From Chat to Action: AI Agents Enter the Enterprise Workflow Stack
A new generation of AI agents enterprise platforms is moving beyond simple chatbots to execute concrete tasks across content, customer experience, and IT service management. Vendors including Laserfiche, Level AI, Freshworks, Ivanti, and ServiceNow are embedding natural language AI into their workflow automation platforms so employees can trigger complex processes by describing outcomes, not configuring rules. These agents sit on top of existing systems, follow governance and security controls, and are designed to own specific roles—from service desk analyst to contact center coach. The goal is to close the long‑standing gap between insight and action: instead of humans reading reports and manually updating systems, agents increasingly orchestrate the work. Yet this shift also exposes a readiness divide. Most enterprises still run ticket‑centric, human‑led processes and fragmented tooling, which can limit the impact of even the most advanced customer service AI or ITSM automation tools.
Laserfiche Uses Natural Language AI to Compress Workflow Design
Laserfiche is bringing AI agents directly into content management, allowing business users to assign tasks with plain language instead of building intricate workflows. Accessible via the Smart Chat interface, these agents inherit each user’s permissions, operating within existing security and compliance rules so that sensitive information remains protected. Backed by generative reasoning models, they handle the “middle ground” between manual steps and fully designed automations, analyzing document data and executing changes based on natural language instructions. In legal, the system can flag inconsistencies in contracts before routing them to humans; in Accounts Payable, it can surface late invoices and send them to the right teams; in HR, it can scan employee records and file documents into appropriate digital folders. By pairing content analysis with role‑aware automation, Laserfiche lowers the skills barrier to workflow automation platforms for non‑technical staff.
Level AI’s Specialized AI Workers Target the Back Office of Customer Experience
Level AI is attacking a different bottleneck: the operational teams behind customer interactions. Its new AI Workers are purpose‑built agents scoped to specific roles such as coaches, analysts, QA leaders, and CX executives. Instead of generic summarization, each Worker is responsible for a defined job and deliverable, powered by the same customer intelligence data that existing quality and analytics teams rely on. Early deployments span nearly 100 enterprise contact centers, with more than 25,000 Worker runs reported and daily use at brands like Smartsheet, VistaPrint, and Ollie Pets. Level AI argues that most customer service AI to date has focused on front‑office automation—voice bots, chat deflection, IVR—while the workflows that connect insights to coaching plans, quality improvement, or product fixes remain largely manual. AI Workers aim to fill that gap by automating research, analysis, and planning work that consumes the majority of time in customer‑centric operations.
Freshworks’ Freddy AI Agent Studio Brings No‑Code Autonomy to ServiceOps
Freshworks is extending its ServiceOps platform with Freddy AI Agent Studio, a no‑code environment for building and governing service‑oriented AI agents at enterprise scale. Positioned as a way to connect service, assets, and incidents on one agile platform, Freddy lets organizations deploy pre‑built, domain‑specific agents or design bespoke ones in weeks rather than quarters. Telemetry from millions of service interactions revealed a growing support gap: nearly half of IT tickets now arrive outside standard business hours, yet after‑hours response times lag significantly and SLA performance drops. Freddy agents are intended to operate as always‑on service staff, meeting employees where they already work—in Microsoft Teams, Slack, or employee portals—while connecting to systems like Workday and Rippling to execute secure workflows from onboarding to payroll. By embedding natural language AI into routine service requests, Freshworks aims to reclaim time, reduce “ghost shift” frustration, and standardize service delivery.
Agentic ITSM Tools Are Shipping Faster Than Enterprises Can Adapt
In IT service management, Ivanti and ServiceNow are already delivering agentic tools that can autonomously handle incidents and requests, but most organizations are not structurally ready. Ivanti’s autonomous service desk agent, launched in April, can create incidents, submit requests, and search knowledge bases without analyst intervention, helping teams shift away from repetitive ticket handling toward higher‑value initiatives. Research cited by McKinsey shows how powerful this can be: one multinational automated up to 80% of roughly 450,000 annual tickets and redeployed half its service team—but only after redesigning workflows and customer journeys around agent‑led resolution. Many enterprises still run infrastructure optimised for ticket‑based, human‑centric processes, a “plumbing problem” that prevents agents from reliably traversing systems and APIs under strong governance. As Red Hat leadership has noted, organizations are back in a “basics” phase, shoring up integration and patching before they can fully exploit ITSM automation tools powered by natural language AI.
