In the world of Salesforce, the buzz around Agentforce is undeniable. Teams are eager to leverage its capabilities to streamline processes, enhance customer experiences, and drive innovation. But in the rush to adopt and scale Agentforce, one critical factor can determine success or failure: your data. With data volumes growing, compliance requirements evolving, and the increasing reliance on AI insights, having reliable, resilient data is as important as ever.
In this article, we’ll explore the top data risks that can derail your Agentforce momentum and provide steps on how to start building a modern data resilience strategy. By addressing these challenges head-on, you’ll be better equipped to protect your data and unlock its full potential to ensure continuous innovation.
Top Data Risks That Can Stall Agentforce Momentum
Risk #1: Innovation Stalls Due to Data Loss or Corruption
Imagine you’re on the brink of launching your first Agent in Salesforce, but a rogue integration or human error wipes out critical data. These disruptions aren’t just setbacks; they can grind your innovation to a halt and erode trust in your Agentforce outputs. Inaccurate or corrupted data leads to suboptimal results and unexpected behaviors, undermining the very purpose of your AI initiatives.
🔎 Own customers undertook 18,800 data restoration jobs—an average of over 1,500 a month—in 2023.
Risk #2: Performance Degradation from Data Bloat
Salesforce is meant to be your team’s trusted hub for managing customer data and driving business decisions. However, as your organization grows, data can accumulate, leading to a cluttered environment. This data bloat not only consumes storage but also slows down system performance, making everyday tasks more cumbersome. Over time, this can erode user trust, create inefficiencies in reporting and workflows, and hurt your team’s ability to innovate and respond to new opportunities.
🔎 78% of analytics and IT leaders struggle to drive business priorities because of data volume and quality issues.
Risk #3: Missed Opportunities from Unready Data
AI systems like Agentforce depend on identifying patterns and trends to deliver meaningful insights. However, this data is often scattered across platforms, locked in backup systems, or siloed within different departments. Extracting and consolidating this data can be a slow, labor-intensive process, and by the time it’s ready, it may no longer be relevant. This delay hinders AI’s ability to provide accurate, up-to-date insights and limits your team’s ability to act quickly and confidently on emerging trends.
🔎 41% of businesses say they face challenges accessing the data they need when they need it.
Risk #4: Increased Exposure to Security and Compliance Risks
The more data you handle, the greater the responsibility to manage it effectively. Regulatory requirements are constantly evolving, and cyber threats are becoming more sophisticated, putting sensitive data at higher risk. Without a proactive strategy to monitor, secure, and protect your data, your organization faces serious consequences, including costly non-compliance fines, data breaches, and disruptions that can stall innovation and growth.
🔎 IT leaders rank security threats as their #1 challenge.
Risk #5: Inability to Scale AI and Advanced Analytics
The success of AI initiatives, including Agentforce, depends on accurate, unified data. However, many organizations struggle with fragmented, inconsistent, or outdated datasets spread across multiple systems. These issues create barriers to effective analysis, leading to skewed insights and unreliable predictions. Without a clear, integrated view of your data, it’s challenging to build trust in Agentforce outcomes, slowing adoption and hindering your ability to leverage its full potential.
🔎 54% of AI users say they don’t trust the data used to train their systems.
How to Build a Resilient Data Strategy for Agentforce
Building a resilient data strategy starts with the three R's of modern data resilience: Reliability, Relevance, and Readiness. Here’s how to implement them:
Step #1: Assess Your Current Org Data Resilience
Begin by evaluating your Salesforce environment to identify gaps in your data protection, management, and recovery processes.
Step #2: Implement Full-Org Protection with Automated Backups and Establish a Rapid Recovery Strategy
Implement regular automated backups to ensure your data is always recoverable. Pair this with a rapid recovery plan to minimize downtime and disruption.
Step #3: Optimize Performance with Intelligent Archiving
Use automated archiving tools to declutter your Salesforce org, improve system performance, and reduce storage costs while retaining access to critical historical data.
Step #4: Activate Backup Data for Advanced Analytics
Leverage historical backup data to fuel AI-driven insights and build time-series models, enhancing predictive accuracy.
Step #5: Establish a Culture of Data Governance and Monitoring
Foster a culture of data governance and monitoring by implementing policies and tools to ensure your data remains secure, compliant, and accessible. Regular monitoring is crucial to mitigate risks.
Ready to Future-Proof Your Agentforce Data?
Data resilience isn’t just a nice-to-have; it’s essential for staying ahead. By addressing the risks outlined and implementing a robust data strategy, you’ll set your organization up for success with Agentforce.
Download the Salesforce Data Resilience Playbook to dive deeper into these steps and start building a data strategy that stands the test of time.
