“The future of work will be less monotonous. AI will take care of it on the back end and free up time to do more critical thinking…you will challenge yourself and actually push the limits of what’s possible because time will no longer be constrained”
That’s one of the observations from David Shim, CEO at Read AI, on this episode of Shift AI, a show that explores what it takes to thrive and adapt to the changing workplace in the digital age of remote work and AI. We discuss David’s background and experience bringing innovative technology to life and launching multiple successful ventures.
Listen below, and continue reading for highlights from his comments, edited for context and clarity. Subscribe to Shift AI and hear more episodes at ShiftAIPodcast.com.
David’s early background: I initially majored in political science because I struggled with math, which prevented me from entering the business school at UW. After graduating, I identified a gap in the stock trading market and attempted to create a competitive stock trading league, well before the era of Wall Street Bets. Although the venture didn’t take off, it served as my first startup experience and taught me the importance of following through on a business plan. This early endeavor set the tone for my career approach: identifying emerging opportunities in nascent markets. I found that entering these untapped spaces at the right time could significantly accelerate my career.
First Job and Family: My first job was at an Alderwood movie theater, where I learned customer service skills and the art of upselling. Coming from a family where education was valued, my Korean immigrant parents ran various businesses despite language barriers, relying on long hours and hard work to succeed. Their entrepreneurial spirit resembled a startup mentality: starting with nothing and gaining traction through sheer effort. My father eventually transitioned into auto sales, becoming one of the top salesmen in the late ’80s. Their experiences taught me that problems can be solved either through smart solutions or brute force, emphasizing the importance of commitment and effort.
Early career in startups: In my early career, I found immense satisfaction in building startups like Placed and Read AI from scratch, despite the challenges. Placed, founded in 2011, focused on location analytics and evolved its technology to fit into the mobile ads market, eventually being acquired by Snapchat and later by Foursquare. At Read AI, I addressed the gap in video meeting engagement, especially highlighted by the COVID-19 pandemic’s impact on remote work. The startup aims to analyze various data points to assess the productivity and quality of virtual meetings. While each venture had its ups and downs, the rewarding moments made the journey worthwhile.
How the AI shift has changed Read AI direction: When Read AI first launched, the focus was on R&D and finding a product-market fit, primarily measuring real-time engagement and sentiment. We soon realized that users were more interested in meeting transcriptions and summaries. To meet this need, we developed a unique approach that combines audio, video, and participant reactions to create superior meeting summaries. We also introduced a feature that condenses a two-hour meeting into a one-minute video trailer, highlighting key moments of engagement. This evolution in our AI capabilities now allows us to offer actionable recommendations for running meetings more efficiently.
Startups vs. Incumbents: In the startup landscape, we maintain a positive relationship with established companies, viewing them as partners in market education. These incumbents play a crucial role in informing the market about available solutions. Newer companies can benefit by integrating their services with these larger players, creating a more comprehensive offering. This symbiotic relationship allows startups to leverage the reach and credibility of incumbents. Overall, collaboration with established firms can significantly enhance a startup’s market presence and solution robustness.
Meeting management: In meetings, we often struggle to decline requests due to politeness, yet meetings are fundamentally transactional. To enhance meetings, we begin by evaluating them as good or bad. Analyzing metadata helps identify meeting elements for improvement. Smart scheduler, for instance, leverages this data to provide guidance for a better meeting experience.
Meeting Culture: Today’s meeting problem revolves around the need for intentionality. While meaningful feedback can have an impact, its longevity is a concern. Saying no when your boss requests an hour-long meeting can be challenging due to ingrained habits. This is where technology steps in, subtly organizing things without offense or disruption, like reconfiguring without feeling like a loss.
Meeting Equity: AI can suggest making remote participants optional or excusing them from low-value meetings if they haven’t contributed lately. This avoids direct feedback discomfort. People accept AI nudges more easily than peer feedback, aiming for improved meeting outcomes without interpersonal friction. Unlike humans, computers don’t provoke anger, similar to following Google Maps directions. AI’s data-driven, impersonal approach can address inclusion and engagement concerns effectively.
Hybrid / Remote Work: Remote work is promising, but we’re still in the early stages. Initially, hiring globally for the same skill set was excellent, but there’s now some pullback due to setup overhead. However, remote work allows retaining talent regardless of location. The rise of asynchronous meetings is a testament to this evolving landscape.
Mentors: From a hard work perspective, my parents ensured a solid foundation for us. In my business journey, mentors played a crucial role. Steve Jarvis, an Alaska Airlines executive, guided me in handling challenges and presenting issues effectively. Matt McIlwain was instrumental in navigating the startup landscape and the world of venture capital, offering valuable advice and posing critical questions to steer our path.
Emerging Tech: Regarding AI, there’s a shift happening in question-asking. People enjoy interactive prompts and visuals, but content consumption is now leaning towards discovery and algorithms.
Listen to the full episode of Shift AI with David Shim here.