> **来源：[研报客](https://pc.yanbaoke.cn)** # Summary of "The new rules of platform strategy in the age of agentic AI" ## Core Content This report explores the evolution of enterprise platform strategy in the context of agentic AI, highlighting the need for a new approach that integrates AI, platforms, and human elements into a unified, adaptive architecture. It outlines five key priorities that companies must adopt to remain competitive in an AI-first world. ## Main Authors - **Frédéric Brunier**: Senior Managing Director—Global Lead – Technology Strategy and Lead – Strategy, EMEA. Focuses on aligning technology and AI with corporate and business strategies. - **Christopher Roark**: Senior Managing Director—Global Lead - Cost & Productivity and Lead - Strategy, Americas. Specializes in growth strategies and cost productivity reinvention. - **Surya Mukherjee**: Principal Director—Accenture Research. Leads cloud and platforms research and oversees the firm's Technology Research agenda in Europe. ## Key Findings - **AI and platform integration is critical**: Companies that align AI, platform, and business strategies outperform peers by a wide margin, with double the revenue growth and up to 37% higher profitability. - **The alignment gap**: Only 18% of companies fully align their AI, platform, and business strategies, leading to inefficiencies and missed opportunities. - **Platform evolution**: Enterprise platforms are shifting from static systems of record to dynamic systems of action, enabled by agentic AI's ability to reason, adapt, and act autonomously. - **Operational impact**: Companies that modernize their digital cores see significant benefits, such as faster onboarding, reduced processing times, and enhanced customer engagement. ## Key Terms - **Platforms**: Software systems used for daily business operations, including ERP, CRM, HR, and more. - **Agentic AI**: AI systems capable of acting autonomously or semi-autonomously, using reasoning and decision-making to complete tasks. - **Embedded AI**: AI capabilities integrated into existing systems and workflows to improve performance and insights. ## Two Forces Driving Change 1. **AI-driven transformation of work**: Generative and agentic AI are redefining work by automating tasks that once required human judgment and enabling new forms of collaboration. 2. **Business demands outpacing platforms**: As markets and customer expectations evolve rapidly, traditional platforms are no longer sufficient to meet the need for real-time adaptability and innovation. ## Five Priorities for Platform Strategy in an AI-First World 1. **Architect for the future** Build an AI-ready, platform-aware infrastructure that supports seamless integration and scalability. The focus is on creating a unified architecture that allows AI agents to operate effectively across systems. 2. **Design a fit-for-purpose foundation** Modernize the digital core to enable real-time data access, flexible workflows, and modular integration. A strong foundation is essential for AI to deliver sustainable value. 3. **Articulate the interplay** Define clear roles for humans, platforms, and AI agents. This involves mapping who does what and ensuring that automation, decision-making, and human oversight are appropriately aligned. 4. **Prepare for operating model reinvention** Reimagine how the enterprise operates to support AI-driven performance and agility. This includes rethinking workflows, roles, and decision-making processes. 5. **Transform culture** Equip employees with the trust, fluency, and mindset to lead in an AI-driven environment. Cultural transformation is key to enabling collaboration and innovation. ## Case Studies - **Lenovo**: Leveraged Adobe Experience Platform and Microsoft Copilot to scale AI across marketing, customer service, and internal workflows, resulting in $11 million in efficiency savings and a 12.5% increase in click-through rates. - **Zurich Insurance**: Developed an AI-powered CRM that centralizes customer data, integrates with external tools, and reduces service times by over 70%, shifting agents from transactional roles to trusted advisors. - **Mascoma Bank**: Consolidated 66 fragmented systems onto Salesforce Data Cloud, reducing onboarding times and processing PPP loans in just 13 days. - **Western Sugar**: Used SAP Ariba Central Invoice Management to automate 40,000 invoices annually, with minimal human intervention, and enabled finance teams to focus on strategic tasks. ## Conclusion The future of enterprise platforms lies in their ability to evolve into intelligent, adaptive systems that work in harmony with AI and human expertise. Companies must move beyond treating AI and platforms as separate domains and instead integrate them into a cohesive strategy. This requires a shift in mindset, architecture, and culture to unlock new levels of performance, growth, and innovation.