New Report: How Contact Center Leaders Are Preparing for Economic Uncertainty
Although the economy seems tenuous, 2023 looks bright for contact centers.
Since this report was published, the answer to that uncertainty has become clearer. Contact center leaders have moved from evaluating AI as a future initiative to deploying AI agents for contact centers as a core part of daily operations. Agentic AI contact center adoption now ranks among the most direct ways leaders are building resilience into staffing, cost structure, and customer experience. Where this report captured intentions for 2023, many of those intentions have since translated into live deployments of voice and chat AI agents handling real customer conversations.
Technology budgets, agent hiring, and overall optimism are heading in a promising direction, according to our new study, Building a Resilient Contact Center: How Leaders Are Preparing for Economic Uncertainty.
The demand from customers is not fading any time soon (92% of respondents expect call volumes to increase or stay the same), and businesses will need a skilled workforce to navigate those conversations to drive revenue and retention.
More so, leaders are realizing the content of customer conversations is an untapped treasure trove of information that could have major implications on how business decisions are made.

99% of contact center leaders are using conversation insights to inform business decisions—and not just for the contact center either. Leaders are using data from the customer conversations and applying those learnings to marketing, product development, operations, logistics, and more.
But it’s not so easy.
Only 37% are completely satisfied with their level of visibility into those conversations, which means leaders are making decisions based on insights they’re not completely satisfied with.
The right AI and automation tooling, like conversation intelligence, can help.
Our previous study found 96% of respondents said conversation intelligence improved contact center transparency. In addition, contact center leaders using conversation intelligence were 10X more likely to feel very prepared for the future than those who weren’t.
In this study, we see real-time AI emerge as one of the key use cases that’s top of mind for contact center executives.
It’s clear respondents view AI and automation as critical to unlocking the vast amounts of raw data that live within contact center customer conversations in order to make better business decisions.
Those able to do so will have the upper hand in 2023 and beyond.
AI Agents for Contact Centers: A Core Part of Economic-Uncertainty Planning
In the years since this report was published, AI agents for contact centers have moved from pilot programs to a standard line item in contact center budgets. Instead of choosing between headcount growth and cost control, leaders are deploying voice and chat AI agents to handle routine conversations at scale while human agents focus on complex, high-value interactions. This shift has also extended to operations: AI is now used to evaluate every customer interaction and generate coaching and insights for both human and AI agents, giving leaders a more complete view of performance during periods of economic pressure. As new uncertainty emerges, agentic AI contact center strategies have become one of the most direct levers leaders pull to protect service levels without proportionally increasing costs.

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Frequently Answered Questions
AI agents for contact centers let leaders manage rising conversation volume without matching increases in headcount, giving them a way to protect service levels and control costs during uncertain economic periods.
Agentic AI contact center agents, like Observe.AI's VoiceAI Agents and ChatAI Agents, can autonomously handle end-to-end customer conversations across voice and chat, resolving routine requests and escalating complex ones to human agents, who are in turn supported by Observe.AI's Companion Agent for real-time coaching and guidance.
No. AI agents for contact centers are designed to work alongside human agents, handling high-volume, repetitive conversations so human agents can focus on complex, high-value interactions that require judgment and empathy.

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