AI isn’t a distant concept—it’s here, and it’s advancing the way businesses operate, measure impact, and scale results. That was the central theme of the Demystifying Agentforce webinar hosted by Coastal, Salesforce, and Salesforce Ben.
The webinar, featuring Sam Taylor, Coastal’s Director of Innovation and Emerging Technologies, and Sidd Shende, an Agentforce Product Manager at Salesforce, explored how Salesforce’s AI platform is helping organizations streamline workflows, deliver better customer experiences, and achieve a measurable Return on AI (ROAI).
Here’s what we learned: how Agentforce works, answers to key questions, and what initiatives to prioritize for quick results while setting up for future growth.
What is Agentforce, anyway?
Agentforce is Salesforce’s AI platform, described as a digital labor platform. It’s a system designed to help businesses scale productivity using Agentic AI, a type of artificial intelligence capable of working independently to complete tasks.
Unlike basic chatbots that follow a fixed script, Agentic AI is designed to think more independently. By combining advanced language models with your business data, these AI agents can assess information in context, spot patterns, and decide the next steps based on what they’ve learned—without waiting for a pre-set command. This flexibility allows them to take meaningful action with little to no oversight, handling tasks in a way that feels more like a capable teammate than a programmed tool.
Think of it as adding digital team members who don’t just assist—they take action. These agents can perceive their environment, reason through tasks, and complete multi-step processes independently, much like humans. For example, while some AI tools suggest next steps or surface insights for review, Agentforce agents can actively manage processes—like summarizing customer history, automating approvals, or resolving service inquiries—without needing human input at every stage.
Sam summed it up simply: “AI is here to take care of the tasks that don’t need human creativity so teams can focus on where they really make an impact.”
At the core of Agentforce is the Atlas Reasoning Engine, an advanced evolution of Salesforce’s Einstein AI. Atlas powers the platform’s ability to:
- Make Context-Aware Decisions: Agents can manage multi-step processes, assess data relationships, and deliver reliable, traceable outputs.
- Integrate Seamlessly: Built for the Salesforce ecosystem, Agentforce connects with tools like Slack, Data Cloud, and core CRM workflows, using your existing data for smarter automation without complex integrations.
- Scale with Your Business: Whether supporting a small admin team or automating enterprise-wide processes, Agentforce adapts to match your business needs.
Staying true to Salesforce’s clicks-not-code approach, Agentforce is designed for rapid deployment with minimal technical lift. Tools like Prompt Builder and pre-built agents make it easy to start small, demonstrate value quickly, and expand as your organization grows.
Sam and Sidd emphasized during the webinar: adopting AI doesn’t have to be overwhelming. Agentforce is built to fit into your existing systems, scale with your needs, and deliver meaningful results from day one.
Agentforce in Action: Real Examples That Deliver Results
Agentforce is already solving real problems for businesses. During the webinar, Sam and Sidd shared examples of how organizations use it to simplify processes and get more done with fewer complications.
Customer Service: Better Support at Any Scale
Agentforce transforms customer service by allowing teams to handle higher volumes without sacrificing quality.
- Automating Routine Inquiries: Businesses report resolving up to 90% of tier-one questions with Agentforce, handling tasks like answering FAQs, resetting passwords, and providing account updates.
- Improving Escalations: When issues require human involvement, Agentforce ensures all relevant context—like past interactions and preferences—is passed along seamlessly, speeding up resolution and improving the experience.
Example: Salesforce implemented Agentforce on help.salesforce.com, achieving an 83% resolution rate and cutting escalations to human agents by 50%.
Sam noted: “What we’re seeing with Agentforce is the ability for customers to get the answers they need faster and with fewer escalations. It’s about solving issues in a way that feels seamless, so customers don’t have to repeat themselves or face unnecessary delays.”
Sales Enablement: Helping Teams Focus on Closing
Agentforce makes it easier for sales teams to spend their time on the conversations and deals that matter.
- Qualifying Leads: By automating lead qualification, Agentforce helps sales teams zero in on the best opportunities.
- Providing Pipeline Insights: Real-time visibility into the pipeline ensures teams can prioritize effectively and identify deals that might need extra attention.
- Personalizing Pitches: Agentforce uses customer data to surface tailored recommendations so reps can come prepared with insights that resonate.
Sidd explained: “Sales teams are often working with overwhelming amounts of data. The power of Agentforce lies in its ability to surface the right insights at the right time so reps can focus on selling, not searching.”
Operational Efficiency: Simplifying the Complex
Sam and Sidd emphasized operational efficiency is where many businesses see immediate value with Agentforce. It’s not about adding more tools—it’s about simplifying how work gets done.
