#73: The Enduring Power of Data Storytelling in the Generative AI EraðŸ§
Hello,
This newsletter will take you about 4 minutes to read.
I. Spotlight: The Enduring Power of Data Storytelling in the Generative AI EraðŸ§
Today, generative artificial intelligence tools like ChatGPT and Gemini perform an impressive set of tasks with just a few simple prompts. They interpret even poorly formed user questions, identify deep domain insights from data, and share answers as well-structured recommendations. Increasingly, these exchanges are getting conversational, using text-to-speech AI technology.
AI can answer questions off the bat, like a (true) executive assistant. Not surprisingly, that has led people to question whether the visual presentation of information is relevant anymore — and even to sound a death knell for visualization dashboards and data stories.
Not so fast.
Yes, the latest advances in generative AI can help people automatically discover hidden patterns from numbers and unstructured data such as text, audio, or video. It is now possible to translate insights into business recommendations, almost at the level of a domain expert. This eliminates a lot of manual effort and inefficiencies involved in creating and consuming data visualizations. However, trying to entirely do away with the visual display of information is a costly mistake. There is a strong case for deploying conversational intelligence while retaining the magic of visual narratives in certain critical scenarios.
Here, I’ll share a simple yet powerful framework to help leaders and their teams understand four key decision-making situations and how to pick the right information presentation tool for the job. We’ll see where AI is ready to fully automate information presentation and where it can play only a secondary role in enabling data teams.
II. Industry Roundup:
1. Article: Why Your Company Needs Data-Product Managers
06 minutes | Â HBR | Thomas H. Davenport, Randy Bean, and Shail Jain
Companies often struggle to deploy data scientists' models into production, leading to the adoption of data products for reusable, analyzable datasets. Successful implementation requires a new role: the data product manager. This role coordinates development and deployment, managing diverse teams without needing deep technical expertise. They are key to leveraging data for significant business benefits.
->Â Read the Article
2. Article: A New Survey Of Generative AI Shows Lots Of Work To Do
05 minutes | Forbes | Tom Davenport
A survey involving 334 chief data officers reveals excitement but slow preparation for generative AI in organizations. While 80% believe it will transform their companies, only a minority have begun experimenting or deploying it. CDOs recognize the need for data strategy in leveraging generative AI but often lack the necessary data foundation. The survey suggests a need for increased focus and investment in data preparation and understanding of generative AI to capitalize on its potential fully.
->Â Read the Article
III. From my Desk:Â
1. Announcement: Kicking off my Column with MIT-SMR
01 min | MIT Sloan Management Review
I'm happy to share that I’ve begun contributing to a quarterly column in the MIT Sloan Management Review (MIT SMR) on enterprise value from data and AI. MIT SMR offers an amazing platform at the forefront of business and technology to spark conversations on key industry trends, innovations, and enterprise applications. Stay tuned for insightful content and I look forward to your feedback as always!
Thank you for subscribing and reading the newsletter. I appreciate your attention,
Ganes.
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I’m Ganes Kesari. I publish ‘Data-Driven Future’ to help understand how data shapes our world, explore key trends, and explain what they mean for you today. I speak and write to demystify data science for decision-makers and organizations.
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