Why It's Time to Replace Your Legacy ITSM in 2026

What to Expect in This Session

• Why the risk of staying on legacy ITSM is greater than the risk of switching

• How Rezolve.ai's service catalog is built around process execution, not data collection

• Bot integration that collects intent, not just form fields

• Agent Assist features embedded directly in the ticket workflow

• Out-of-the-box and customizable analytics dashboards

INTRODUCTION

This session, presented at Rezolve.ai Connect 2026, was a candid examination of why legacy IT service management platforms are no longer fit for purpose — not because they lack features, but because they are built on the wrong assumption. Honey Arora, Director of Product Management, and Avanish Kumar, Customer Success Manager at Rezolve.ai, walked through the core architectural differences between legacy systems and Rezolve.ai, using live product demos to illustrate what intent-driven IT service looks like in practice.

If you're evaluating your current ITSM platform, or questioning whether your AI investments are delivering real value, this session is worth your time.

➜  Access all Rezolve Connect 2026 sessions on demand

The Real Risk Isn't Switching — It's Staying

Most conversations about legacy ITSM start with cost and feature gaps. This session started somewhere more important: the risk of inaction.

The market is moving fast with agentic AI, and many traditional platforms are still struggling to deliver basic AI outcomes that Rezolve.ai delivered years ago. The issue isn't just what legacy platforms can't do — it's what they're designed to do and whether that design still makes sense.

"The bigger issue isn't the feature gaps — it's the vision gaps. Most legacy platforms still see themselves as ticketing systems and cost centers, not efficiency engines. Buyers often perceive risk in switching platforms, but there is also a measurable risk in staying: ongoing licensing and services costs, complexity, tiered pricing, and low automation ceilings."  — Avanish Kumar, Customer Success Manager, Rezolve.ai

The webinar Evaluating the Shift from Legacy ITSM explores this in further depth — including a structured framework for assessing when staying has become the higher-risk option.

A Different Assumption at the Core

Every legacy ITSM is built on the same foundational premise: when an employee needs something, the next step is to open a ticket. Even with bots bolted on, the best outcome most platforms deliver is a faster, better-formatted ticket.

Rezolve.ai is built on a completely different assumption.

"The most important moment in IT service is not when a ticket is created. It's when a user expresses intent. When you get that moment right, you don't just manage work better — you start removing work altogether."  — Avanish Kumar, Customer Success Manager, Rezolve.ai

This shift — from ticket management to intent resolution — shapes everything: how the service catalog is structured, how the bot collects information, how agents triage their queue, and how performance is measured.  

To understand more about the broader trend driving this change, see: From Automation to AI-First ITSM: What Changed in 2025.

The Service Catalog: Process Engine, Not Form Library

WHAT IS IT?

In most platforms, a service catalog is a list of forms. In Rezolve.ai, it is a process definition layer. Every item in the catalog specifies the ticket type, workflow, actors, required fields, and any automations that should run when the item is triggered. The system is not optimized to collect data — it is optimized to execute a process.

HOW IT WORKS

The catalog supports all standard ticket types — incident, change management, task, request — and any custom type is a single clone away. Field configuration includes text, dropdown, and rich text options, with role-based visibility so sensitive fields are only surfaced to the right people. Validation rules — reject patterns, minimum and maximum lengths — are applied at the field level.

Layouts are independently configurable for agents and end users. SLAs — first response and full resolution — are defined per ticket type. Workflows are built visually, with state transition rules that enforce approval chains. Events and actions add a final layer: at ticket creation, the system can automatically notify the end user, route to the correct queue, and apply category and subcategory — without any manual intervention.

WHY IT MATTERS

"Legacy ITSM systems are designed around the idea that tickets are inevitable — so let's manage them better, route them faster, summarize them with AI. Our platform is designed around a different idea: tickets are not inevitable. They are a signal that automation isn't mature enough yet."  — Avanish Kumar, Customer Success Manager, Rezolve.ai

Instead of asking 'How do we manage tickets better?', Rezolve.ai asks 'How do we design processes and conversations so that fewer tickets are needed in the first place?' This is the architectural difference between optimization and transformation.

Related reading: AI-First ITSM: Help Desk Solutions Guide

Bot Integration: From Form Collector to Intent Engine

The service catalog and the conversational bot work together in a way that goes beyond standard implementations. Every catalog item is configured with trigger context and trigger phrases — signals the bot uses to match user intent to the right process. When a user types a request, the system evaluates which catalog item to surface and begins a structured conversation to gather the necessary information.

