Utilizing Agent Co-Pilot to Improve Agent Productivity
Organizations looking to improve IT service desk efficiency while still maintaining costs can utilize Barista Agent Co-Pilot: a suite of capabilities from Espressive focused specifically on improving agent efficiency. These capabilities add AI assistance to the phases of ticket handling where MTTR is most often increased, including new knowledge generation, ticket field population, language translation, and more.
Faster Ticket Resolution, Same Agent Workspace
Agent Co-Pilot doesn’t require agents to learn or load a separate UI. Instead, Agent Co-Pilot can be deployed into any existing call center system, such as CXone, AWS Connect, Genesys, or even ServiceNow’s Agent Workspace. In addition, Agent Co-Pilot works in conjunction with Espressive Barista, our GenAI-based virtual agent, but can also be deployed separately.
Agent Co-Pilot positively impacts key service desk metrics.
MTTR
Drives down mean time to resolution (MTTR)
FCR
Increases first call resolution (FCR)
Escalation
Reduces the need to escalate routine employee service requests
Ramp Time
Shortens the ramp time for new service desk agents
Key Features of Agent Co-Pilot
New Ticket Enrichment
It’s time consuming for agents to determine ticket attributes (e.g., Category, Assignment, Priority, etc.) as well as find other relevant knowledge or similar tickets to help solve the issue at hand. New Ticket Enrichment leverages AI to accurately predict the values of any ticket field and fetch any relevant knowledge or solution from other similar tickets.
Barista Live Translation
With Barista Live Translation, even if agents are not familiar with the languages employees are communicating in, they can immediately engage Barista to begin live translation to assist employees. Barista Live Translation provides a bi-directional communication layer using the best in translation technologies.
Direct Access to Barista
With Agent Co-Pilot, agents can get direct access to Barista by simply adding “@Barista” from inside a ticket or chat, utilizing Barista automations or other specific data they need to resolve employee issues. Barista will also automatically fetch the needed context and user info from the ticket and CMDB to carry out these instructions.
Automatic Knowledge Generation
Automatic Knowledge Generation leverages AI to observe agent and employee interactions and generate new knowledge articles once tickets are resolved. Having quality KB articles helps resolve tickets faster, since remediation steps are documented and can now be retrieved when similar problems happen in the future. Intelligent article creation also means that the AI pipeline verifies that ticket content contains valuable information, and that knowledge is not redundant with other articles.
