The Rise of the Agentic Enterprise: What We Learned at Dreamforce 2025
Writing AI Agent
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Oct 13, 2025
AI is no longer just a tool - it’s becoming a teammate. At Dreamforce 2025, the spotlight was on the "agentic enterprise", where AI agents are deeply integrated into workplace systems to assist with repetitive tasks, provide timely answers, and enhance collaboration. These agents are designed to work alongside humans, delivering knowledge at the point of need and streamlining workflows in platforms like Slack.
Here’s what stood out:
Agentforce 360: Salesforce’s new platform connects AI agents to enterprise data while ensuring human oversight, enabling smooth collaboration and secure decision-making.
Slack Integration: AI agents embedded in Slack now respond to common questions, organize knowledge, and even escalate issues to human experts when needed.
Data 360 and Customer 360: These tools ensure AI agents have access to accurate, real-time data, improving reliability and security for enterprise operations.
Knowledge Management Solutions: Specialized tools like Question Base outperform general AI tools by offering verified answers, deeper analytics, and greater customization for enterprise needs.
As businesses grapple with remote work, scattered data, and rising support demands, these advancements are transforming how teams operate. Companies that embrace these tools today will build smarter, more efficient workplaces tomorrow.
Agentforce Keynote: Become an Agentic Enterprise
Major Announcements from Dreamforce 2025
At Dreamforce 2025, Salesforce introduced a suite of tools designed to enhance collaboration between AI agents, human workflows, and enterprise data systems. These announcements mark a shift from standalone AI tools to integrated systems that seamlessly fit into workplace environments. Below, we explore how these tools support the vision of an agentic enterprise.
Agentforce 360: Bridging AI and Human Collaboration
Agentforce 360 is Salesforce's cornerstone platform for agentic enterprises. It connects AI agents directly to company data while ensuring human oversight remains central. Unlike earlier AI tools that operated in silos, Agentforce 360 positions AI agents as collaborative teammates, working alongside human employees.
The platform streamlines workflows by integrating AI and human decision-making. For example, if an AI agent encounters a customer issue it can't resolve, Agentforce 360 automatically escalates the case to the right human expert, preserving the context of the interaction. This ensures a smooth transition, maintaining continuity for customers and internal teams alike.
What truly sets Agentforce 360 apart is its enterprise-grade governance system. Organizations can define clear parameters for AI behavior, implement approval workflows for sensitive tasks, and maintain detailed audit trails for AI-driven decisions. This framework addresses compliance and security concerns, which have often been barriers to adopting AI at scale.
Additionally, the platform includes real-time learning features. When a human expert corrects an AI response or provides additional context, that knowledge is shared across the system, creating a self-improving knowledge base that enhances future interactions.
Slack's Role in Agentic Workflows
Salesforce has also reimagined Slack's role, making it the primary hub for human-AI collaboration. This approach acknowledges that employees are most effective when AI tools are embedded directly into their existing workflows, eliminating the need to juggle multiple applications.
With this integration, AI agents can actively participate in Slack conversations, offering relevant insights and suggestions without interrupting the natural flow of communication. Slack's threading feature becomes a key asset, allowing AI agents to provide detailed responses in threads while keeping the main conversation focused. This ensures that AI contributions are both helpful and unobtrusive.
The platform also supports context-aware AI assistance, tailoring responses to specific channels or teams. For example, an AI agent in an HR channel will use terminology and knowledge relevant to HR, while an agent in an engineering channel adapts its responses accordingly. This contextual understanding makes AI support feel more intuitive and aligned with departmental needs.
Data 360 and Customer 360: The Backbone of AI Accuracy
Salesforce's Data 360 and Customer 360 applications provide the essential infrastructure that powers AI agents with accurate and up-to-date information. These tools address a critical challenge for agentic enterprises: ensuring AI agents have access to reliable, real-time data.
Data 360 consolidates enterprise data from various sources into a unified system. This means AI agents can pull the latest information on customer status, inventory, or project timelines, ensuring responses are accurate and informed. The platform guarantees that AI agents work with clean and trustworthy data.
Customer 360 builds on this foundation for customer-facing operations. It compiles customer interactions into detailed profiles, enabling AI agents to deliver personalized and effective responses. For example, when a customer service agent handles a query, they can instantly access the customer's full history, streamlining the interaction.
Both platforms include intelligent data governance tools that restrict AI agents' access to only the information they're authorized to use. This ensures that organizations can deploy AI agents widely without compromising data security or privacy. Access levels can be tailored to the function of each AI agent and the sensitivity of the data they handle.
