5 ways data scientists can prepare now for genAI transformation



For example, Salesforce recently announced Industries AI, a set of pre-built customizable AI capabilities that address industry-specific challenges across 15 industries, including automotive, financial services, healthcare, manufacturing, and retail. One healthcare model provides benefits verification, and an automotive model provides vehicle telemetry summaries.

Regarding AI agents, Abhi Maheshwari, CEO of Aisera, says, “AI agents elevate LLMs by engaging in reasoning, planning, decision-making, and tool usage, handling tasks like CRM and ERP transactions autonomously. These agents simplify data tasks usually done by data analysts, including cleaning, exploratory data analysis, feature engineering, and forecasting.”

These two trends illustrate a secondary shift in the data science role—from wrangling data and developing machine learning models to focusing on leveraging AI agents, investigating third-party models, and collaborating with citizen data scientists on applying AI, machine learning, and other data science capabilities.

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