Berkie

PRODUCT

Berkie

ROLE

Design Lead

DURATION

1.5 years

OVERVIEW

In 2023, Berkadia embarked on a transformative journey to leverage artificial intelligence (AI) across its commercial real estate (CRE) services. Our primary objective was to enhance data-driven decision-making and improve operational efficiency in key business lines such as mortgage banking, investment sales, and loan servicing. While the potential of AI in real estate was evident, we knew the real challenge lay in how effectively we could integrate these solutions into daily work processes while fostering a culture of innovation and collaboration.

00 The Challenge of AI Adoption in CRE

The CRE industry is traditionally slow to embrace new technologies, and introducing AI posed significant challenges. From cultural resistance to aligning stakeholders, the adoption process required a thoughtful strategy:

01 MVP Launched on one month

We started with discovery sessions across various Berkadia teams, such as mortgage bankers and loan servicing, to understand how AI could improve daily tasks. Key findings included:
• Overwhelmed by data: Employees struggled to find meaningful insights.
• Repetitive tasks: Many tasks could be automated to save time.

With these insights, we developed and launched an MVP in just one month. The AI tool included:
• Automated Knowledge Retrieval: Instant answers to routine industry questions.
‍• Engagement Tracking: Built-in analytics to monitor usage and gather feedback.

03 Designing a Lo-Fi Vision & Testing Ideas

At the second phase, we gathered feedback through interactive sessions, focusing on validating key functionalities and usability. Insights from these tests helped prioritize features that would have the greatest impact on users’ daily tasks.

Post-launch, feedback data revealed:
• High adoption for routine tasks. But there are still users don't understand the best practice to utilizing AI in day -to-day work.
• A need for refining the accuracy and relevance of knowledge retrieval.
• User requests for better integration with existing tools and platforms.
These insights confirmed the MVP’s promise and provided direction for further iterations.

04 Iterative Design: User & Data based evaluation

With initial feedback in hand, we moved into the iteration phase, where we made targeted improvements to the platform. We prioritized enhancements based on employee usage patterns and areas of friction:
1. Data/Guide Assistant for Investment advisors and Mortgage Bankers
2. Prompt Library for all user engagment
3. Document Upload/Analysis for Underwriting

Usability improvements:
• Improved User Interface:
Easy Access Simplify the interface Dark/light mode for better readabilityOptimum text input fields
• Accuracy of AI Insights: We refined the lead generation algorithms, making them more sophisticated by incorporating more data points and refining the machine learning models.

05 Sparkle User Engagement

To enhance user engagement by creating a more cohesive and visually appealing experience that meets user expectations, we decided to rebrand this product. Refreshed brand identity into UI elements, interactive components, and storytelling can make interactions more intuitive and engaging. A modernized design system also improves usability, streamlining workflows and building trust in the platform.

06 Best UX Practice

AI product design differs from traditional UX, as it’s driven by technological advancements rather than user needs. Designers must adapt by aligning AI capabilities with real problems while leveraging AI tools to accelerate research and development.

The rapid pace of AI shortens product cycles, requiring agile processes to keep users at the center. However, blindly copying existing AI models can be ineffective. Instead, designers should prioritize usability, integrate AI seamlessly into workflows, and validate solutions through rapid testing.

Success in AI UX hinges on adaptability, critical thinking, and balancing innovation with human-centered design to create meaningful user experiences.

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