Together, these tools create a robust data framework, ensuring AI agents operate with precision while meeting the security and compliance needs of enterprise organizations.
AI-Powered Slack Agents for Knowledge Management
At Dreamforce 2025, a spotlight was placed on how enterprises are embedding intelligent agents directly into Slack workflows. These agents are transforming how teams access information, making it available right when it’s needed. Let’s explore how they automate repetitive tasks, preserve critical knowledge, and connect seamlessly with trusted documentation.
Automating Repetitive Questions and Requests
AI-powered Slack agents are a game-changer for HR, IT, and support teams, handling routine inquiries with ease. Research shared at Dreamforce 2025 revealed that integrating generative AI into Slack workflows can increase employee performance by 40%. Considering that 60% of enterprise budgets typically go toward human capital, this improvement is no small feat[1]. These agents provide instant answers to common questions about policies, technical procedures, and operational processes, freeing up human experts to tackle more complex problems.
But their capabilities don’t stop at answering questions. These AI agents can take proactive actions within Slack, such as creating project channels, updating shared resources, or sending direct messages to escalate issues[1]. For instance, if an employee asks about requesting new software, the agent might not only share the relevant policy but also set up a dedicated channel and loop in the appropriate IT staff.
Preserving Knowledge from Slack Conversations
In addition to automating inquiries, these agents play a vital role in preserving organizational knowledge. By extracting key details from Slack conversations and organizing them into a searchable FAQ, they ensure that valuable insights don’t get lost in endless message threads. This approach reduces reliance on individual team members and makes critical knowledge accessible across the organization.
Connecting to Trusted Documentation Sources
The reliability of these agents comes from their ability to pull data from verified sources. By integrating with platforms like Notion, Confluence, and Salesforce, they deliver accurate, up-to-date information. For example, when handling a question about customer onboarding, an agent might pull account setup details from Salesforce, operational steps from Notion, and technical guidelines from Confluence. This eliminates the need for manual cross-referencing, offering a comprehensive answer in seconds.
These agents also ensure that responses are both accurate and secure. By adhering to established security protocols and access controls, they guarantee that employees receive only the information they’re authorized to view. This combination of real-time accuracy and robust security builds trust and efficiency within teams.
Question Base vs. Slack AI: Enterprise Knowledge Management Comparison
After Dreamforce 2025, many organizations are taking a closer look at AI tools to streamline their Slack workflows. Choosing the right solution is a key step toward improving operational efficiency. While Slack AI brings useful features for general productivity, Question Base is designed to address enterprise-level knowledge management challenges, particularly for internal support teams.
Feature Comparison Table
Feature | Question Base | Slack AI |
|---|---|---|
Accuracy | Provides expert-verified answers from trusted documentation | Relies on AI-generated responses based on Slack message history |
Data Sources | Integrates with tools like Notion, Confluence, Salesforce, Google Drive, Zendesk, and Intercom | Primarily uses Slack conversations; external integrations available with enterprise plans |
Knowledge Management | Includes thread summarization, tracking unanswered questions, and automated FAQ creation | Offers basic search and summarization features |
Analytics | Tracks resolution rates, automation metrics, knowledge gaps, and generates content audit reports | Provides general usage statistics |
Enterprise Security | Ensures SOC 2 Type II compliance, on-premise deployment options, and white-labeling | Adheres to standard Slack security protocols |
Customization | Allows full customization of AI tone, escalation workflows, and content access controls | Offers limited customization options |
When Question Base is the Better Choice
Question Base stands out when enterprises need a dependable, scalable solution for managing knowledge. Whether it's HR teams addressing policy-related questions, IT departments organizing technical documentation, or operations teams managing intricate workflows, Question Base delivers the structure and reliability that Slack AI doesn’t aim to provide.
Unlike Slack AI, which relies on chat history that may become outdated, Question Base taps into your organization’s trusted documentation sources, such as Notion or Confluence. For instance, if an employee needs details about the latest software procurement policy, Question Base will pull the most current information directly from your documentation, avoiding reliance on potentially outdated Slack messages.
Additionally, Question Base provides in-depth analytics, including resolution rates, automation metrics, and knowledge gap identification. These insights help organizations keep their documentation updated and effective.
The platform also offers robust customization options, enabling teams to adjust the AI’s tone, create department-specific escalation workflows, and enforce strict access controls for sensitive information. This level of control is particularly valuable for handling confidential HR policies, technical procedures, or data compliance guidelines.
In contrast, Slack AI is primarily geared toward summarizing conversations and retrieving quick answers, making it less suited for comprehensive knowledge management.
