How to Enable Agentforce in Salesforce Right Now: An Implementation Guide

This comprehensive guide explains how to enable Agentforce in Salesforce, integrate Agentforce with your existing Salesforce environment, and enable it for measurable business success. Learn how to benefit from AI agents and get guidance about how to get started.

In brief:

• Agentforce success starts with planning. Organizations must assess data readiness, define use cases, and align stakeholders before enabling Agentforce.
• Security and cost concerns are common. Salesforce’s Einstein Trust Layer addresses data protection, and ROI calculators can help you justify your investment.
• Cross-functional teams are key. AI agents thrive when built collaboratively across departments, not in silos.
• Begin with low-lift, high-impact workflows and expand as your team gains confidence.
• Track ROI through reduced human effort, improved customer metrics (NPS, CES), and operational efficiency.

Salesforce Agentforce is the new agent-centric artificial intelligence (AI) platform from Salesforce, designed to automate workflows, enhance sales and marketing efforts, and boost productivity. In our previous blog post, we covered the fundamentals of Agentforce and its functionality across the Salesforce ecosystem. Now, we’ll dive into how to enable Agentforce in Salesforce for measurable business success.

If you’re ready to take action, we’ll guide you through step-by-step assessments of readiness across your organization.

Enable Agentforce With Strategic Planning and Organizational Change Management

Agentforce includes the user-facing Agent Builder, the behind-the-scenes Einstein model, and the Agent Console. With these tools, users can create, train, and deploy different AI agents. Agentforce uses data, reasoning, and actions to perform tasks, which can lead to significant competitive advantages and benefits for your business.

However, one of the most significant factors in an AI agent’s success is ensuring that your business is ready across both people and technology. Many companies rush to implement shiny new AI without considering data security, internal resources or change management.

Do a Business Readiness Assessment for Integrating Agentforce in Your Salesforce Organization

My colleague and Salesforce expert Betsy Stokes explains that turning on Agentforce is not simply the push of a button: “It’s important for organizations to focus on the prework of setting up Agentforce — thinking through data readiness and appropriate use cases prior to rolling it out. Another important thing to avoid is chasing the shiny object. AI is very exciting, but it’s important to think through the appropriate use cases and where it fits before rolling it out.”

Preparation matters, so consider the following to focus on a smooth Agentforce deployment:

• Gather stakeholder alignment and executive buy-in to ensure you’re all on the same page.
• Start by assessing your current Salesforce workflow and process maturity. For example, are you already using automated lead routing or triggers for content personalization?
• Assess your business’s cultural readiness for Agentforce adoption. Do you have the resources to train, onboard, and upskill workers in emerging technologies?
• Consider your compliance and governance frameworks. Agentforce comes with built-in safety and privacy guardrails, but you should also analyze any industry-specific compliance regulations or unique data security needs.

“The biggest consideration for clients thinking of implementing agents in their Salesforce instance is 1) What will the agents do? 2) What information does the agent need to do its job? And 3) Is that information already available within Salesforce?” Stokes says.

If the use case requires external data from a billing or enterprise resource planning (ERP) system, then also consider integrations.

Build a Cross-Functional Team

AI agents can’t succeed if they’re built in a silo within revenue operations or IT. A cross-functional team will help you acquire the right resources, gain executive buy-in, and keep the AI agents grounded in practical application. Bring in different levels of technical users, and consider including some potential change management champions to drive adoption after launch.

Establish a Comprehensive Change Management Strategy

Around 70 percent of projects fail, and it’s often because of poor change management. Establish consistent and clear communication and timelines across all teams, and engage stakeholders at various levels. Proactively address employee concerns and combat any resistance with internal champions and advocates. Share the “why” behind AI agents as well as key performance indicators (KPIs) you’ll be measuring along the way.

