Gartner’s Post

My headline based on this very insightful article: “Why is AI still waiting for its board-room invite?” Here is my takeaway from the PingCAP “data basement to boardroom” vantage. 🔍 My view The tech-sounding stuff is great, but boardrooms don’t book lunch for “cool ML algorithm demo”. They show up for clear business outcomes: revenue uplift, risk reduction, regulation compliance, sustainability wins. → If we can’t frame AI/data as “here’s how we’ll win or survive”, the board stays put. The data foundation still doesn’t get VIP access. It’s too often a basement mission: IT ops, DevOps, data team hustle. Meanwhile, the board’s looking for “How many new product lines, how many fewer recalls, how many fewer carbon credits?” → Without the data backbone being visible and reliable, the AI/GenAI ambitions look like a flashy side-project. → Data infrastructure must earn trust before the board will invite AI in. The leap from experimentation to scale is still the hard part. Gartner says many AI pilots never scale. Why? Because the foundation wasn’t ready. → As we like to say: “You don’t build a Formula 1 car in the parking lot. You build a chassis that can take it to 300 km/h, then add the turbo.”

If knowledge + experience = wisdom, how do we provide the experience for "AI" to better understand context? What really needs to happen is to solve for how we can move from Artificial Intelligence to Artificial Wisdom.

Gartner Excellent perspective on the necessity of moving past 'demo-ware.' The hardest part of the AI journey is not the model build, but the data governance and operational change management required to scale the impact. Execution dictates value. 👏 #AIStrategy #RealizedValue #DigitalTransformation #Gartner #EnterpriseAI #Execution #ROI

The path from pilot to scaling should be seamless if well planned. Sometimes there is great effort to “make it work” without determining if the capability can be scaled.

Great insightful research paper!

The promise and the reality are still far apart. The massive spending on AI may still take years to provide the ROI promised. At present, the spending and the impact of AI is a drag on jobs and the US economy. If Elon Musk is to be believed, there will be no need for human work in a few years. Without humans and the ability to earn a living, to be productive and contribute, what does the world look like? AI can't solve the really big problems like war and abuses of power. Overpromised and underdelivered?

Congratulations for sure footed growth strategy from AI experimentations to implementations.

Interesting to note customer behaviours that will shape and evolve ground strategies.

Absolutely agree, the transition from AI pilots to tangible business outcomes requires strong alignment between IT and business leaders to drive sustainable value.

Insightful Gartner!!!! AI is moving fast, but the real game changer isn’t more pilots—it’s connecting AI engineering with actual supply chain realities. In manufacturing, value is lost when we chase shiny tech without cross-functional, commercial buy-in. The winners will be those who challenge silos, confront “AI-washing,” and turn talk into measurable results. Who’s ready to disrupt?