Unlock the Power of Your Data with Agentforce

Across most enterprises, critical customer and operational data is fragmented across CRM systems, support platforms, finance tools, and unstructured sources like emails or collaboration tools. Retrieving relevant information quickly and effectively is virtually impossible, preventing teams from responding to customer needs in real time.

Agentforce by Salesforce is an integrated solution designed to build and deploy AI agents. These agents are not like typical chatbots; they use advanced reasoning abilities to understand inquiries and complete specific tasks like automating workflows, processing information, and making decisions with minimal human intervention.

Agentforce enables humans and AI agents to work together seamlessly, streamlining operations and improving customer interactions.

However, realizing the value of Agentforce requires a deliberate approach to how data is structured, governed, and activated across the organization. The good news: that work doesn’t have to be finished before you start.

Why Data Quality Determines Agentforce Success

AI agents do not independently validate, question, or correct the information they receive. They rely entirely on the data provided to generate responses, trigger workflows, and support decision-making. As a result, data quality becomes the single most important factor in determining whether Agentforce delivers value or introduces risk.

At its core, AI reflects the quality of its inputs. If the data feeding an AI system is:

• Accurate, then outputs are more reliable.
• Complete, then decisions are more context-aware.
• Consistent, then workflows operate as intended.

If it is not, the opposite is true. In an Agentforce environment, data quality issues rarely appear as obvious system failures. Instead, they surface as operational friction, such as:

• Incorrect or irrelevant responses to customer inquiries.
• Misrouted workflows due to inconsistent or missing data.
• Conflicting insights across teams using different systems.
• Erosion of trust in AI-driven recommendations.

Even advanced AI systems will produce unreliable or biased outputs when trained or operated on incomplete, inconsistent, or outdated data.

Putting a focused agent to work is often the fastest way to surface these issues. Data problems that hide in spreadsheets become visible — and fixable — once an agent is using that data every day.

Start with the Data You Already Have

A strong data foundation is the path to scale — but it isn’t the price of admission. Some of the most valuable early Agentforce use cases run on unstructured data your organization already has: knowledge articles, product documentation, policy PDFs, and resolved case histories.

Agentforce can ground its responses directly in that existing content, which makes focused use cases practical today:

• Case deflection: An agent that resolves common support questions from your knowledge base before they become tickets.
• FAQ and self-service agents: Grounded in your existing help content and available around the clock.
• Internal knowledge assistants: Help employees find answers buried in policies, SOPs, and documentation.

Because each agent is scoped to a defined set of vetted sources — and operates within Salesforce’s Einstein Trust Layer — you control exactly what it knows and does at launch. Start narrow, prove value, and widen the scope as your data foundation matures.

You don’t have to choose between starting now and getting your data right. A focused agent and a data foundation roadmap can run in parallel.

Building a Strong Data Foundation

Salesforce Data Cloud is the heart of Agentforce’s next-generation capabilities. To harness its full power as your agents scale, organizations should establish a robust data foundation — work that can begin alongside your first agents rather than before them.

This involves several key components:

Data Integration:

Integrating data from various sources ensures that your team has access to comprehensive and up-to-date information. This can be achieved through data lakes, APIs, e-commerce integrations, and more. By unifying their data, businesses can trigger AI-driven workflows and automations, maximizing efficiency and effectiveness.

Data Quality Management:

The success of AI initiatives relies on the accuracy, consistency, and reliability of data. Implementing data governance practices and regular data cleansing processes can help maintain high data quality.

Scalability:

As your organization grows, your data needs evolve. By choosing a scalable cloud solution, you can expand data capabilities without significant infrastructure changes. Salesforce's Data Cloud provides a tailored solution for Salesforce-specific environments, ensuring that your data infrastructure can grow with you.

Leveraging Agentforce for Enhanced Performance

As your data foundation matures, you can expand beyond those first focused agents to empower your team and optimize performance using Agentforce capabilities such as:

• Predictive Analytics: Historical data can be utilized to forecast future trends, allowing your team to make informed decisions and anticipate customer needs.
• Real-time Analytics: Providing your team with real-time insights enables them to respond quickly to customer inquiries and market changes. This keeps your organization agile and competitive.
• Performance Metrics: Implementing analytics tools to track performance can identify areas for improvement and help you build targeted training programs.
• Enhanced Collaboration: By centralizing data access, Agentforce empowers teams to share insights and collaborate on projects more effectively. Tools such as shared dashboards and collaborative platforms can enhance communication and streamline workflows.

At Eide Bailly, we understand the importance of empowering your team, improving customer service, and fostering innovation. Our data professionals can help you leverage Salesforce’s Data Cloud and Agentforce to streamline workflows and maximize your data — so your customers can receive the information they need, when they need it.

Not sure where to start? Our AI Readiness Assessment can show you where you stand today — and which use cases you could launch with the data you already have.