AIforce - The New Salesforce Ecosystem

As Dreamforce 2026 came to a conclusion, the buzzword is AIforce. With all the advancements and developments in Salesforce happening at breakneck speed, it has become increasingly difficult for consultants and the like to stay updated. Einstein, BOTs, CDP, Data Cloud, Data 360, Agentic AI, Agentforce, MCP, Headless Toolkit, Claudeforce and most recently, AIforce have ended up confusing many consultants in the industry. How do these products fit in and which one should be used, and when? Will Agentforce continue to exist with the announcement of Claudeforce and AIforce? These are questions which need to be answered with clarity.

As the products and technology evolved, Salesforce has managed to navigate the AI bubble and stay relevant, much as it has done with the CRM market it helped define. Agentforce is Salesforce's platform for building and deploying AI agents that can automate and execute tasks across Sales, Service, Marketing and other Salesforce applications. With the Einstein Trust Layer providing security and governance protections, the Atlas Reasoning Engine enabling agents to reason and make decisions, and well-grounded business data providing the necessary context, Agentforce can help companies accelerate sales processes and enhance customer service. Using the new Agentforce Builder, Salesforce allows users to describe what they want their agents to do using natural language. With the right instructions, actions, data and guardrails configured, an agent can be built, tested and eventually deployed.

Agentforce Agents

Agentforce agents can be analogous to robots or assistants that perform tasks based on how they are configured — through instructions and guardrails — and the data and context provided to them through grounding. An Agentforce Agent can comprise multiple subagents, each with its own instructions and actions. Associated channels define how agents interact with the outside world. Actions can be as simple as updating a field or summarizing a conversation and can be implemented using Apex, Flows and Prompt Builders. Agents are quite different from BOTs which relied on predefined rules and scripted responses while agents can reason using the available data, instructions and conversational context. Agents are also more dynamic in nature and support multiple languages.

Broadly, there are three ways to build agents. The recently released Agentforce builder accepts instructions in natural language, allowing an agent to be built using a more conversational approach. Agent Script can be leveraged by more tech-savvy developers for better control, while Agentforce DX is also available through Salesforce CLI & VS Code.

Testing any agent is paramount before deploying it. The Agentforce Builder offers Simulate and Live test modes. Agentforce Testing Center generates test cases and batch testing.

AIforce

AIforce has catapulted the Salesforce usage to new levels by reducing the need to log into the Salesforce User Interface. With AI increasingly becoming the new Salesforce UI, it encompasses Salesforce within other commonly used tools such as AI platforms like Claude and ChatGPT and collaboration platforms like Slack. This live interface opens up a wide range of possibilities while retaining Salesforce's security and permission controls. Claudeforce, Slackforce and Agentforce Coworker, launched alongside AIforce, offer unique advantages.

Claudeforce

AI and CRM are stitched together now. Salesforce in Claude offers 37 pre-built skills which add value for reps, such as pipeline management and deal reviews. The development plugin works with IDEs and fast-tracks development. Claude is also available within Salesforce Agentforce, making the partnership more interesting and powerful.

Slackforce

Slack CRM, Slackbot and Slack Code combine to help users create and update records, pull data to create interactive views, along with AI-assisted development.

Agentforce Coworker

Coworker runs within Salesforce and can use the available context, agents and actions to assist users with tasks and workflows. Instead of users having to manually perform every step, the Coworker can determine the appropriate actions. It can also call specialised Agentforce agents that have already been built and deployed.

Headless Toolkit

As AIforce has virtually detached the Salesforce Platform from a fixed UI or browser, it uses the underlying Headless Toolkit to empower other platforms and access Salesforce capabilities by leveraging MCPs, APIs, CLIs and Skills.

MCP Servers, APIs, CLI & Skills

Model Context Protocol is an open standard for accessing Salesforce tools outside its UI. It's a plug-and-play mechanism to access, query and update data while respecting assigned permissions. To give an example, a user using an AI tool like Claude or ChatGPT can request a report or ask to retrieve or update Salesforce data, and MCP provides the protocol through which the AI application can invoke the required Salesforce capability. Apart from the standard MCP servers available out of the box, custom ones can be created as well. MCP acts like a common adaptor between AI applications and external tools.

APIs and CLIs are relatively self-explanatory, while Skills are like command-based workflows which can be invoked when needed through AI tools. Agent Skills can be used to build applications, while Sandbox Skills can help manage environments.

Salesforce has stayed true to its number-one position and has been quick to introduce revolutionary and phenomenal additions to its ecosystem, as it usually does. Most of these features are planned for release soon, while some are still in the beta stage. The pricing needs further clarification as Salesforce moves towards bringing more of its AI features under the purview of Flex Credits.

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