VOLUME 1 - ISSUE 12 ~ april 9, 2024
How is your data strategy? In this edition of the “CIO Two Cents” newsletter, I take a look at how Gen AI technology is revolutionizing data management in the workplace. Read on for insights from me—Yvette Kanouff, Partner at JC2 Ventures—into what is on the mind of CIOs at this moment in time.
The JC2 Ventures team (John J. Chambers, Shannon Pina, John T. Chambers, me, and Pankaj Patel)
As we all know, CIOs are actively exploring how Gen AI can revolutionize various business and IT domains. Initially focused on code generation, the application of Gen AI has expanded into new domains such as escalation management, security automation, and enhancing internal communications at an unprecedented pace. In a recent CIO article, Sunny Bedi, the CIO of Snowflake, shared that he foresees a future in which all employees work closely with AI copilots to assist with actions like coordinating internal communication and prototyping innovative ideas. One area that I am particularly interested in lately is the ability to use generative AI to help optimize the work of an organization’s data teams and their development processes.
A key area starting to undergo transformation through Gen AI is the organization's data management and processing workflows. Traditionally, extracting valuable business insights from data involves a multi-step process: aggregating data across different systems into a data warehouse, transforming, testing, and documenting the data, and finally, creating dashboards or reports in collaboration with business teams. The complexity and sheer number of steps involved make this process lengthy and resource intensive. Gen AI is set to accelerate and automate these steps within ETL (Extract, Transform, Load) frameworks, data warehouses, and analytics platforms.
The emergence of AI assistants tailored to specific stages of the data management process is already noticeable. For instance, ThoughtSpot introduced Sage to simplify report generation, while Salesforce unveiled Einstein copilot to enhance data analysis in Tableau. For other steps in the process, new AI copilots have started emerging. For example, there is DataPilot by Altimate AI, a company that is leading the pack in this area with hundreds of enterprises quickly adopting their solution to fast-track their data development efforts. These AI assistants are designed to automate tasks such as data transformation, documentation, testing, as well as enable AI-enhanced collaboration among data and business teams.
I see a significant amount of cost savings, time savings, and quality improvement for businesses with the integration of Gen AI into the data landscape. The early results are very exciting. I look forward to seeing the technologies and implementations evolve. Maybe this can free up our time to focus on ever-changing AI governance, security controls, compliance, and support for AI applications—but that’s another topic altogether.
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