AI Product Strategy · GenAI · Conversational AI · UX Strategy · Salesforce Lightning · Product Roadmapping

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While at Deloitte, I partnered with Edward Jones to define and deliver an integrated AI product ecosystem designed to modernize how clients, advisors, and internal teams access information and process client documentation.

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My involvement began during the proposal stage, where I developed the initial AI product blueprint, identifying the AI capabilities required, how they would communicate with existing enterprise systems, and how those capabilities could evolve through a phased product roadmap. After the engagement was awarded, I moved into discovery, interviewing stakeholders and users to validate the strategy and identify where AI could provide the greatest value.

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The resulting ecosystem centered on two interconnected products: a GenAI-powered document processing platform integrated with Salesforce Lightning and an AI-enabled IVR experience designed to provide clients with more intuitive, conversational access to information and services.

 

What I Did

I led the UX and AI product strategy from early concept through research, experience definition, product design, and implementation. Working alongside product stakeholders, AI engineers, frontend and backend developers, and QA, I translated complex financial-service workflows into an integrated ecosystem of AI-assisted experiences.

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For the GenAI document platform, I designed workflows that allowed advisors and internal teams to upload scanned images, handwritten forms, PDFs, and typed documents. The AI classified and interpreted the content, extracted critical client information including names, identification numbers, financial data, and other relevant fields and mapped that information to the appropriate client record. I also designed the review experience around AI confidence scoring, validation, exception handling, and human override, ensuring users remained in control of consequential data decisions.

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For the AI-enabled IVR product, I used stakeholder and user research to rethink the traditional phone-tree experience. The resulting concept combined natural-language interaction with existing client and enterprise data, allowing common inquiries and tasks to be handled more intelligently while preserving escalation to human support when needed.

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Across both products, I incorporated WCAG/Section 508 accessibility, data integrity, human-in-the-loop validation, security considerations, and scalable product architecture into the experience strategy.

 

Outcome

The work transformed previously manual, disconnected processes into a more intelligent and connected experience spanning clients, advisors, internal teams, AI services, and enterprise systems.

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60%+ reduction in manual processing time

Automated document interpretation, extraction, mapping, and filing significantly reduced repetitive processing work.

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45% improvement in data-field accuracy and filing precision

AI-assisted extraction combined with confidence scoring, validation, and human review improved the reliability of information entering client records.

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Greater advisor confidence

Usability testing and iterative design helped create workflows where users could understand what the AI had done, verify its output, and intervene when necessary.

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Built for enterprise scale

The product strategy and architecture were designed to support high document volumes, including peak tax-season demand, while maintaining accessibility, data quality, version control, and consistency.

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From Strategy to Experience

Explore the AI ecosystem, product roadmap, research and journey mapping, GenAI document-processing workflows, AI IVR architecture, and Salesforce Lightning experience that brought the strategy to life.