How Data and ML Priorities Are Changing in Generative AI Programs Early generative AI programs often prioritized access to a capable model and a visible pilot. As enterprises move toward production, data and ML…
Generative AI Programs: Data and ML Trends Leaders Should Watch Generative AI programs can stall when leaders focus on model selection while the data, machine learning, and operating disciplines around the model remain…
Emerging Data and Machine Learning Trends Shaping Generative AI Programs Enterprise generative AI programs are moving beyond the question of which model can generate the best response. The harder decisions now sit in…
What AI-Driven Data Analysis Adds to Generative AI Programs Generative AI programs can answer questions and summarize documents, but many enterprise users need something more valuable: help connecting information to a…
Using AI for Data Analysis Inside Governed Generative AI Programs Using AI for data analysis can make enterprise information easier to interrogate, but governance becomes more demanding when the system can read…
AI in Data Analysis: Where It Fits in Enterprise Generative AI Programs Enterprise generative AI programs often begin with search, summarization, or copilots, but the harder business question is how AI in data analysis…
How Data for Machine Learning Is Evolving Around Decision Support Needs Data for machine learning is evolving around decision support needs because organizations increasingly care less about producing a score and more…
Emerging Data Trends for Machine Learning and Trusted Decision Support Emerging data trends for machine learning are increasingly shaped by one requirement: decision support must be trustworthy when conditions change.…
Data for Machine Learning: Trends Shaping Better Decision Support Data for machine learning is changing as organizations shift from building models around whatever historical data is available to designing data around…
When GenAI Tools Are Ready to Move From Pilot to Scalable Deployment GenAI tools are ready to move from pilot to scalable deployment when the organization can manage failure as deliberately as it demonstrates success.…