
The AI Hype Trap: Why Overblown Promises Backfire
AI and GenAI adoption must make a visible and material positive impact on the business or it’s a waste of money.
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Skip to contentData integration, DataOps, real-time architecture and AI-ready data without the platform theatre. We write about the engineering problems that appear when enterprise data has to move, stay current, remain governed and support real operational outcomes.

AI and GenAI adoption must make a visible and material positive impact on the business or it’s a waste of money.

Manufacturing is all about getting the most out of automation, skilled workforce, and data. Data helps drive the decisions that keep everything running smoothly

No company is immune from the pains of data integration. It is one of the top IT cost items. Companies must get on top of their integration effort.

Operational analytics involves processing and analysing operational data in “real-time” to gain insights that inform immediate and actionable decisions.

Many data teams aren’t aware of the concept of Total Ownership Cost or its importance. Getting it right in planning will save you a massive headache later.

In the modern days of GenAI and advanced analytics, businesses need to bring domain expertise and data knowledge together in an effective manner.

Data must be fresh, i.e. readily available, relevant, trustworthy, and current to be of any practical use. Otherwise, it loses its value.