- Summarizing Data: Salesforce contains so much information that finding what matters can feel overwhelming. Agentforce generates summaries highlighting key details, giving teams what they need at a glance.
- For example, Teams can add AI-generated summaries directly to Salesforce records, saving time and helping employees make faster decisions.
- Speeding Up Approvals: Traditional approval processes can slow work down. Agentforce automates straightforward cases by validating data and flagging inconsistencies, reducing bottlenecks.
- Filtering Notifications: Agentforce reduces unnecessary alerts by prioritizing only what needs immediate attention. This helps teams stay focused without getting buried in noise.
Sam reflected: “We need to think about how we measure both efficiency and human impact…It’s about reducing the work that slows people down, those repetitive tasks that take energy away from more strategic efforts.”
How to Prioritize Your Agentforce Initiatives
One of the most valuable insights from the webinar was prioritizing Agentforce initiatives so businesses can focus on the areas with the most impact first. Sam and Sidd emphasized that adopting AI isn’t about deploying every capability all at once—it’s about starting where it will drive the most meaningful results based on your current needs and readiness.
Key Factors to Consider When Prioritizing:
- Identify Repetitive, Time-Consuming Tasks: Look for processes where manual effort slows productivity—like data summaries, approvals, or tier-one support cases. These tasks are often ideal starting points for Agentforce automation.
- Target High-Impact Areas: Prioritize initiatives where AI can directly improve efficiency or decision-making, such as reducing customer escalations or surfacing sales insights faster.
- Start with Embedded AI: Tools like Prompt Builder allow businesses to test and apply AI internally before expanding to customer-facing use cases.
- Evaluate Data Readiness: Clean, well-organized data is key for effective AI adoption. Start with areas where your data is already structured and reliable.
- Consider Scalability: Think beyond initial wins—how can AI help reduce friction across multiple departments over time?
Sidd shared: “You don’t need a fully defined AI strategy just to get started. You can focus on solving specific pain points and build out your strategy as you learn. Start small, see results, and expand when you’re confident.”
This structured approach allows businesses to build momentum while minimizing risk, ensuring that each AI initiative contributes measurable value.
Webinar Q&A: Key Takeaways
The live Q&A clarified some of the most pressing questions about Agentforce. Here’s what Sam and Sidd had to say:
How can small teams benefit from Agentforce?
Agentforce is designed to work at any scale. Tools like Prompt Builder allow small teams to automate repetitive tasks—like summarizing account data or generating reports—without requiring significant technical expertise or large-scale rollouts.
What does “a conversation” mean in pricing?
A conversation refers to a continuous interaction lasting up to 24 hours. Embedded AI features, like generating summaries, are priced separately based on prompt size and usage, providing flexibility for different business needs.
How do I structure workflows for complex tasks?
Topics should reflect discrete “jobs to be done,” such as order tracking or returns. Natural language instructions act as guardrails, while the Atlas Reasoning Engine handles dependencies to ensure seamless workflows.
Do I need Service Cloud to use Agentforce?
No. Agentforce is equally effective for organizations using Sales Cloud or Revenue Cloud, supporting use cases like lead qualification, pipeline analysis, and personalized recommendations.
What You Asked in the Chat: Unanswered Questions Follow-Up
Beyond the live Q&A, insightful questions came through in the chat. Here are the answers to what wasn’t covered during the session:
What happens when a customer query includes multiple tasks?
Agentforce’s reasoning engine breaks down multi-tasking queries into actionable steps, addressing each part in sequence or parallel, depending on how the tasks are connected.
Can users override pre-defined instructions, such as security protocols?
Agentforce is designed to operate safely and reliably. There are some capabilities for customers to add more safeguards (such as masking sensitive fields or providing more restrictive instructions), but the base Trust Layer and Reasoning Engine defend against prompt hacking.
How do I budget for usage if I’m new to consumption-based pricing?
Salesforce is developing tools to help estimate costs, but for now, starting small with embedded AI can help track usage patterns and identify where the most value is coming from before scaling.
Will sandbox testing support all environments, including partial and developer sandboxes?
Yes. Agentforce supports full, partial, and developer sandboxes so businesses can test and refine their solutions in a controlled environment before deploying them live.
Next Steps
The Demystifying Agentforce webinar made one thing clear: AI has the potential to reshape businesses using humans with AI to drive customer success together. To ensure a Return on AI (ROAI), companies must start with a clear strategy. If you missed the live session, the on-demand recording is available here.
For a deeper look at where Agentforce is headed, check out Coastal’s blog on Agentforce 2.0.
We’re also offering complimentary AI strategy workshops to help organizations:
- Identify high-value AI use cases.
- Assess readiness for adoption.
- Build a roadmap tailored to their goals.
