{"id":90699,"date":"2025-10-22T09:00:00","date_gmt":"2025-10-22T16:00:00","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=90699"},"modified":"2025-10-22T13:04:48","modified_gmt":"2025-10-22T20:04:48","slug":"five-dreamforce-2025-takeaways","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/news\/stories\/five-dreamforce-2025-takeaways\/","title":{"rendered":"Five Key Takeaways from Dreamforce 2025"},"content":{"rendered":"\n

The transition to becoming an Agentic Enterprise<\/a> \u2014 where every company operates with boundless capacity, precision, and speed by pairing human expertise with AI-powered agents<\/a> \u2014 is not just an upgrade. It is a fundamental shift that can create entirely new capabilities, revenue streams, and ways of working. At Dreamforce 2025<\/a>, attendees had the opportunity to explore what that looks like from a range of angles, whether they are CIOs at large organizations or founders and small business owners. <\/p>\n\n\n\n

To become truly Agentic Enterprises, Salesforce Chair and CEO Marc Benioff said on stage during his opening keynote<\/a>, \u201cYou have got to get your data right. You have got to get to more integrated solutions. You have got to get the priorities right. You have to get the governance right.\u201d He mentioned a recent MIT study<\/a> that showed that generative AI pilot projects tend to fail.<\/p>\n\n\n\n

\u201cWe all saw that just making our own models or rolling it ourselves, or DIYing it, isn’t going to do it. We need to all be on this journey together to get to this better place that, in our vision, is the Agentic Enterprise.\u201d Here\u2019s what you need to know about getting started on that journey.<\/p>\n\n\n\n

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We all saw that just making our own models or rolling it ourselves, or DIYing it, isn’t going to do it. We need to all be on this journey together to get to this better place that, in our vision, is the Agentic Enterprise. <\/p>\nMarc Benioff, Chair and CEO at Salesforce <\/cite><\/blockquote>\n\n\n\n

1. To become an Agentic Enterprise, focus on scalable, sustainable change<\/strong><\/h2>\n\n\n\n

One of the sessions was a series of roundtable discussions about building a successful Agentic Enterprise<\/a>, and it kicked off with an honest dose of reality: everything\u2019s changing, nothing feels stable, and everyone\u2019s boss suddenly wants \u201call the AI.\u201d The message? Identify a single small use case, refine it, and build your Agentic Enterprise from there. <\/p>\n\n\n\n

The presenters and audience alike wrestled with the tension between ambition and readiness: AI<\/a> is moving fast, but adoption requires grounding in solid data, thoughtful design, and a deep understanding of how people actually do their jobs. Success depends on getting the right information to the right agent \u2014 human or digital \u2014 at the right time.<\/p>\n\n\n\n

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AI is moving fast, but adoption requires grounding in solid data, thoughtful design, and a deep understanding of how people actually do their jobs.<\/p>\n<\/blockquote>\n\n\n\n

To do that, data, data, data is key, and in another session, Salesforce on Salesforce: 5 Agentic Lessons, <\/em>executives shared a tidy framework based on Salesforce\u2019s experience as customer zero for other companies as they seek to become Agentic Enterprises:<\/p>\n\n\n\n

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  1. Start small and go fast<\/li>\n\n\n\n
  2. Test, tune, repeat<\/li>\n\n\n\n
  3. The right data is gold<\/li>\n\n\n\n
  4. Measure value and impact<\/li>\n\n\n\n
  5. Embrace new ways of working<\/li>\n<\/ol>\n\n\n\n

    When the roundtable discussion turned to business priorities, the common driver was clear: do more with fewer people. Teams are stretched thin, yet expectations for customer experience remain sky-high. The promise of AI, many noted, lies not in replacement but in elevation \u2014 helping humans work smarter and deliver more.<\/p>\n\n\n\n

    A case study from RBC Wealth Management, presented by Greg Beltzer, Chief Customer Officer for AI, Agentforce at Salesforce, drove the point home. RBC\u2019s journey began with wealth advisors using AI to surface insights and save time during the meeting prep process. Because RBC had long treated data as a strategic asset, it was able to activate AI quickly and see tangible results: data completion rates soared, notes became richer, and adoption happened naturally \u2014 no incentives required. <\/p>\n\n\n\n

    The session closed on a human-centered note with William Dressler, Salesforce Global Head of AI Innovation, AI Practice, reframing \u201cAI architecture\u201d not as a tech stack, but as a blend of people, process, and trust. Building an Agentic Enterprise, he said, is as much about designing human-AI collaboration as it is about engineering systems. Without trust \u2014 especially in the data \u2014 AI can\u2019t take root. But with it, organizations can unlock something far more powerful than automation: alignment between human intelligence and machine capability.<\/p>\n\n\n\n

    2. CIOs need a new architecture for the Agentic Enterprise<\/strong><\/h2>\n\n\n\n

    The “Agentic Enterprise” requires a fundamental architectural shift, moving from the traditional seven-layer IT model to an 11-layer architecture<\/strong><\/a> designed specifically to support AI agents. This transformation is necessary to allow AI agents to be able to sense, reason, and act with increasing autonomy. The four new layers are: the Semantic Layer, which provides unified data understanding and context for agents to reason effectively; the AI\/ML Layer, which acts as a centralized intelligence hub for training and managing internal and external models; the Agentic Layer, which is the operational core providing frameworks and runtimes for building and executing agents at scale; and the Enterprise Orchestration Layer, which serves as the control plane for coordinating, governing, and optimizing workflows that span agents, humans, and deterministic systems.<\/p>\n\n\n\n

    To manage this shift, enterprises should adopt a phased approach that delivers tangible business value at each step, moving from basic information retrieval to full multi-agent, cross-domain orchestration. This journey begins with Phase 1: Information Retrieval Agents, focused on building a trustworthy data foundation and the basic AI components needed for information retrieval through the agentic, AI\/ML, and semantic layers. Once trust is established, move on to Phase 2: Domain-Specific Agent Workflows, where agents shift to “action-oriented” tasks within a specific area. The final stages are Phase 3: Cross-Domain Orchestration, automating complex processes that span organizational silos, and Phase 4: Multi-Agent, Multi-Domain Orchestration, which creates a holistic digital simulation of the enterprise for continuous improvement and strategic planning. <\/p>\n\n\n\n

    These changes are more than a technical upgrade; they\u2019re part of a strategic journey that helps enterprises truly harness the power of autonomous agents.<\/p>\n\n\n\n

    3. For AI to truly empower companies, it has to be deeply integrated across the product suite <\/strong><\/h2>\n\n\n\n

    In the last 26 years, more than 20 million potential customers contacted Salesforce and Salesforce didn\u2019t call them back. \u201cWe didn\u2019t have enough people,\u201d said Benioff during his keynote. \u201cIt fueled our competitors.\u201d Now, the Salesforce SDR agent handles 50,000 customers a week. It can do that because it\u2019s deeply integrated with the Sales Cloud and Agentforce 360 Sales, he told the audience.<\/p>\n\n\n\n

    If companies are going to use AI to operate with this kind of intelligence and speed, their tools need to have that kind of integration with each other and across the enterprise. That, he said, is what Agentforce 360 is.<\/p>\n\n\n\n

    Introduced during Benioff\u2019s opening keynote, Agentforce 360<\/a> is the fourth edition of Agentforce<\/a>, and now it\u2019s the platform that powers everything Salesforce does, bringing together the four ingredients of an Agentic Enterprise: <\/p>\n\n\n\n