“软件已死，AI当立”？

Core Viewpoint - The article discusses the transformative impact of AI on the software industry, suggesting that AI could act as a "force multiplier" for leading suppliers rather than being a disruptive force that undermines existing business models [2][3][4]. Group 1: AI's Role in the Software Industry - AI is seen as a potential "force multiplier" for industry leaders, similar to the transition from on-premises software to cloud computing, which led to the emergence of new leaders and the transformation of established companies like Adobe and Intuit into larger, faster-growing, and more profitable entities [2][4]. - Concerns about AI replacing traditional software have led to significant market reactions, such as SAP's stock dropping 7.1%, resulting in a loss of nearly €22 billion in market value [3]. - High expectations for AI's contribution to revenue stability and growth are anticipated as the pressure from enterprise software renewal cycles eases by 2026 [4]. Group 2: Challenges for AI-native Companies - The debate centers on whether AI-native companies can offer products that are "meaningfully better and cheaper" than existing SaaS solutions [6]. - The entry barriers for enterprise software are significantly higher than for consumer software, primarily due to the critical nature of tasks involved [11]. - AI-native companies face challenges in pricing strategies, particularly in providing value-based pricing models that could threaten traditional seat-based pricing [6][7]. Group 3: Hybrid AI Strategies - Major software companies are adopting hybrid AI model strategies, combining proprietary data-driven models with external large language models (LLMs) to enhance their offerings while maintaining competitive advantages [9]. - This strategy helps mitigate risks from AI-native competitors by locking customers into familiar and integrated ecosystems [9]. - The complexity of enterprise workflows and high data migration costs make it difficult for AI-native products to gain customer trust and adoption quickly [9]. Group 4: Future Indicators to Monitor - Key indicators to watch include the stability of Net Revenue Retention (NRR), which has faced significant pressure in recent years due to pandemic-related demand peaks [15]. - The contribution of AI to revenue growth is crucial, with companies like Adobe projecting $250 million in annual recurring revenue from AI products by the end of 2025 [15]. - Feedback from customers regarding SaaS leaders' innovations and the development momentum of AI-native companies will be essential in assessing their long-term impact on existing profit pools [15].