AI agents are evolving—fast. But how do companies keep pace, especially when scaling these systems across an enterprise feels more like rocket science than business strategy?
Enter Salesforce’s Agentic Maturity Model, a four-step framework designed to help organizations not only adopt AI agents but scale them effectively. Think of it as the self-driving roadmap—but for AI in the workplace. Just as autonomous vehicles move from cruise control to full autonomy, AI agents follow a similar path, growing from simple rule-followers into sophisticated, multi-tasking collaborators.
So, what’s the big challenge? While a whopping 84% of CIOs agree that having an AI strategy is now a competitive must-have, many admit they’re stuck when it comes to execution. Acknowledging the need for AI is the first step. It’s another thing entirely to implement it, measure success, and scale.
According to Shibani Ahuja, SVP of Enterprise IT Strategy at Salesforce, success starts with a "thoughtful, phased approach." In other words: slow down to speed up.
Here’s how the Agentic Maturity Model breaks it down:
🚦 The 4 Levels of AI Agent Maturity
🔹 Level 0: Fixed Rules and Repetitive Tasks
This is your standard chatbot—simple, rigid, and frankly, not really AI. These systems operate on predefined rules with zero learning or reasoning involved.
🔹 Level 1: Information Retrieval Agent
At this stage, agents assist humans by fetching data and suggesting actions. They're helpful, but still very much sidekicks—not decision-makers.
🔹 Level 2: Simple Orchestration
Now we’re talking autonomy. These agents can complete basic tasks on their own, though typically within siloed systems and without broader context.
🔹 Level 3: Complex Orchestration
Here, agents operate across harmonized data sets, managing multiple workflows independently. Think of them as AI project managers—intelligent, efficient, and cross-functional.
