Here’s what you might not know about starting your first AI project in Salesforce.
1. Key Industry Trend
– AI’s growing influence is transforming business operations.
– Salesforce’s Agentforce, unveiled at Dreamforce ’24, is a game-changer for productivity.
2. Data Governance Insight
– Data governance is foundational to AI success.
– Ensure data is clean and structured to prevent skewed AI outcomes.
3. Challenges and Implications
– Incomplete or messy data can undermine AI efforts.
– AI governance defines how and where AI should be applied effectively.
4. Execution Steps for a Successful Start
– Identify all relevant stakeholders and clarify roles.
– Define an AI governance structure for evaluating and selecting use cases.
– Conduct a thorough risk assessment and prepare communication plans.
– Begin with manageable, lower-risk projects to test AI governance.
Salesforce technical debt can impede growth if left unchecked. Incomplete or outdated data, lack of documentation, and unoptimized processes can slow down AI initiatives, reducing ROI and business agility. Engaging with a Salesforce architect helps managers address this debt, aligning technology with strategic goals to support sustainable growth.
Begin your AI journey by focusing on data quality improvements as your first project. This approach not only enhances data integrity but also provides a practical way to refine AI processes and governance.
You can read it here: https://sfdc.blog/tvAwz
Source from admin(dot)salesforce(dot)com