For more practical perspectives to help leaders navigate the challenges and opportunities of building a growth company subscribe to The Ascent 

Webinar Highlights

Use Cases: Key Considerations [03:35]

Generative AI is probabilistic, offering varied outputs for the same inputs. While this can be challenging and disorienting, there are a number of use-cases where this can be an advantage.

Use Cases: External and Internal Examples [5:57]

Internal use cases for AI often focus on productivity and creativity, including by automating manual tasks, speeding up content creation, and helping employees with tasks outside their immediate expertise.

External use cases for AI are more varied and dependent on your business; consider enhancements or extensions of your current products and services that have the potential to build long-term value and differentiated experiences for customers.

Using Large Language Models: Buy vs. Build Strategies [11:08]

Many companies will likely use generative AI via third party software. For those looking to build custom experiences, it’s important to understand the spectrum of build vs. buy options to decide on the approach that aligns with your business needs.

Getting Started: Balancing Top-Down and Bottom-Up Approaches [14:05]

Incorporating generative AI requires a balance between top-down guidance from leadership and bottoms-up experimentation from teams. Experimentation and proof of concepts are crucial in the early stages to determine valuable use cases.

Cost Considerations [16:43]

The costs associated with integrating generative AI technologies into your business operations vary significantly depending on your use cases and the models or applications you employ, or resources (including talent) your organization requires.

Cathy Tanimura

Vice President, Analytics & Data Science, Summit Partners Peak Performance Group

Cathy works closely with the Summit team and our portfolio companies to help create and execute strategies that effectively use data and analytics to drive better decisions and build better products.

Prior to Summit, Cathy worked at Strava, where she built an analytics and data science team focused on product, marketing and business development. Previously, she led analytics teams at Okta and Zynga.

Related Content

Additional frameworks and perspective from Summit Partners

Subscribe to The Ascent


The Ascent offers frameworks and strategies to support growth company leaders through a quarterly newsletter and on-demand webinars. Sign-up to view the latest issue and stay up to date on insights and activity from across the Summit Partners Network.