Bot input configuration gives teams three modes for each field:

• Ask leading questions — the bot proactively prompts the user for the field value

• Fetch from conversation — the bot extracts information the user has already mentioned, without asking again

• Hide from bot user — the field is populated in the background, invisible to the end user

Field-level descriptions provide additional context so the bot asks more relevant follow-up questions. The result is a bot that doesn't open a ticket — it understands what the employee is trying to accomplish and works toward resolving it.

Learn more about how AI agents work in this context: What Are AI Agents? A Complete Guide

Agent Assist: AI Embedded Where Agents Already Work

Most AI features in legacy ITSM live in separate chat interfaces. Agents have to leave their workflow, frame the right question, interpret the answer, and bring the insight back manually. Rezolve.ai takes a different approach: AI utilities are embedded directly in the ticketing interface.

Smart Summary and Sentiment Analysis

Without opening a ticket, agents can access a smart summary and real-time sentiment analysis from the inbox view. For high-volume teams, this is significant — an agent understands the user's emotional state and grasps the full context of an issue in seconds, not after reading through an entire thread. For tickets that have been paused or handed off, smart summaries eliminate the cognitive overhead of re-orienting.

Response Autocomplete

When an agent begins drafting a reply, autocomplete takes the intent they've started to express and generates a complete, professional response. The agent writes the direction; the AI writes the message. This saves composition time while preserving agent judgment on what to communicate.

Knowledge Article Autocomplete

A knowledge analyst provides a title and a brief description, specifies purpose, outline structure, and citation preferences, and the system generates a fully structured article ready for review. A richer, more current knowledge base means the bot can resolve more queries without escalation — which means fewer tickets overall.

See how this connects to broader Level 1 deflection strategy: The Future of Level-1 IT Support with Agentic AI

Dashboards and Analytics: Built for How IT Teams Actually Report

Rezolve.ai provides two types of dashboards: out-of-the-box and fully customizable — acknowledging that reporting needs vary significantly across organizations.

Out-of-the-Box Dashboards

The conversation dashboard provides an immediate view of bot performance: total conversations, query accuracy, user feedback (thumbs up/down), CSAT scores, completion versus abandonment rates, and knowledge base utilization. Metrics toggle between percentage and absolute values. Sentiment breakdowns are available per category.

Explainability views show why the bot answered a specific query the way it did — which knowledge results were used, what feedback influenced the response. This closes the loop between bot behavior and knowledge quality, and gives teams the evidence needed to improve both.

Customizable Dashboards

The customizable dashboard layer lets teams build any view they need: any chart type, any filter combination. Cross-filtering is particularly useful — a manager can surface high-priority in-progress tickets assigned to a specific agent in a few clicks, without writing a report.

Replacing a Mindset, Not Just a Tool

For years, ITSM improvement meant optimizing the ticket queue: route faster, resolve faster, summarize with AI. In the agentic AI era, that is no longer a sufficient ambition.

"Employees don't want better tickets. They want faster outcomes. Legacy ITSM manages tickets. Rezolve.ai is designed to reduce or eliminate them through automation and intent-driven workflows. The choice isn't just about replacing a tool — it's about replacing a mindset."  — Honey Arora, Director of Product Management, Rezolve.ai

The organizations already making this shift are seeing the results. Those still optimizing their ticket queues are falling further behind.

See Rezolve.ai's AI-native ITSM platform in action  →

Frequently Asked Questions

What is the biggest risk of staying on a legacy ITSM platform?

Beyond ongoing licensing costs and tiered pricing complexity, the primary risk is a vision gap. Legacy platforms are designed around ticket management as an end goal. As agentic AI accelerates, organizations on legacy systems will find it increasingly difficult to achieve the automation outcomes their employees and leadership expect.

How is Rezolve.ai's service catalog different from a traditional one?

A traditional service catalog is a form library — it collects data. Rezolve.ai's service catalog is a process definition layer — it executes business processes. Every item defines the workflow, actors, required data, and automations that should run, meaning the system drives outcomes, not just intake.

Can Agent Assist features work with existing ticket workflows?

Yes. Agent Assist features are embedded directly in the Rezolve.ai ticketing interface. Smart summaries, sentiment analysis, response autocomplete, and knowledge article generation are all available within the ticket view — agents do not need to switch to a separate AI interface.

What does 'intent-driven' ITSM mean in practice?

It means the platform captures what an employee is trying to accomplish before deciding what process to run. Rather than defaulting to ticket creation, the system evaluates whether the intent can be resolved through automation, self-service, or conversation — and only creates a ticket when necessary.

Where can I learn more or see a live demo?

Watch the session recording: YouTube — Why It's Time to Replace Your Legacy ITSM  |  Access all sessions: Rezolve Connect 2026 On Demand