Generative AI: Transforming the Business Landscape
The Rise of Generative AI
Generative AI (GenAI) has transitioned from a buzzword to a standard. Today, it’s a crucial asset for innovative businesses. Rajesh Ramdas, Senior Director at Databricks, discussed this at YourStory’s India Tech Leaders’ Conclave 2024.
Ramdas highlighted GenAI’s fast adoption. Approximately 90% of organizations he interacted with are either invested in or experimenting with GenAI.
Impact on Productivity and Competitiveness
Ramdas noted that 75% of CEOs see GenAI as a competitive advantage. Employees using GenAI have experienced productivity boosts of around 40%.
Though proficient in general knowledge, GenAI struggles with specific queries. Additionally, widespread adoption faces regulatory, privacy, and cost challenges.
Challenges at Various Levels
At the organizational level, ownership and model responsibility are key concerns. Data privacy and cybersecurity also pose significant challenges, especially for AI models.
Ramdas emphasized the need for high-quality outputs and observability of model drifts to ensure reliability.
Solutions and Best Practices
To address these concerns, establishing clear business rules and good data governance is crucial. Centralizing data and understanding its semantics also play a vital role.
Companies like Uber and Netflix attribute their competitive edge to relevant data. Centralized governance simplifies the management of fragmented data.
Ensuring Model Quality
Monitoring and correcting model outputs are essential for trustworthy results. Having robust tools and processes mitigates errors.
As GenAI evolves, it is increasingly used for image and video generation. Organizations like Shutterstock manage copyright issues by using their image data for model training.
AI for Multiple Languages
One of GenAI’s future focuses is on non-English content generation. Ramdas suggested that soon, GenAI will not only answer queries but also take action.
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