How a Global Financial Intelligence Enterprise Proved Its AI Investment Was Paying Off

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THE CHALLENGE

No Visibility, No Benchmarks, No Way to Prove AI Was Working

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Senior leadership was asking hard questions about AI’s impact on costs and headcount. The company had invested heavily in Salesforce Service Cloud licenses and Einstein AI add-ons, along with Microsoft Copilot. Yet no one knew what share of cases were actually being handled with AI. Handle time had never been broken down by product line. And reports were being assembled manually by a single senior specialist. 

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The assumption from outside the team was that the data would show AI licenses could be cut. The ops team knew the real question was harder: was AI being used effectively enough to justify keeping a high-skill, high-cost team at its current size and budget? Without precision work intelligence data, there was no way to answer.

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THE SOLUTION

One Platform to Make AI Work Visible and Defensible

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The enterprise turned to Insightful's Workflow Optimization to consolidate fragmented GenAI usage tracking and surface workflow visibility in one place. 

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The deployment was built around anonymized, team-level reporting, not individual monitoring. The goal wasn’t to watch employees. The enterprise wanted to know whether their processes were actually working at scale, across teams, handoffs, and the customer service department as a whole.

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Now, with Workflow Optimization, for the first time leadership could see their teams’ processes end-to-end. Insightful’s advanced task mining and process intelligence features quickly revealed: 

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• Exactly what share of cases were being handled with AI
• How handle time varied by product lines
• Whether teams were hitting internal benchmarks
• Where coaching could have the most impact

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All in one place, across 78,000 cases, without a manual export in sight.

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THE RESULTS

Clarity Where There Was None

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For the first time, the enterprise had a complete picture of how AI was being used across its service operation:

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• 83.7% non-AI vs 16.3% AI usage split. The fact most cases didn’t involve AI wasn’t a problem. On the contrary, Workflow Optimization showed AI was being deployed specifically on complex cases where it provided the most value.
• 10.1% to 25.7% variation in AI absorption across product lines. Workflow Optimization pinpointed exactly where managers were driving AI usage, and where they weren’t.
• Handle time tracked by product line for the first time. No manual exports required.
• Real answers to hard questions about AI spend and headcount. The customer service team was able to quantify hard returns on its AI investment, previously impossible with manual reporting or surface-level vendor dashboards.

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How Insightful Became the Source of Truth for AI ROI

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Leadership was already writing the narrative: the spends on GenAI and high-skill specialists weren’t showing measurable results. 

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The customer service team needed precision data to tell a different story. Six months of case-level visibility across 78,000 cases showed exactly how AI was being used, which products were driving adoption, and why the work couldn't simply be automated away. For the first time, they could walk into that conversation prepared.

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THE FUTURE

From Visibility to AI Governance

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The next step is expanding beyond Salesforce Service Cloud and Copilot to track every AI tool in use across the organization, including Claude and Cursor. What started as a question about one department’s AI adoption is becoming a company-wide intelligence layer, giving leadership a complete, ongoing picture of how AI is actually being used across the business.

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What It Means for Your Bottom Line

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When leadership demands proof that AI is paying off, Workflow Optimization turns invisible work into a defensible ROI story.