BigQuery And AlloyDB Hit Major Milestone With AI-Enabled Updates
Google Cloud News, Thursday, February 29th, 2024
While generative AI is a revolutionary technology that's disrupting industries and transforming business operations, its success depends on data. Data is crucial for AI, as it is the foundation upon which machine learning algorithms learn, are grounded, make predictions, and improve performance over time.
As a result, many CIOs are asking the question: are we bringing our data together and applying the latest AI and best data tools to innovate? A key challenge for customers harnessing generative AI is the ability to access, manage, and activate all types of data, regardless of format.
The rise of generative AI is widely welcomed by data teams. In our recent study, Google Data and AI Trends Report, 2024, 84% of data decision makers believe generative AI will help their organization access insights faster. But there are challenges too, with over 80% of respondents agreeing that the lines between data and AI roles are starting to blur, where many data analysts are now seeking to leverage capabilities that were traditionally reserved for data scientists and vice versa. For example, data analysts need ML for improved insights and data scientists require broader sets of enterprise data to train their models.