Cracking the code for evolving AI with faster and better agent rollouts that meet the demands of businesses today.
For organizations in Asia Pacific, artificial intelligence (AI) is fast evolving from the consumer-ish kind of generative AI to take on more serious business tasks.
Progressing from passive assistance to active co-piloting, many now see agentic AI as the next evolution of enterprise AI.
But with the proliferation of tools and strategies to roll out AI agents today, how can an organization stay ahead? To crack the code for faster AI agent rollouts, we sought out some insights and perspectives from Simon Ma, Managing Director, Asia, Freshworks.
How is agentic AI shaping the evolution of enterprise service software compared to earlier generative AI models?
Ma: Agentic AI marks a significant step forward from earlier forms of generative AI. While previous models focused on generating responses or content based on prompts, agentic AI introduces autonomy. This means allowing AI agents to act with intent, make decisions, learn from outcomes, and complete tasks across enterprise workflows. This represents a shift from passive assistance to active co-piloting.
At Freshworks, we see this evolution as a natural response to the complexity of modern business needs. Traditional generative AI offered value in content generation and summarisation, but it often required manual orchestration and oversight. Agentic AI, on the other hand, operates more like a trusted teammate, it’s goal-oriented, aware of context, and capable of driving outcomes without constant human intervention.
This change also redefines the architecture of service software. With AI agents embedded across helpdesk, IT, and CRM tools, businesses can design systems where tasks such as triaging tickets, pulling data, or triggering workflows are handled autonomously. It’s not just about speed, but about simplifying enterprise capability without adding enterprise complexity, allowing humans to focus on strategic, creative work.
In what ways does AI help businesses of all sizes achieve faster, easier automation without complex setup?
Ma: AI today has matured to the point where businesses no longer need complex infrastructure or long deployment cycles to benefit from automation. The shift is toward making automation intuitive and context-aware, where systems can understand intent, act independently, and deliver value quickly without relying on technical teams to build or maintain elaborate workflows.
This is especially important for small and mid-sized businesses, where resources are limited but the need for efficiency is just as urgent. The goal is not more features but fewer unnecessary ones—automation that works out of the box and adapts quickly to real-world use. AI today helps teams reduce busywork and accelerate service without testing their patience or requiring weeks of onboarding.
We build on this by offering AI that is pre-integrated and designed for rapid impact. Features like intelligent ticketing, auto-summarisation, and proactive response suggestions require minimal setup and training. The AI works quietly in the background, drawing from unified data and understanding context across service, sales, and IT functions.
The result is that businesses of all sizes can access enterprise-grade automation without the traditional barriers. Automation becomes something teams can use immediately, not a project they need to plan for. This is what unlocks real scale—when AI becomes an invisible yet powerful part of the everyday workflow.
How do you ensure that its AI supplements rather than replaces human agents, keeping the customer service experience people-first?
Ma: We believe that AI should enhance human potential, not sideline it. This principle shapes how we design every Freddy AI experience. Our goal is to give employees superpowers, not substitutes.
Agentic AI should be built to act as a collaborative teammate. It proactively assists agents by surfacing relevant information, summarising past interactions, and even suggesting the next best action. But the human agent remains in control, deciding when to accept, edit, or override suggestions. This keeps empathy, judgment, and nuance at the center of service delivery.
Importantly, we’ve designed Freddy’s agentic tools to be transparent and explainable. That’s critical for trust. When the AI acts, whether it’s resolving a ticket or automating a process, it’s clear why and how that action was taken.
By reducing the busy work, AI allows agents to spend more time building customer relationships. This aligns with our people-first philosophy: the best customer experiences happen when humans and AI work side by side, each doing what they do best.
What are some examples of real-world impact where Freddy AI Agents have driven measurable improvements in resolution time or customer satisfaction?
Ma: We’ve seen strong real-world outcomes from customers deploying Freddy AI Agents across industries. For instance, a global technology services firm reduced ticket resolution time by 50% after automating triage and classification with Freddy. AI agents could instantly route tickets to the right department based on intent and urgency, something that previously required manual intervention.
In e-commerce, a Freshworks customer used Freddy Self-Service to deflect over 60% of routine customer queries, such as order tracking and refund policies. This not only reduced support load but also boosted CSAT scores due to faster response times.
Even in regulated industries like healthcare, where accuracy is critical, AI agents have helped surface relevant policy documents and case summaries within seconds. This enables support staff to provide timely and informed responses.
These outcomes reinforce that AI isn’t just about reducing costs but about creating value. Measurable gains in speed, satisfaction, and consistency are possible when AI is integrated with business context and deployed thoughtfully.
