The Current State of AI with Jaclyn Rice Nelson from Tribe AI
Some takeaways:
— There’s a significant gap between the hype around AI and its actual implementation in businesses. Many companies are still in the experimental phase, with few AI solutions in production. The main barriers to AI adoptions are technical challenges, cost considerations, and lack of expertise. We’re still very early in realizing AI’s promise.
— AI adoption was slow, then immediate. In a pre-ChatGPT world, the focus was on convincing companies to care about data science and machine learning. Post-ChatGPT, there’s been an explosion in demand, with companies actively seeking AI solutions.
— Most companies are still in the proof-of-concept stage. There’re limited production-ready AI use cases, which hinders adoption. But with major cloud providers (Microsoft, Amazon, Google) aggressively pursuing AI strategies, that’s bound to change. There’s constant evolution in model performance and capabilities. Companies need to view AI as a continuous investment, similar to cloud infrastructure, rather than a one-time project.
— Tribe’s approach to AI implementation is what made it such an interesting investment for indie. Their focus on education to help companies understand AI's potential, and emphasis on quick, cost-effective proof of concepts to demonstrate value, means they’re positioned to continue rapidly growing. As a services business, they’re able to help companies balance cost with value creation, navigate rapidly evolving AI technologies, and future-proofing AI investments.
— There’s a significant gap between the hype around AI and its actual implementation in businesses. Many companies are still in the experimental phase, with few AI solutions in production. The main barriers to AI adoptions are technical challenges, cost considerations, and lack of expertise. We’re still very early in realizing AI’s promise.
— AI adoption was slow, then immediate. In a pre-ChatGPT world, the focus was on convincing companies to care about data science and machine learning. Post-ChatGPT, there’s been an explosion in demand, with companies actively seeking AI solutions.
— Most companies are still in the proof-of-concept stage. There’re limited production-ready AI use cases, which hinders adoption. But with major cloud providers (Microsoft, Amazon, Google) aggressively pursuing AI strategies, that’s bound to change. There’s constant evolution in model performance and capabilities. Companies need to view AI as a continuous investment, similar to cloud infrastructure, rather than a one-time project.
— Tribe’s approach to AI implementation is what made it such an interesting investment for indie. Their focus on education to help companies understand AI's potential, and emphasis on quick, cost-effective proof of concepts to demonstrate value, means they’re positioned to continue rapidly growing. As a services business, they’re able to help companies balance cost with value creation, navigate rapidly evolving AI technologies, and future-proofing AI investments.