Systems | Development | Analytics | API | Testing

If 2023 was the year we woke up to how generative AI would change our world, 2024 is the year we realize the change. The real-time AI-driven enterprise may not be pixel-perfect yet, but we’re well on the way. Gen AI has a knock-on effect on all the trends and challenges we will see in 2024. Here’s our take.

For the next interview in our series speaking to tech founders from around the world, we’ve welcomed Seung Oh, Co-Founder and CEO of Data B, the company behind Engram, the first AI-powered writing platform designed for non-native English speakers.

Artificial intelligence is changing the world. With use cases ranging from content generation to deep data analysis to detecting health issues, AI can greatly improve lives and enhance business outcomes. And with the explosion of generative AI services and large language models, we can expect AI to become even more ubiquitous than it already is. But AI isn’t perfect. In particular, AI privacy issues put organizations at risk or prevent adoption in the first place.

Snowflake account managers need their fingers on the pulse of which workload shifts or performance optimizations could improve customer experience. Yet without an all-encompassing view of their customers, sales teams have to piece together customers’ wants and needs through duplicate CRM accounts and various BI tools and dashboards.

AI automation is changing the game in business operations. For many companies, global competition is heating up fast on an increasingly crowded playing field. In the past, business leaders knew their competitors and how they operated. But now, executives across industries have to look over their shoulders for new challengers that arrive with surprising speed from virtually any corner of the globe.

As an industry built on data, financial services has always been an early adopter of AI technologies. In a recent industry survey, 46% of respondents said AI has improved customer experience, 35% said it has created operational efficiencies, and 20% said it has reduced total cost of ownership. Now, generative AI (gen AI) has supercharged its importance and organizations have begun heavily investing in this technology.

With the integration of BigQuery and Document AI, you can extract insights from document data and build new large language model (LLM) applications.

Vertex AI transcription models in BigQuery let you transcribe speech files and combine them with structured data to build analytics and AI use cases.