Routine prep and manual research bottlenecked 4,000 employees. Copilot now structures content, freeing staff for strategic thinking.
A global Swiss provider of electrical and optical connection technologies operating with 4,000 employees across 40 locations and a production network spanning over 80 countries.
The organization needed to improve how knowledge was shared and accessed across its global footprint to foster better internal collaboration....
“We are introducing Microsoft Copilot not just as a new tool: We specifically want to try out how generative AI can support our strategic goals.”
Electrical and optical connectivity components for data and energy transmission.
Assisted Huber+Suhner with technical implementation, strategic orientation, and user enablement.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Huber+Suhner's Workplace productivity is part of this use case:
Related implementations across industries and use cases
Teams spent hours digging through internal data. Now, Copilot accelerates client research and drafts targeted pitch copy.
Critical know-how was retiring with veteran engineers. Now, AI agents turn expert videos into instant, searchable guidance for new hires.
Employees spent hours manually summarizing and translating technical documents. Now, custom GPTs generate first drafts for teams to refine.
Teams spent hours digging through internal data. Now, Copilot accelerates client research and drafts targeted pitch copy.
Sales reps lost hours manually hunting for proposal data. Now, teams consult AI first to surface best practices and draft pitches.
Manually updated profiles left skills stale. The first prototype took two hours per 1,000 consultants—now the agent covers 130K in minutes.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Routine prep and manual research bottlenecked 4,000 employees. Copilot now structures content, freeing staff for strategic thinking.
A global Swiss provider of electrical and optical connection technologies operating with 4,000 employees across 40 locations and a production network spanning over 80 countries.
The organization needed to improve how knowledge was shared and accessed across its global footprint to foster better internal collaboration....
“We are introducing Microsoft Copilot not just as a new tool: We specifically want to try out how generative AI can support our strategic goals.”
Electrical and optical connectivity components for data and energy transmission.
Assisted Huber+Suhner with technical implementation, strategic orientation, and user enablement.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Huber+Suhner's Workplace productivity is part of this use case:
Related implementations across industries and use cases
Teams spent hours digging through internal data. Now, Copilot accelerates client research and drafts targeted pitch copy.
Critical know-how was retiring with veteran engineers. Now, AI agents turn expert videos into instant, searchable guidance for new hires.
Employees spent hours manually summarizing and translating technical documents. Now, custom GPTs generate first drafts for teams to refine.
Teams spent hours digging through internal data. Now, Copilot accelerates client research and drafts targeted pitch copy.
Sales reps lost hours manually hunting for proposal data. Now, teams consult AI first to surface best practices and draft pitches.
Manually updated profiles left skills stale. The first prototype took two hours per 1,000 consultants—now the agent covers 130K in minutes.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.