Every morning, Veselin Vuković, Infobip's head of partnerships, sits down to a stack of unstructured data — meeting transcripts, partner emails, negotiation notes, cultural briefs from global telecoms and tech companies. His job is to find the intersection where two organizations with different business goals and corporate cultures can strike a deal. The bottleneck has always been the same: turning that mountain of text into a decision.

Infobip, a cloud-based customer communication platform, decided 18 months ago that the bottleneck had to go. The company rolled out Microsoft 365 Copilot to all 3,500 employees. Not as a pilot. Not to a select team. Everyone.

Section 1: How Infobip Deployed Copilot Across 3,500 Employees

Vuković uses Copilot to summarize internal meetings and conversations with partners, then extract follow-up action items. But the deployment goes far beyond meeting notes. Infobip feeds both structured data and unstructured text — the kind that lives in emails, chat logs, and documents — into the AI for analysis.

The company also built custom AI agents using Copilot Studio, Microsoft's tool for creating enterprise chatbots without heavy engineering. These agents live inside Microsoft Teams and serve two primary functions: internal knowledge retrieval assistants and workflow-specific bots. They were deployed directly to business teams without requiring large development cycles.

Before Copilot, a team member would manually transcribe meeting takeaways, write an email summary, and then copy action items into a task list. That process took hours, sometimes spilling into the next day. Now, insights from a meeting flow directly into Outlook as follow-up emails, into Word as structured summaries, or into Planner as task lists. The manual translation layer — converting spoken conversation into structured work — has been eliminated.

Section 2: What Actually Changed — The Speed of Analysis

The headline number is the shift in cycle time. Data analysis and decision-making that used to take days now takes hours. That is not a marginal improvement. It is a structural change in how the organization processes information.

But the real insight is not about the tool. It is about what the tool forced Infobip to do. Deploying Copilot at scale required the company to look at its existing workflows and ask which ones were built around human limitations rather than business logic. The old process — manual transcription, email forwarding, task entry — existed because there was no alternative. Once the alternative arrived, the process itself became the obstacle.

Vuković's team did not just add AI to the old workflow. They dismantled the old workflow and rebuilt it around the AI. The result is that analysis speed is no longer a function of how fast a person can type or copy-paste. It is a function of how fast the AI can parse the input and surface the output.

Closing

Infobip's experience suggests that the real ROI of enterprise AI is not in doing the same work faster, but in redesigning work so that speed becomes a default property of the system, not a goal to chase.