What Slack AI Does Well
Slack AI shines when it comes to boosting general productivity and summarizing discussions. It’s especially helpful for catching up on missed conversations, creating summaries of long threads, and providing context for ongoing projects.
For situations where quick, ad-hoc information retrieval is necessary - like recalling details from a recent meeting or finding a decision made in a project channel - Slack AI offers an efficient way to locate relevant information within chat history.
Ultimately, the decision between these tools depends on your organization’s specific needs. Slack AI excels at summarizing past conversations, while Question Base transforms internal knowledge into verified, actionable insights that keep teams aligned and informed.
How to Implement AI-Powered Knowledge Solutions
Bringing AI-powered knowledge solutions into your organization requires a well-thought-out plan. Successful implementations focus on three key areas: a methodical rollout, selecting tools tailored to your needs, and addressing enterprise-level requirements to ensure long-term success. With insights from Dreamforce, here’s how to seamlessly integrate AI into your workflow.
Step-by-Step Implementation Guide
To start, conduct an initial evaluation by identifying your organization’s most common internal questions and the teams responsible for answering them. For example, HR often handles policy inquiries, IT tackles technical troubleshooting, and operations manages process-related questions. Documenting these patterns establishes baseline metrics to measure improvements.
Next, audit and organize your existing documentation. Take inventory of your information sources and pinpoint which ones are accurate and up to date. This ensures your AI agents pull reliable data and avoid outdated or contradictory information.
When it comes to the technical setup, solutions like Question Base simplify the process. You can install the app directly from Slack's App Marketplace and invite the bot into your busiest support channels using the /invite @questionbase command.
Integrate your primary documentation sources to give the AI access to your most frequently used materials. Question Base supports integrations with platforms like Notion, Confluence, Google Drive, Zendesk, Intercom, Salesforce, and Dropbox. Start small - connect one or two key sources, test the AI’s accuracy, and gradually expand integrations as needed.
Finally, customize AI responses and escalation workflows. Set clear rules for when the AI should escalate queries to human experts, and establish protocols for handling sensitive topics like HR policies or compliance-related issues. This ensures a smooth balance between automation and human oversight.
General vs. Specialized Tools: How to Choose
Once you’ve mapped out your implementation process, it's time to choose the right tool for your organization. The decision between general-purpose tools and specialized knowledge management solutions depends on your needs and scale.
General-purpose tools like Slack AI are excellent for tasks like summarizing conversations or retrieving information from chat history. These work best for smaller teams with informal knowledge-sharing needs.
On the other hand, specialized tools are crucial when accuracy, compliance, or structured knowledge management takes priority. If your organization deals with sensitive data, complex technical documentation, or strict regulatory requirements, a tool designed specifically for enterprise knowledge management is a better fit.
Specialized solutions shine in scenarios where teams repeatedly ask the same questions, where incorrect information could disrupt operations, or where detailed analytics on knowledge gaps are necessary. These tools can automate routine responses while also identifying areas where documentation needs improvement.
When weighing your options, consider the return on investment (ROI). General tools may seem less expensive upfront, but specialized solutions often save more in the long run by reducing support costs and improving efficiency. For instance, Question Base’s Pro plan, priced at $8 per user per month, helps cut down on repetitive queries, freeing up employees’ time for higher-value work.
What to Consider When Scaling Knowledge Management
Scaling your AI-powered knowledge base is essential for building a more efficient and responsive organization. Here are some key factors to keep in mind:
Security and compliance: Ensure your solution meets enterprise-grade standards like SOC 2 Type II certification and includes encryption for data at rest and in transit. For sensitive data, consider on-premise deployment options.
AI governance frameworks: As your implementation grows, establish policies and best practices to guide the ethical and responsible use of AI. These frameworks help manage risks, align AI initiatives with company values, and comply with regulations [2].
Integration flexibility: As your needs evolve, your tools should adapt. Question Base supports multiple Slack workspaces, white-labeling, and custom development, ensuring you won’t need to switch platforms as your organization scales.
Content governance: As your knowledge base expands, assign clear ownership for different documentation areas, schedule regular reviews to keep information accurate, and develop processes to retire outdated content. Use analytics to identify and fill knowledge gaps, ensuring your resources remain valuable.
Change management: Gaining organizational buy-in can be a bigger challenge than the technical setup. Start with pilot programs in departments eager to improve knowledge sharing. Use measurable results from these pilots to drive broader adoption across the company.
The most effective implementations treat AI-powered knowledge tools as dynamic systems that grow and improve over time. Regularly review AI responses, integrate new documentation, and fine-tune workflows to ensure these tools continue delivering value as your organization’s needs evolve. By doing so, you’ll not only enhance efficiency but also create a more informed and empowered workforce.
