AI Prepared Daily — April 17, 2026

▸ AI/LLM · The Decoder

OpenAI's 'Spud' Model Enters Final Phase, April Launch Expected

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.

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▸ Data Engineering · Yahoo Finance

Qlik Launches Agentic Data Engineering With Declarative Pipelines

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.

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▸ MarTech/AdTech · MarTech

IAB Report: 75% of Marketers Say Measurement Systems Falling Short

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.

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▸ Emerging Tools · SiliconANGLE

Qlik Introduces Predict Agent for AI-Powered Forecasting

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.

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In Other News

Qlik Partners With ServiceNow to Power AI-Driven Workflows — For marketing ops teams using ServiceNow, this integration creates a direct path from enterprise data insights to automated workflow execution, reducing the latency between analytics and action.Business Wire →
April 2026 Sets Record: Nine Major LLM Releases in Two Weeks — Model switching costs are falling as standardized formats like MCP enable teams to swap models with a config change, meaning marketing teams should build for model portability rather than betting on a single provider.Fazm Blog →
Zero-Click World: 60% of Searches Now End Without Website Visits — Marketing data teams must rebuild measurement frameworks around incrementality testing and first-party data rather than relying on click-based attribution that increasingly misses how customers actually discover brands.Mervyn Chua →
Multi-Touch Attribution Adoption Hits 41% But Accuracy Lags — The competitive advantage window for building integrated measurement capabilities is 2026-2027. After that, the approach becomes table stakes rather than a differentiator.Digital Applied →