's core business data, remain essential for AI applications. These systems provide the necessary training, grounding, permissioning, and contextual execution that AI relies on. The report states, "Systems of action, the applications that execute tasks and drive workflows, depend on systems of record for training, grounding, permissioning, and contextual execution." As AI usage expands, the report argues that the importance of these systems will increase rather than diminish.

The integration of well-governed data is highlighted as a critical factor for the performance of AI models. Fragmented datasets and isolated silos can severely limit the effectiveness of AI applications, particularly as these systems begin to operate across various business functions. This need for cohesive data management is expected to drive a continued migration towards cloud and data-platform architectures, despite potential short-term customer churn.

The Competitive Advantage of Contextual Layers

A key insight from the Goldman Sachs report is the assertion that raw enterprise data alone will not provide a sustainable competitive advantage in the AI era. Instead, the report posits that the true differentiator will be the contextual layer built upon this data. This layer includes workflows, metadata, permissioning, auditability, embedded business logic, and cross-functional reconciliation. Goldman Sachs states, "In our view, the contextual layer built on top is a defensible moat in the AI era that contains the processes, workflows, metadata, permissioning, auditability, embedded business logic and cross-silo reconciliation."

This contextual layer is crucial as it allows AI applications to deliver actionable, domain-specific business outcomes. Moreover, it is difficult to replicate, as it embodies years of implementation, operational controls, business exceptions, and institutional knowledge. This complexity and depth create a significant barrier for competitors who may attempt to enter the market with similar AI solutions.

Industry-Specific Software and AI Integration

The report also indicates that industry-specific or vertical software is likely to thrive alongside AI advancements rather than be replaced by them. Such platforms are designed around specialized workflows, regulatory requirements, proprietary data, and high switching costs, which create a robust framework for AI integration. Furthermore, AI-driven productivity gains could catalyze adoption in industries that have historically lagged due to a lack of technological talent.

Goldman Sachs notes that many large enterprises are increasingly opting to develop AI applications in collaboration with large language model providers and systems integrators while maintaining their existing enterprise software platforms. Collaborations involving companies like Stellantis, Mistral, Accenture, Palantir, Prometheus, and Schindler exemplify this trend, showcasing a strategic approach to harnessing AI capabilities without discarding established systems.

Looking forward, the report concludes that key competitive advantages for incumbent enterprise software companies will continue to include governance, auditability, trust, embedded customer relationships, domain expertise, and distribution networks. As AI adoption accelerates, these factors will play a crucial role in determining which companies succeed in the evolving landscape of enterprise software.

Why it matters

The insights from Goldman Sachs provide a clear perspective on the future of enterprise software in the context of AI. For creators and technologists, this means that rather than viewing AI as a threat to existing software solutions, there is an opportunity to enhance and build upon these systems. The emphasis on contextual layers suggests that those who can effectively integrate AI into their existing frameworks will have a competitive edge.

Moreover, the report highlights the importance of data governance and integration, urging organizations to focus on creating cohesive data environments that can support advanced AI applications. As industries increasingly adopt AI, the demand for specialized, industry-specific software solutions will likely grow, presenting opportunities for innovation and development in these areas. Overall, the findings underscore the potential for enterprise software firms to not only survive but thrive in the AI era, provided they adapt and evolve alongside technological advancements.