While investment in enterprise AI continues to surge, true systemic workflow transformation remains out of reach. The core barrier is fragmented, unowned business context that keeps AI locked in operational silos. This paper explores why context is the missing piece of enterprise AI infrastructure and provides the strategic roadmap to fix it.
Topic: Business Insights
The Agentic Enterprise: Own vs Rent vs Compose
AI success depends on the right architectural decisions, not just the right models. This white paper introduces a practical framework for designing future-ready, agentic AI systems across retail, manufacturing, pharma, and CPG. Learn how to strategically navigate ownership across the entire AI stack, minimize vendor lock-in, and turn proprietary workflows and context into compounding business value.
Automation vs. Augmentation: Where Enterprise AI Investment Actually Sits
Enterprise AI is moving beyond experimentation. Based on joint research by MathCo and HFS Research, this article explores the growing focus on process intelligence, the trust gap between automation and augmentation, and why transparency, explainability, and human-centered AI will determine enterprise AI adoption at scale.
Four Compounding Constraints Preventing Enterprise AI from Scaling
As AI adoption accelerates, many organizations continue to struggle with enterprise-wide impact. Explore the structural constraints identified through MathCo and HFS Research that reveal why enterprise context is becoming the defining factor in AI scale.
Fund the Context Layer and Close the 2.5x AI Ambition Gap
AI transformation requires more than models, it requires enterprise context. Our latest report, developed in collaboration with HFS Research, reveals why AI initiatives stall and how organizations can scale AI to drive smarter decisions and measurable business impact.
Reimagining Customer Intelligence: The Role of Identity Resolution in AI-Driven C360
Discover how Always-On Marketing Mix Modeling is transforming CPG marketing with continuous measurement, real-time optimization, unified retail media analytics, and AI-powered decision-making. This white paper explores how modern enterprises are using marketing mix modeling to improve ROI, accelerate budget decisions, and drive sustainable growth in an increasingly dynamic and data-driven marketing landscape.
The Shift to Always-On Marketing Mix Modeling: Continuous Measurement for Marketing Leaders
Discover how Always-On Marketing Mix Modeling is transforming CPG marketing with continuous measurement, real-time optimization, unified retail media analytics, and AI-powered decision-making. This white paper explores how modern enterprises are using marketing mix modeling to improve ROI, accelerate budget decisions, and drive sustainable growth in an increasingly dynamic and data-driven marketing landscape.
Winning the AI Shelf: How AEO & GEO Are Redefining CPG Discovery
AI is reshaping how consumers discover and choose products, shifting decisions from search engines to AI-driven recommendations. For CPG brands, this creates a new battleground where visibility depends on AEO, GEO, and AI-readable product data. Brands that fail to appear in AI-generated answers risk losing relevance at the moment of decision. This article explores how AI Commerce Intelligence helps CPG enterprises measure visibility, understand perception, uncover competitive gaps, and optimize content across AI platforms. The future of digital shelf success is no longer about ranking in search, but being recommended by AI.
From Static Models to Living Forecasts – MathCo’s AI Approach to Pharma Decision-Making
MathCo enables AI and GenAI-driven pharma forecasting with unified data, scenario planning, and transparent insights for faster, confident decisions.
Engineering 2.0: The Strategic Shift to AI-Powered Data Foundations for CPG
CPG firms are data-rich but often slowed by fragmented systems and manual engineering. Engineering 2.0 introduces AI-powered data foundations that automate pipelines, improve data quality, and accelerate insights. By embedding intelligence across the lifecycle, it enables faster decisions, scalable analytics, and measurable business impact.