This might include:

• Reorganize and restructure teams or roles to take on new responsibilities
• Plan for any customer-facing changes
• Train and upskill existing team members in AI best practices
• Create support and resources
• Develop internal Agentforce enablement programs
• Decide on KPIs, measure success, and drive feedback loops for what’s working and what’s not

With any technical project, strong change management protocols ensure adoption goes smoothly. However, AI agents require even more oversight and human input.

Create a Cultural Integration Strategy

It’s natural that some employees might feel resistant to AI-driven change. Embed AI improvements into your company’s culture and values by encouraging team members to grow professionally and rewarding those who lean into new technologies.

“Prepare for change resistance when considering organizational readiness for Agentforce,” Stokes says.

As you prepare to adopt Salesforce Agentforce, you may run into adoption barriers. Let’s discuss two of the most common ones — and how to overcome them.

Overcome Common Agentforce Adoption Barriers

The two biggest barriers we see clients face when adopting Agentforce are data security concerns and implementation costs. Here’s how to overcome these issues.

Data Security Concerns

We still hear many concerns about data security from clients who are considering AI. Salesforce’s Einstein Trust Layer can help alleviate some of those legitimate concerns.

Salesforce’s Einstein Trust Layer includes numerous security features: zero-data retention, dynamic grounding, data masking, prompt defense to reduce hallucinations, toxicity scoring, and auditing.

Cost Implementation Concerns

Additionally, there are concerns about the costs of implementing Agentforce in Salesforce — both the initial setup costs and the long-term usage costs. While costs are definitely a consideration for clients, we have calculators to help clients measure return on investment (ROI) and determine where and how agents make the most sense.

To maximize your Salesforce investment with intentionally and thoughtfully planned AI agents, you must first clean up data, create a training plan for users, and establish guardrails.

Once you’re ready with a cross-functional team, a business readiness assessment, and a comprehensive change management strategy, it’s time to move on to technical implementation.

How to Implement Salesforce Agentforce: A Week-by-Week Guide

If your stakeholders are aligned and you have a change management plan in place, you’re ready to implement Agentforce. Take a look at an example week-by-week breakdown below.

Week 1: Establish Your Business Case for Using Agents

Your first step needs to be identifying why and how you want to use AI agents.

Build a business case for technology first to ensure any new solution you implement aligns with your organization’s strategic goals and will deliver measurable value. Otherwise, you might be chasing technology for the sake of technology.

When you clearly define objectives, expected outcomes, and potential ROI, stakeholders can make informed decisions and prioritize technology investments that are most likely to drive success.

This approach also helps secure buy-in across departments, reduces the risk of wasted resources, and sets the foundation for a smooth implementation process that supports long-term adoption and growth.

Week 2: Assess Your Environmental Prerequisites for Agentforce

Second, assess the Salesforce cloud environment and compatibility. You may need to upgrade your license or adjust your permissions. Review what external data, if any, you need to support your chosen use cases, and determine if you’ll need Data Cloud to help consolidate your data. You might need to perform a data hygiene cleanup.

Action Item: Perform basic technical prelaunch requirements such as:

• Confirm you have the right Salesforce license tier.
• Verify user permissions across different roles to ensure all the right people have access.
• Double-check the integrations and connections within Data Cloud.
• Check data hygiene to clean up duplicates, archive irrelevant data, and consolidate naming conventions and structure.

Weeks 3–5: Develop Your Salesforce Agents

Now, it’s the fun part — selecting use cases and beginning to build your first AI agent. Identify quick wins across your organization that could use a major upgrade with AI. Develop a prioritization framework that scores high impact versus high lift.

Start with the Agent Builder, a low-code builder that works with natural language descriptions. Write what you want the AI agent to do, and connect a library of actions from existing business logic. Test, gather feedback, and enable your AI agent to learn like a human employee.

Use Case: For example, your first AI agent could start with a prebuilt flow to automate sales discovery. It could pull in any company data from Salesforce, such as revenue size, industry, or other account details, and then craft a personalized discovery email. Then, the AI agent logs the email activity as an interaction. A human business development representative is valuable input on this output since this automates one of their core daily activities.

