▸ AI/LLM · The Decoder
OpenAI's next frontier model, internally codenamed 'Spud,' completed pre-training on March 24, 2026, and is now in safety evaluation. Sam Altman described it as a 'very strong model that could really accelerate the economy,' while Greg Brockman called it 'two years of research' with a 'big model feel.' Polymarket assigns 78% probability of release by April 30.
The bottom line: Marketing data teams should prepare for potential benchmark gains in coding and tool use that could accelerate AI-powered campaign automation and analysis workflows.
▸ Data Engineering · Yahoo Finance
At Qlik Connect 2026, Qlik announced a major expansion of agentic execution into data engineering. New capabilities include declarative pipelines that let engineers describe outcomes in natural language, real-time routing for agentic processes, Open Lakehouse Streaming, and a suite of AI agents including Data Product, Data Quality, and Analytics agents. The release also introduces Trust Score for measuring data product reliability.
The bottom line: Marketing data teams can now build and modify data pipelines using natural language prompts, potentially cutting pipeline development time while maintaining governance controls required for AI workloads.
▸ MarTech/AdTech · MarTech
The IAB's State of Data 2026 report reveals that 75% of buy-side leaders say core measurement approaches like attribution analysis, incrementality tests, and marketing mix models underperform. About 50% of marketers are already scaling AI in measurement, with 69% of analytics teams leading adoption. However, trust remains a barrier, with half anticipating legal or accuracy challenges.
The bottom line: Marketing data professionals should prioritize building hybrid measurement frameworks that combine MTA, MMM, and AI to cross-check outputs, as single-method approaches are losing credibility in the boardroom.
▸ Emerging Tools · SiliconANGLE
Qlik unveiled a new Predict Agent that lets users ask forward-looking business questions in natural language. The agent automatically builds machine learning models, generates forecasts, and interprets results. A companion Automate Agent can trigger complex workflows based on predictions, such as automatically creating procurement workflows when supply chain problems are forecast.
The bottom line: Marketing teams can now access predictive analytics without data science expertise, enabling faster scenario planning and automated responses to forecast-triggered events.
