This article was based on the interview with Eric Madariaga of CData by Greg Kihlström, MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
Data connectivity plays a crucial role in simplifying AI adoption for organizations. In a recent podcast, the speaker from CDATA highlighted the importance of making all systems within an organization speak the same language, which is essential for structuring data for consumption by AI. By using connectivity technologies like CDA Connect Cloud, organizations can consolidate their data sources and create a common interface for AI implementation.
One key benefit of data connectivity is the ability to layer AI technology on top of the connected systems. For example, CDATA’s product allows for text to SQL interfaces, enabling users to ask questions in natural language and have the system translate them into SQL queries that retrieve data from various systems. This seamless integration of data sources not only simplifies the process of accessing and analyzing data but also sets organizations up for success in AI implementation.
However, despite the potential benefits of AI adoption, many organizations face challenges in validating the outputs of AI models. This is especially true for predictive models that evolve over time and require continuous validation to ensure accuracy and reliability. To address this challenge, organizations need to have mature data systems in place that allow for ongoing testing and validation of AI outputs against historic data.
The podcast also touched on the growing maturity gap between organizations that are leading in AI adoption and those that are struggling to keep pace. This gap may have implications for the industry as a whole, with organizations that lag behind potentially falling further behind as technology continues to evolve. It is crucial for organizations to prioritize data connectivity and invest in building mature data systems to bridge this gap and stay competitive in the AI-driven marketing landscape.
In conclusion, data connectivity plays a vital role in simplifying AI adoption for organizations. By creating a common language for all systems and integrating data sources effectively, organizations can optimize their data operations for AI implementation. With clear goals, accessible data, and ongoing validation processes, organizations can harness the power of AI to enhance their marketing strategies, improve customer experiences, and drive business growth.
