Artefact Value By Data

How to Build an Agentic Enterprise: The 4Ps of AI Transformation

How can organizations move from experimentation to true scale with generative and agentic AI? Over the past two years, many companies have launched promising pilots only to hit a wall when trying to operationalize them. The difficulty isn’t accessing technology anymore. Today, the challenge lies in scaling AI responsibly and effectively across the organization. To do that, companies must look beyond individual use cases and focus instead on holistic transformation. There are four critical dimensions that determine success: Processes, People, Platform, and Position: the 4Ps of Agentics.

The Race to Black Friday: Why timing is the new performance metric

Originally coined by Philadelphia police in the 1950s to describe chaotic post-Thanksgiving crowds, “Black Friday” later gained a positive spin as the day stores turned “in the black” financially. Today, it marks the start of the holiday shopping season, both in stores and online.

Enriching the DIY experience: How ADEO uses AI to connect content and knowledge

Assortment optimization is a critical process in retail that involves curating the ideal mix of products to meet consumer demand while taking into account the many logistics constraints involved. The retailers need to make sure that they offer the right products, in the right quantities, at the right time. By leveraging data and consumer insights, retailers can make informed decisions on which items to stock, how to manage inventory, and what products to prioritize based on customer preferences, seasonal trends, and sales patterns.

The Long View: Treating Data Investments Like Real Estate Assets

Real estate in the Gulf is moving faster and at a larger scale than at any point in the last decade. In Dubai, more than 43,000 property deals worth AED 115 billion were recorded in Q1 2025, with nearly 70% off-plan — evidence of liquidity but also exposure to delivery and handover risks.

Grounding AI Agents: Why Clean Data Is Non-Negotiable

In this article, we explore why marketers – despite having more data than ever – struggle to turn it into actionable insights, and how AI Agents promise to deliver autonomous, high-value recommendations. Yet there’s a hidden barrier few talk about: inconsistent naming conventions. Without a standardized structure, AI Agents can’t reliably read, unify, or optimize your campaign data. Daniel shows why grounding your AI Agents in clean, enforceable data is critical for cross-channel analysis, faster insights, and confident budget decisions.

MotherDuck Explained: How the Next-Gen AI & Analytics Solution Fits Into Your Data Stack

MotherDuck extends DuckDB's analytical performance to the cloud with collaborative features, delivering 4x faster performance than BigQuery and cost savings over traditional data warehouses through serverless, pay-per-use pricing. Following the announcement of MotherDuck’s new European cloud region, we were impressed by its performance and attractive pricing. MotherDuck can already be integrated into your gold layers in order to accelerate the serving of data use cases while saving costs at the same time. See performance benchmark.

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