AI adoption in the contact center continues to accelerate. Many organizations feel pressure to deploy AI quickly while also worrying about readiness, quality control, and operational risk. The framing of Agent Assist versus Virtual Agents often makes the decision harder. Jon Quayle, Product Evangelist at Deepdesk, believes the most successful organizations move past this binary choice. They treat AI as a capability that develops in stages and evolves with operational needs.
Leaders do not need to take sides in the debate on Agent Assist versus Virtual Agents. The most effective CX strategies use both, and the balance shifts as the organization matures
A clear roadmap helps leaders understand where AI supports people today and where automation can take on more responsibility later.
Business Issues and Human Impact
Contact centers face ongoing pressure to deliver more with limited resources. Cost control, speed, and quality improvement remain core priorities. Jon notes that many CX leaders also feel a strong fear of missing out. They believe competitors are already succeeding with AI and worry about losing ground if they delay. Jon understands,
Every organization is being asked to do more with less, and that pressure creates both fear of missing out and fear of jumping in.
This tension often appears before internal strategy is fully defined. Some leaders feel pushed toward AI by senior teams or vendors, without clarity on where automation makes sense. This is where the Agent Assist versus Virtual Agents dilemma becomes visible.
The turning point usually comes when leaders realize they can start small. Agent Assist gives them a controlled entry point. Jon believes,
When leaders see they can adopt AI without risk and keep humans in control, that is when the movement starts.
Human agents work exactly as before but gain real-time support that reduces cognitive load and improves consistency. Once organizations see that AI can add value without replacing the agent, the roadmap becomes easier to define.
Transition to Technology
The first step in any AI roadmap is understanding the work happening inside the contact center. Jon encourages leaders to identify repetitive tasks, high-friction steps, and excessive context switching that consume frontline attention.
Here, the balance of Agent Assist versus Virtual Agents becomes actionable. AI that augments agents rather than replacing them is a logical starting point. Leaders can observe AI behavior in real conversations and collect evidence for future automation, from Jon’s perspective,
Agent Assist is a low-risk proving ground. If agents rate the prompts highly every day, you can automate with confidence later.
Deepdesk treats Agent Assist as the foundation for autonomous workflows. When organizations see consistent value from AI-supported conversations, the leap to virtual agents becomes a structured and data-driven progression.
Technology, Products, and Solutions
Jon emphasizes that AI maturity is not linear. Agent Assist and Virtual Agents are complementary and work best when deployed together.
- Agent Assist delivers early value through faster handling times, better focus, and stronger CSAT.
- Virtual Agents take on targeted workloads later once the organization has tested the logic, context, and workflows through Agent Assist.
One critical element is contextual continuity. Customers expect a smooth transition when moving between automated and human support. Deepdesk maintains this through consistent AI-generated summaries and guidance, Jon highlights
The same AI that supports a virtual agent can support a human agent seconds later. Context moves with the conversation.
This minimizes friction and avoids customers repeating themselves.
Market Trends and Forward Look
Jon believes organizations can adopt Agent Assist and Virtual Agents responsibly by understanding their risk tolerance and where human value matters most. Automation should not be framed simply as cost reduction. The biggest gains often come when humans are freed from routine tasks and can focus on complex or emotionally sensitive interactions.
A commercial trend is also shaping expectations. Some organizations invest in virtual agents with ambitious targets for automated call volume. When those expectations fall short, ROI can suffer. Jon believes Agent Assist avoids this risk because it enhances every conversation, not just automated flows.
No one goes out looking for Agent Assist, but it is often what delivers the most reliable return because it applies across the whole conversation.
Jon also sees a pattern of vendor fatigue.
Many teams have tried virtual agents and been overpromised. We often come in after a failed POC because organizations want balance, not big claims.
A roadmap built around staged adoption meets that need.
Conclusion
The Agent Assist versus Virtual Agents debate is changing. Organizations no longer need to choose one path. They need a sequence.
Agent Assist provides a low-risk foundation that strengthens human performance. Virtual Agents extend automation once the organization has evidence, governance, and confidence. A structured roadmap helps CX leaders adopt AI at a pace that protects quality, improves efficiency, and preserves the human experience.
