Solving Customer Support’s biggest problems with AI Agents
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With the rapid pace of AI adoption in businesses today, its use in customer support has become a critical differentiator. About 80% of business leaders prioritize customer support as a key factor for success. However, organizations find themselves grappling with complex challenges in their pursuit of delivering exceptional customer experiences. The customer support conundrum requires a paradigm shift to navigate the challenges of the modern business landscape and reimagine the way businesses serve their customers.
Self-service in customer support has traditionally been known to compromise customer experience because self-service portals, search functionality, and chatbots were frequently ineffective and failed to provide the seamless, personalized support that customers demand.
Human agents are overwhelmed with repetitive tasks, hindering their ability to engage in deep work on issues that require their undivided focus. Even disgruntled users are frustrated by the inherent repetitiveness in finding a solution or getting an issue resolved.
As product teams strive to innovate more iteratively using the large volume of information hidden in customer tickets and app reviews, and as engineering teams struggle to stay ahead of incidents, the need for modern, AI-driven solutions has become paramount.
{AI} Agents of change are here
AI Agents, working alongside human agents, is the answer to the problems that hinder organizations from efficiently delivering exceptional customer experiences. AI agents function like employees with specific skill sets. They leverage knowledge about an organization’s products, customers, and people to autonomously complete tasks and save humans time. Organizations can create multiple agents, similar to a team, to tackle complex tasks by breaking them down into smaller components.This allows human agents to engage in deep work and spend more time focused on solving complex issues.
AI agents are goal-oriented, integrating skills and functions to achieve specific outcomes. These agents can be categorized into three types based on their objectives: Autonomous Agents that perform operations eliminating the need for human intervention, Augmented Agents that act as co-pilots for employees, and Analyst Agents that surface actionable business insights from enterprise data.
Autonomous Agents
Autonomous Agents can independently handle customer support queries without human intervention. These agents can instantly resolve up to 60% of user queries on their own, primarily using Semantic Search and AI-powered Deflection. By integrating Semantic Search across channels such as in-app chat, Help Centers, and support portals, users are equipped to seek information instantly on their own. The solution to an issue a user is facing is only a few keystrokes away, as Autonomous Agents can understand natural language inputs and retrieve relevant information from knowledge articles.
What differentiates AI Agents from even the most effective chatbots is that agents are empowered to resolve customer queries without involving a human agent. Autonomous AI Agents are more than just simple chatbots as they have the capability to entirely automate Level 1-2 Support. These self-learning agents can go beyond simple information retrieval and leverage APIs to actually perform actions and transactions on the backend to fully resolve certain issues.
Augmented Agents
Augmented Agents, serving as AI copilots, work alongside human agents to enhance their capabilities and streamline workflows. These agents gather deeper insights by leveraging real-time Session Recordings of user sessions, enabling organizations to identify friction points, detect patterns, and proactively address issues to create frictionless experiences. As co-pilots to Customer Support teams, they provide real-time recommendations, including Similar Tickets & Articles suggestions, enabling human agents to resolve issues faster and more efficiently.
AI Agents empower support teams to unlock valuable insights hidden within vast amounts of customer tickets and app store reviews. By intelligently clustering dormant data, these agents help support teams identify common issues and recurring customer pain points. With AI-powered Smart Cluster at their fingertips, support teams can proactively address concerns, improve self-service resources, and optimize support workflows. AI Agents augment human expertise, enabling support teams to focus on delivering exceptional customer experiences.
Analyst Agents
Analyst Agents specialize in data analysis, deriving actionable business insights from vast amounts of information. These AI-powered agents can monitor sentiment in customer conversations, proactively alert teams about potential SLA breaches, and provide valuable insights with just a simple natural language prompt. By integrating data from an organization's existing tech stack, Analyst Agents offer a comprehensive Customer360, enabling businesses to make informed decisions and generate reports in seconds using natural language queries. With Analyst Agents, organizations can harness the power of AI to unlock valuable insights, optimize operations, and drive customer satisfaction to new heights.
The future of work
The future of work is undeniably agentic, with AI Agents becoming increasingly ubiquitous in modern organizations to enhance productivity and efficiency. AI Agents will be the key to unlocking new opportunities for innovation, growth, and customer delight as they automate the mundane, augment human capabilities, and analyze dense information, enabling businesses to deliver exceptional customer experiences. Powered by a platform that unifies data and information around products and customers, AI Agents will be the catalysts for reimagining how modern organizations support their customers, build products, and grow their revenue. We call this platform AgentOS. Learn more about it today!
