Reported impact
Business outcome
This is what they told us in that conversation as summarized by Azure OpenAI Service
- Customer Experience
- Productivity Improvement
MicrosoftCommercial and Professional ServicesDocument ProcessingEnterprise Knowledge SearchAI and Machine LearningGenerative AI / LLMCustomer ExperienceProductivity Improvement2023 MicrosoftMS#0078d4Commercial and Professional ServicesUnited StatesBrad Brown, Global Technology leader and CIO for Tax at KPMG, and Rafiq Jalal, Principal at KPMG, Cloud and Data Strategy, spoke with us about how KPMG is putting Azure OpenAI Service to work.Jalal says, “There’s been demonstrable value on day one, that changes your perspective about success.” The KPMG…Mar 16, 20235Document Processing|Enterprise Knowledge SearchAzure OpenAI Service0 2023-03-16 5
KPMG
Document Processing · Enterprise Knowledge Search
Brad Brown, Global Technology leader and CIO for Tax at KPMG, and Rafiq Jalal, Principal at KPMG, Cloud and Data Strategy, spoke with us about how KPMG is putting Azure OpenAI Service to work.
Jalal says, “There’s been demonstrable value on day one, that changes your perspective about success.” The KPMG global tax group is using Azure OpenAI Service as a foundational layer for building use cases on top of generative AI.
Microsoft technical architecture supports these goals by allowing KPMG to have more control and give its clients accurate lineage of information.
The KPMG strategy for measuring success is based on its capabilities to assist and augment and how it can help its people and clients become more productive.
Solution
KPMG built a Microsoft-based workflow around Azure OpenAI Service because Brad Brown, Global Technology leader and CIO for Tax at KPMG, and Rafiq Jalal, Principal at KPMG, Cloud and Data Strategy, spoke with us about how KPMG is putting Azure OpenAI.... Source information is captured from frontline systems, documents, transactions, images, or conversations and then processed with cloud services that classify, summarize, model, or route the data for downstream use. The resulting records are stored in shared business or analytical systems and surfaced through apps, dashboards, or case workflows so staff can move from manual review to faster action while still keeping a governed human-in-the-loop process. This turns scattered data into an operational workflow rather than a static report, making the same platform useful for both daily execution and future scaling, and This is what they told us in that conversation as summarized by Azure OpenAI Service.
Data flow
Source data is captured from frontline systems or content, processed by the Microsoft-based workflow, stored in a shared business or analytical layer, and then surfaced back to staff through apps, dashboards, or case-management experiences.
Solution architecture
- Compute
- Azure OpenAI Service Runs generative AI prompts on governed enterprise data to summarize, reason, or draft outputs.
Architecture clues
- Microsoft technical architecture supports these goals by allowing KPMG to have more control and give its clients accurate lineage of information.
- Primary implementation components: Azure OpenAI Service
- The KPMG strategy for measuring success is based on its capabilities to assist and augment and how it can help its people and clients become more productive.
Evidence from the source
Brad Brown, Global Technology leader and CIO for Tax at KPMG, and Rafiq Jalal, Principal at KPMG, Cloud and Data Strategy, spoke with us about how KPMG is putting Azure OpenAI Service to work.
KPMG believes that Azure OpenAI Service will change its service delivery model and impact its coding lifecycle through product experience enhancement, knowledge enhancement, and content distribution. KPMG has chosen
Microsoft Azure OpenAI Service
This is what they told us in that conversation as summarized by Azure OpenAI Service
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value57/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity12/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact0/250 metrics describe measurable impact.
- Deployment scale5/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/204 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity8/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.microsoft.com/en/customers/story/1607565448540657318-kpmg-professional-services-azure-openai-serviceMicrosoftFirst-party
KPMG customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
Date evidence
- Published on source page Mar 16, 2023 · Microsoft · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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