How Motive Uses Glean to Deploy 2,000+ AI Agents and Save Thousands of Hours

Motive builds the operating system for physical operations — a unified platform for fleet management, safety, and financial tools used by nearly 100,000 customers in transportation, construction, energy, agriculture, manufacturing, and logistics. As a self-described AI-first company, Motive holds a high bar for how AI should work internally: tools need to be accessible to every employee, grounded in real company context, and governed without slowing innovation down.

As Motive scaled, employees were context-switching between multiple disconnected applications to find the information they needed. Knowledge was fragmented across Salesforce, Slack, Google Drive, and other tools, with no unified way to query across sources. The company set an ambitious target — 50% productivity improvement — and identified enterprise search and agentic AI as the foundational capabilities to get there. The challenge was finding a platform that could support security, model flexibility, and rapid agent deployment without requiring engineering overhead for every new use case.

Motive deployed Glean across the organization in a phased rollout, starting with key data source connections and department-level AI champions. Glean Search gave employees a single interface to query the company’s entire knowledge graph, drawing from all connected tools with permission-aware results. Glean’s Agent Builder allowed teams to create agents using natural language, without code. Within months, Motive had over 2,000 agents in deployment across every department. The company also launched AI Labs — open, cross-functional sessions where employees prototype agents tied to real business outcomes, with subject-matter experts providing live feedback.

The results were measurable. The GTM Account Plan Creation Agent reduced account planning from three days to two hours — a 75% reduction in time — by synthesizing CRM data, external news signals, and unstructured inputs from Slack and meeting tools. The HR Self-Assessment Agent saved 60 to 90 minutes per employee per review cycle, and logged over 1,100 runs in its first performance cycle alone. The Sales Prospecting Agent saves 60 minutes per run by automatically tailoring emails, discovery questions, and talk tracks from Motive’s sales content library. Across AI Labs sessions over six months, the program generated over 55 quantified outcomes and drove cross-functional collaboration at a scale that would not have been achievable with fragmented, function-by-function AI tooling.

Motive’s approach reflects a philosophy of decentralized innovation with centralized guardrails: any employee can build and deploy agents, but quality, security, and data governance are managed centrally through Glean. The company is now analyzing whether high AI adoption correlates with stronger team KPIs — early signals suggest it does — and is shifting from measuring efficiency gains alone to tracking effectiveness improvements and innovation investment returns.