What is a Virtual Agent?
On questioning what is a virtual agent, the answer is complex, as follows. Before answering, consider that Virtual Agents (VA) are transforming how organizations interact with customers. These AI-powered assistants are more than just automated responders. Rather, they can interpret and respond with context, emotions, and intelligence. By simulating human-like interactions, Virtual Agents offer real-time, personalized support across platforms like chat, voice, and email. As businesses strive to enhance customer engagement, Virtual Agents are leading the way with advanced AI capabilities.
Notably, 97% of mobile users are now using AI-powered voice assistants (source: Tech Jury), highlighting the growing reliance on these tools. By 2025, Gartner estimates that “50% of knowledge workers are expected to use virtual assistants” (source: https://www.gartner.com/en/newsroom/press-releases/2019-01-09-gartner-predicts-25-percent-of-digital-workers-will-u), emphasizing the accelerating shift towards AI-driven customer engagement.
Exactly What is a Virtual Agent?
A Virtual Agent is an AI-driven tool that manages customer interactions in real-time. Unlike basic chatbots that follow pre-set scripts, Virtual Agents use AI to understand language naturally. This allows them to provide information, solve issues, and handle complex inquiries independently. They continuously learn from each interaction. This means they get better at answering questions over time. Best of all, when applied well, intelligent virtual agents can help to offload busy call centres, support hubs, and human centric information sources.
Key Technologies Behind Virtual Agents
Virtual Agents combine several advanced AI technologies to create dynamic customer experiences:
Natural Language Understanding (NLU)
NLU lets Virtual Agents interpret and respond by understanding the user’s intent. Unlike traditional Natural Language Processing (NLP), NLU goes further by grasping the meaning behind words, allowing VAs to answer with relevance and precision.
Machine Learning (ML)
Machine Learning allows Virtual Agents to learn from interactions, adapting to new queries as they occur. This continuous improvement means responses get more accurate and helpful over time, personalizing the experience for each user while boosting overall satisfaction.
Large Language Models (LLMs)
LLMs, like ChatGPT, Gemini, Co-Pilot, Claude, and others, support VAs in generating contextually appropriate responses. However, they often produce inaccuracies, called “hallucinations.” LLMs are also susceptible to data poisoning, biased answers, and can respond in culturally insensitive, or even offensively to certain communities. To combat this, many organizations incorporate RAG (retrieval augmented generation) techniques, and Knowledge Graph-based AI to ensure reliability and trustworthiness.
Knowledge Graph-based AI (Graph AI)
Kama.ai’s Virtual Agents use Knowledge Graph-based AI technology, which provides a structured, reliable, and ethically guided approach to responses. Unlike LLMs that generate responses from massive datasets, Graph AI retrieves specific, verified information, eliminating the risk of misinformation to ensure accurate answers every time.
Benefits of a Knowledge Graph-Based Virtual Agent
Virtual Agents built on Knowledge Graph-based AI offer unique advantages:
- Enhanced Accuracy: By using verified information, Virtual Agents deliver reliable responses that customers can trust.
- Reduced Bias: Knowledge Graphs are transparent, which minimizes biases often found in other AI models.
- Responsible AI Practices: Kama.ai’s approach ensures that responses align with organizational values, promoting ethical AI interactions.
Applications of Virtual Agents Across Industries
Virtual Agents are widely used across industries, improving customer engagement in various ways. As few examples include:
- Customer Service: Virtual Agents answer routine questions, freeing human agents to tackle complex issues. Kama.ai’s Responsible Conversational AI ensures these interactions are both effective and ethical.
- Healthcare: In healthcare, Virtual Agents provide real-time access to information, supporting patients with reliable guidance that respects privacy and confidentiality.
- Education: Virtual Agents act as on-demand tutors, offering students personalized help. Often, student questions can be as simple as clarifications on a course curriculum, class times for particular courses, and even as mundane as the bus schedule to help get to class on time. Kama.ai’s AI ensures that the guidance provided is accurate and contextually relevant.
Challenges and Ethical Considerations
As Virtual Agents become more sophisticated, ethical considerations like privacy, bias, and accuracy come into play. Kama.ai addresses these challenges by implementing Responsible AI practices, including human oversight and governance. If a query becomes too complex, Virtual Agents can pass it to a human agent for a seamless transition.
Conclusion
We return to the question of what is a Virtual Agent? After all, VAs are transforming customer engagement, while providing organizations with tools that combine intelligence and empathy. By using advanced technologies like NLU, ML, LLMs, and Knowledge Graph-based AI, kama.ai delivers Virtual Agents that meet modern needs with ethical and reliable AI solutions. As organizations look to meet ever-evolving customer expectations, adopting Intelligent Virtual Agents offers a powerful, scalable solution for customer engagement.
In a digital-first world, Virtual Agents provide an opportunity for businesses to connect authentically, ensuring that AI-driven interactions are responsible, trustworthy, and impactful. Ready to explore the possibilities? Let’s connect for a quick discussion of your options.