Weeks 6–7: Deploy Your Agentforce Pilot

Once your AI agents are ready, launch a pilot program to test each agent’s functionality. Ask test users for specific feedback and have them test the agents in real-world scenarios.

A soft launch helps reduce risk by validating agents within real-world scenarios. Keep humans in the loop for feedback and validation, and build an escalation protocol if needed.

Stokes details critical success factors for Agentforce: “Human oversight, careful data readiness, and thoughtful rollout plans.”

Integrate and Scale Agentforce in Salesforce

AI agents are revolutionary because they are dramatically different from previous generative AI or basic automation. For example, early generative AI could answer questions — think basic support chatbots — or generate text, such as a meeting description.

However, the main difference is that new AI agents like Agentforce can take action and perform complex tasks across multiple systems. They’re dramatically more sophisticated and execution-oriented.

AI agents get even more powerful when you connect them to other third-party applications through application programming interface (API) or within Data Cloud. Salesforce already makes this process somewhat easy, and working with an expert partner unlocks the full business potential of AI agent development.

Once you’re confident with a small rollout plan of AI agents, it’s time to scale up and add new use cases. Starting with a workflow can be straightforward, and once your team is comfortable, you can scale up to more complex and sophisticated decision-making.

Stokes encourages businesses to think about sustainable scaling strategies: “Don’t simply invent more business problems for AI agents to exist.” If you encounter actual problems, refer to troubleshooting best practices.

Troubleshooting and Best Practices for Salesforce AI Agents

Salesforce Agentforce is user-friendly and low-code, but there are some common implementation challenges.

Common issues include integration challenges, data quality problems, escalation gaps, access errors, or logic and workflow issues. All of these technical issues can snowball, delaying implementation and launch, which is why it’s so important to assess business readiness properly.

After AI agents are launched, you need humans in the loop to continuously monitor and optimize your AI agents. New issues might arise as connected apps scale or users begin running workflows.

Stokes adds that businesses should start small to avoid feeling overwhelmed. “Start with one or two high-value but relatively low-lift workflows.”

Now that your AI agents are operational and optimized, it’s essential to measure their success and business impact.

Measure Agentforce Success: Business Impact and ROI

Establish goals and KPIs before launching your new AI agents. Across your organization, analyze comprehensive success metrics:

• Operational KPIs: Efficiency gains, response times, accuracy rates
• Business Impact: Cost reduction, revenue impact, customer satisfaction
• Organizational Metrics: User adoption rates, process improvement, employee satisfaction

You should also calculate and report the ROI of using Agentforce.

While one of the benefits of AI agents is cost savings, it comes at the expense of initial upfront investment costs. Closely consider costs, especially when it comes to Salesforce licensing requirements. Consider the internal time and effort required to launch AI agents, as well as any necessary third-party expertise and periodic monitoring.

“Consider the full implementation cost, including human effort to get the tool implemented, plus technology and subscription costs,” Stokes says. “Additionally, when AI is initially rolled out, many organizations still want a human in the mix to review responses and actions being taken by the AI agent.”

For a customer service agent, for instance, include a calculation of the reduced cost in human effort, potentially the number of full-time employees, plus any increases in customer service quality, which you can measure through metrics like net promoter score (NPS) or customer effort score (CES).

Get Started With Agentforce and Centric Consulting

Just like with standard Salesforce adoption, it might take internal teams time to adjust and adopt AI agents. Embracing AI is a journey, not a destination, and implementing Salesforce Agentforce helps you get the most out of your Salesforce ecosystem.

Begin by assessing your organizational readiness in terms of technology, data hygiene, and change management. Then, establish your functional team and KPIs and begin pilot programs and soft rollouts of AI agents.

Start your Agentforce journey with our Salesforce team. Contact our team today. Let’s talk