Conclusion: The Future of Agentic Enterprises
Main Takeaways from Dreamforce 2025
Dreamforce 2025 showcased a new era of AI integration and knowledge management for enterprises, offering a glimpse into how AI is reshaping the way organizations operate.
One standout theme was the rise of the agentic enterprise model - a concept where AI agents are not isolated tools but interconnected systems designed to complement human expertise. Salesforce's Agentforce 360 platform exemplified this by demonstrating how AI and human collaboration can streamline workflows. Meanwhile, their Data 360 and Customer 360 apps highlighted the importance of integrated data in powering these intelligent systems.
Slack emerged as a hub for agentic workflows, evolving beyond its role as a communication tool. It now acts as a central platform where AI agents handle routine questions and provide employees with instant access to accurate information. This shift directly tackles a major challenge: the significant time employees lose when searching for answers or waiting for responses from colleagues.
Another key takeaway was the emphasis on specialized AI solutions for enterprise knowledge management. While general-purpose AI tools are excellent for broad tasks, platforms like Question Base are tailored to meet the unique demands of large organizations, offering the precision, security, and scalability they require.
What's Next for Agentic Solutions
The journey toward fully agentic enterprises is just beginning, with the future promising even deeper integration and smarter automation. Organizations are moving beyond basic chatbots to create knowledge ecosystems that learn from every interaction and continuously refine their responses.
Security and compliance will take center stage as these systems handle increasingly sensitive data. Features like SOC 2 Type II compliance, encryption at rest and in transit, and on-premise deployment options will no longer be optional but essential. As AI adoption grows, companies cannot afford to compromise on data protection.
The next wave of innovation will focus on predictive knowledge management - systems that anticipate what teams need before they even ask. By analyzing project timelines, seasonal trends, and organizational shifts, these solutions will transform onboarding, knowledge transfer, and operational continuity. Platforms like Question Base, which already pull trusted data from multiple sources, offer a glimpse into this proactive future.
Integration flexibility will also be a key factor in determining which solutions succeed. With organizations relying on diverse tech stacks, AI agents must seamlessly connect with tools like Notion, Confluence, Salesforce, and Google Drive. The most successful platforms will adapt to existing workflows rather than forcing companies to overhaul their processes.
Ultimately, the organizations that thrive will be those that see AI not as a replacement for human expertise but as a tool to amplify it. By automating repetitive tasks and delivering relevant knowledge instantly, AI will free up human teams to focus on creative, strategic, and complex problem-solving.
The future starts with small, focused implementations. Companies that begin by deploying AI agents for specific tasks, such as HR or IT support, will find it easier to scale these capabilities across their operations. The key is selecting solutions that grow with your needs while maintaining the precision, security, and customization essential for enterprise success.
FAQs
What is an agentic enterprise, and how is it different from traditional workplace AI solutions?
An agentic enterprise describes an organization that leverages AI systems designed for autonomous, goal-oriented decision-making. Unlike conventional AI, which typically reacts to specific commands or operates within set guidelines, agentic AI evaluates situations, adjusts its strategies, and takes proactive steps to meet the enterprise's objectives.
This model allows for more intelligent and adaptable workflows, enabling AI to function with a higher degree of independence. It supports areas such as knowledge management, internal support, and process improvement, going beyond basic automation to help organizations operate more effectively and strategically.
How does Salesforce's Agentforce 360 combine AI efficiency with enterprise-grade data security?
Salesforce's Agentforce 360 brings together AI-driven efficiency and enterprise-level data protection by pairing advanced AI tools with Salesforce's well-established security framework. It operates on a unified AI platform that features enhanced reasoning capabilities, low-code development options, and secure deployment strategies.
With the support of Salesforce's Data Cloud, Agentforce 360 ensures that AI outputs are based on precise, real-time data while adhering to rigorous privacy and compliance standards. This enables organizations to automate processes and optimize operations, all while safeguarding data integrity and security.
How do AI-powered Slack agents boost team productivity and streamline knowledge management?
AI-powered Slack agents boost productivity by providing precise, expert-backed answers straight from reliable platforms like Notion, Confluence, and Salesforce. This eliminates the hassle of manual searches, saving time and effort. Instead of relying on outdated methods, these agents streamline information retrieval, minimize redundant work, and ensure teams can quickly find the details they need to focus on more impactful tasks.
They also strengthen knowledge management by supporting scalable information sharing with tools like case tracking, duplicate detection, and adjustable settings. These features help organizations preserve institutional knowledge, keep teams aligned, and enhance overall efficiency.