Everyone's asking if AI will pay off. This company has proof it does. (www.businessinsider.com)

Fintech software firm TS Imagine reports concrete ROI from deploying an in-house AI agent, TAIA: the company says three targeted automations — customer‑service ticket triage, classification of ~100,000 vendor emails a year, and converting exchange PDFs of corporate actions into structured data — have eliminated roughly 8.5 full‑time‑employee equivalents out of ~34 data and client‑service analysts. Practical impacts include a tenfold speedup in ticket handling (10 minutes → ~1 minute), email processing at about 3% of prior costs, elimination of manual errors in corporate‑action math, and faster position updates before markets open. TS Imagine used data‑wrangling tools including Snowflake Intelligence and invested thousands of engineering hours to operationalize LLMs and document‑parsing pipelines; rather than mass layoffs, the firm reassigned staff to higher‑value work like data quality and client relationships. TS Imagine’s experience — echoed by a Wharton study finding 74% of enterprises report positive AI ROI — offers a concrete counterpoint to worries that massive AI infrastructure spending won’t pay off. The lesson for AI/ML teams: models alone aren’t enough; measurable returns require careful integration, automation of specific workflows, error‑sensitive pipelines, and change management. For enterprises weighing AI investments, this case shows targeted automation can both cut costs and unlock better allocation of human expertise, making large AI expenditures easier to justify.