Despite the improvements and enhancements made in recent times, AI is still unpredictable and unreliable.
Across the customer service and experience space, the technology is being used to answer questions, guide purchases, and increasingly handle conversations once reserved for human agents.
Yet a familiar problem keeps surfacing: these systems still behave unpredictably.
They can be fluent and insightful one moment, then miss something basic the next. And when that happens, the customer experience suffers.
Salesforce’s latest releases take direct aim at this reliability gap.
Across service, commerce, and AI research, the company is seemingly placing accuracy, consistency, and predictable behavior at the center of its AI system design.
And the CRM powerhouse isn’t tiptoeing around the issue.
This is evident with the launch of eVerse – the vendor’s new simulation environment built by its AI Research department to uncover failures before they ever reach a live customer.
In discussing the motivation behind eVerse, Salesforce pointed to what it refers to as “Jagged Intelligence”, instances where AI excels at complex tasks but struggles with simple ones.
The vendor believes that this phenomenon “creates unacceptable business risk” and that eVerse “directly addresses” the issue.
A Reliability Problem Hiding in Plain Sight
Through its Agentforce platform, vendors like Salesforce have been at the forefront of expanding the capabilities and usage of AI agents in the customer service and experience space.
These tools are moving beyond basic interactions to acting autonomously in key moments of the customer journey – highlighting just how prevalent AI now is within the sector.
As Kishan Chetan, EVP and GM of Salesforce Service Cloud, puts it:
“AI agents go beyond predictions and automation; they can understand context, take action, make decisions, and adapt in real time.”
Indeed, Salesforce’s 2025 State of Service report claims that 30% of service cases are currently handled by AI, with this percentage expected to rise to 50% by 2027.
Given the sometimes volatile nature of AI, this shift has the potential to drastically increase instances of unpredictability.
In an environment where one incorrect decision or confused response can alienate a customer and damage a brand’s reputation, there is plenty of risk accompanying the reward of further automation.
Salesforce appears to be attempting to combat the unreliability of AI so that the technology can become safer while its popularity continues to soar.
Breaking AI Before Customers Do
In a nutshell, eVerse is designed to break AI before customers do.
The training environment is unforgiving. It throws noise, accents, unpredictable behavior, and messy real-world scenarios at AI models to see how they cope.
Salesforce AI COO Madhav Thattai explained how Agentforce Voice was one of the eVerse guineapigs:
“With eVerse, we were able to explore many nuances of human conversation before Agentforce Voice reached production.”
“This type of rigor is what turns breakthrough research into scalable products and dependable customer experiences.
“It’s how we’re expanding that same level of responsiveness and consistency across the full observability stack to solve our customers’ most complex needs.”
UCSF Health is one of the companies currently involved in the pilot phase of eVerse.
Collaborating with clinical experts, the Salesforce team is training AI agents to handle healthcare billing, where precision is essential.
Early tests showed agents reaching up to 88% coverage across routine and complex tasks, with reinforcement learning and clinical oversight shaping the results.