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Summary
Challenges
- Wanted to embed AI across application management, infrastructure management, process management, and data center operations
- Needed practical, prioritized next steps rather than more generic industry reports to work through independently
- Different internal teams' compliance, data center infrastructure, and cloud, each had distinct tools, processes, and gaps that needed to be understood individually
- Limited appetite to scale headcount significantly, increasing the pressure to automate technology operations instead
- Needed the resulting plan understood consistently across both senior leadership and the wider technical team
Solutions
- Mapped the client's existing tools and processes in detail before recommending anything
- Held dedicated working sessions with three separate functional teams to surface specific gaps and needs
- Built a phased 30-60-90 day AI adoption roadmap, refined through iterative client feedback
- Adjusted the roadmap's direction in direct response to client input shifting emphasis from FinOps toward automation
- Delivered a detailed AI intervention plan covering CMDB data hygiene, agentic ticketing enrichment, and CMDB to APM mapping, sequenced across three phases
- Presented recommendations through working sessions with senior leadership, then follow-up sessions with their wider team to keep everyone aligned
- Ran the engagement through a recurring monthly cadence, adapting the plan based on direct stakeholder feedback each cycle
Outcomes
- Delivered a complete, actionable AI adoption roadmap from immediate steps through to longer term goals
- The client's technology team asked Twimbit to help build the AI agents identified in the roadmap
- Improved cross-team alignment, with both senior leadership and functional teams engaging directly with the recommendations
- Advisory engagement remains active on a monthly cadence
Embedding AI into technology operations, without more reports to read
A leading multinational insurance group, operating across Asia, wanted to bring more AI into how their technology function runs not as a single initiative, but across application management, infrastructure management, process management, and data center operations. Facing pressure to do more without significantly growing headcount, the technology leadership team wanted a clear, prioritized path for where AI could genuinely help, rather than another set of broad industry reports to work through on their own time.
Leadership had already been receiving research and frameworks from multiple advisory firms, and found most of it too generic to act on directly. What the team wanted instead was a partner willing to understand their specific tools, teams, and gaps closely enough to come back with something they could actually use.
Mapping the client's reality before recommending a roadmap
Twimbit began by understanding what the client already had in place - the tools, platforms, and processes already running across their environment before recommending anything. An initial framework built on that foundation prompted the client to ask for more specificity, so Twimbit went further, dedicated working sessions were held with three separate functional teams, spanning compliance, data center infrastructure, and cloud, each surfacing its own processes, constraints, and gaps.
That input shaped a phased 30-60-90 day AI adoption roadmap. The roadmap itself evolved through direct client feedback. The client asked for more emphasis on automation, which shaped the phases that followed. The engagement then moved into a detailed AI intervention plan covering data hygiene for the client's configuration management database (CMDB), agentic ticketing enrichment, and CMDB to APM mapping sequenced across three consecutive phases.
Recommendations were delivered through focused working sessions rather than lengthy documents, first with the senior technology stakeholder directly, then in follow-up sessions with his wider team, to keep the plan understood consistently across the organization rather than concentrated at the top. The engagement has continued on a recurring monthly cadence, with each cycle shaped by the client's direct feedback from the one before.
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