Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Artificial intelligence, professionally covered
Process automation
Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.
Reported by wyecliff.ai (vendor self-report). Checked against the source page on 2026-09-05. 0 of 13 figures below appear on that page word for word; the rest are marked.
Adoption of Copilot had stalled even though producers already had Microsoft 365 and Copilot licenses, because they didn't have time to learn a new tool while focused on clients; producers who did engage needed a strong AI foundation and working tools to effectively use Copilot in their day-to-day tasks.
Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.
“We raised the bar on AI knowledge and use across a group of 500+ producers... [stat block label:] Producers trained across the series”
Not found on the source page in these words
“We surveyed the full producer group, and the results averaged 4.6 out of 5. [stat block label:] Average producer rating across the full group”
Not found on the source page in these words
“Morning briefing prep dropped from 30-45 minutes to under 2 minutes. [stat block label:] On morning briefings (45 minutes down to under 2)”
Not found on the source page in these words
“Prospect research went from hours per batch to under 10 minutes.”
Not found on the source page in these words
“We cataloged and prioritized 45+ use cases across their workflows. [stat block label:] AI use cases identified and prioritized”
Not found on the source page in these words
“over 500 producers in the audience immediately saw the value that Copilot brought and wanted to learn more. [stat block label:] Producers reached in live summit demos”
Not found on the source page in these words
“three to four sessions each serving 12-15 producers over roughly eight weeks”
Not found on the source page in these words
“We run the cohort as a concurrent, one-on-one coaching track for small groups of about five or six producers at a time”
Not found on the source page in these words
“its service operation, the Employee Benefits and P&C teams, was ready for a program of its own, covering roughly 2,500 people.”
Not found on the source page in these words
“About 2,000+ people had Copilot Chat, and about 700+ had the full Microsoft 365 Copilot”
Not found on the source page in these words
“About 2,000+ people had Copilot Chat, and about 700+ had the full Microsoft 365 Copilot”
Not found on the source page in these words
“Both ran as weekly one-hour Town Halls, drawing well over a thousand live attendees”
Not found on the source page in these words
“We designed and delivered two independent six-week courses, one for each license tier”
Not found on the source page in these words
“IMA's own IT leadership called it one of the best rollouts and trainings they had seen at the company.”
Not found on the source page in these words
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Independently reportedManufacturing · Process automation · Classical ML · Scaled
under 10 minutes — Time for root cause analysis
Independently reportedManufacturing · Process automation · AI agents · In production
88% — autonomous IT resolution rate
Independently reportedTechnology & software · Process automation · NLP · Scaled
10% more — shopper spend
Independently reportedRetail & e-commerce · Process automation · Computer vision · Scaled · 2024
increased by 15% — accuracy
Independently reportedInsurance · Process automation · Classical ML · Scaled · 2019