There is always a lot that we can learn from successful technology and software developments. There is also a lot we can learn, unfortunately, from technology and software development “failures”. In analyzing over twenty well documented and publicized failures, one fundamental issue came through loud and clear. A major mismatch between the enterprise data representations and processes, and the vendor’s data representations and processes. There is a pretty straightforward way to address this situation.

Yes, anything you say to AI can be used against you, including things that you thought were deleted. Yes, hitting the delete button or key really does not do anything. Let me translate. Public facing AI and associated models are “dangerous”. EAI – (Enterprise Augmented Information) – AI within the boundary of your Enterprise is the answer. Please listen. And we can help.

What is the oil that makes the artificial intelligence world run? Data. Data infrastructure is the key to moving away from guessing to true usefulness. Data infrastructure is made up of two parts – the actual technology, and the data itself. Billions are being spent on the technological side. The data itself is being starved. Why? Because it is hard. We will describe the five transformations needed to make data AI ready.

This broadcast is a commentary. One line I am quoting – “AI models should treat content taken from social media and the internet as untrustworthy sources.” Large Language Models (LLM) ARE the issue, and there is no solution to this – what is public is subject to manipulation. What is the answer to this issue? EAI – Enterprise Augmented (Almigated) Information. Also known as Small Language Model.

Enterprise architecture (EA) and Business Architecture (BA) certifications are often seen as strategic moves - intended to elevate professional credibility, further organizational maturity, and equip leaders with frameworks and methodologies to drive business optimization and transformation. But, unfortunately, most certifications do not live up to these expectations.

The hype around Artificial Intelligence (AI) continues to accelerate. Billions are being spent in industry, by investors, and by you and I. Beyond FOMO (Feal Of Missing Out), where is all of this going?

This Broadcast provides some valuable insight and questions you need to ask, as you take this rollercoaster ride. Fasten your seat belt and be sure you also have a tight harness.

The adoption of Artificial Intelligence (AI) to develop Enterprise Architectures (EA) is attempting to transform the field, but it comes at a cost: a noticeable decline in traditional EA competency and growing skepticism among stakeholders as to the worth of Enterprise Architecture. Contemporary Enterprise Architects expertise is no longer just a nice-to-have - it is a strategic imperative for any organization seeking to thrive in an AI-driven world.

This is a post from Peter Kinev that I will be embellishing a bit. Somehow, over time, Enterprise Architecture has developed a language of its own. A language that seems more designed to deflect than to inform. I think it is time we change the narrative.