Across the enterprise landscape, an overwhelming sense of urgency surrounds Artificial Intelligence. Leaders read headlines about autonomous agents and generative tools, then immediately task their teams with deploying cutting-edge models. Yet in boardroom after boardroom, the outcome is often the same: expensive pilot programs stall, algorithms hallucinate or produce conflicting metrics, and executive confidence collapses. To unlock actual enterprise value, organizations mus

For non-profits, higher education, and healthcare foundations, Blackbaud’s Raiser’s Edge (RE NXT) is the undisputed center of gravity for donor data. But as Artificial Intelligence reshapes how businesses operate, many fundraising leaders are asking a critical question: Is our Raiser’s Edge data stuck in the past, or can we leverage it with modern AI? The short answer: You absolutely can. But getting there requires understanding the difference between Blackbaud’s internal too

Every week, I speak with executives trying to map out their technology and AI strategies for 2027. A common question I hear is, "Should we use AI for this?" While Generative AI is incredibly powerful, it isn’t a silver bullet for every operational bottleneck. Sometimes you need an LLM; sometimes you need a predictive dashboard; and sometimes, you just need to buy an existing software license. To help our clients avoid costly missteps, we use a simple framework to determine wh

Even though DIY for AI is getting easier and easier, it's also getting more and more complicated.

Intro to the 'growing' growing gap problem, compounding and investments The human impact: workforce and education, org structure changes, aging workforce and the trickle down effect The dichotomy of AI gains: efficiency vs. disruption, solo unicorns, under indexing of human skillsets, the mundanity of excellence Our collective responsibility and activism: why AI regulation might look like car regulations, our values and action to affect the fine AI line we are curren

For decades, the standard in residential real estate analytics has been the static dashboard. Asset managers and property teams have spent countless hours exporting data from property management systems (PMS) to hunt for insights. Today, the frontier has shifted toward Agentic AI—systems that not only aggregate data but actively synthesize it, detect variances, and generate executive-ready performance reports. By leveraging Google’s Gemini and NotebookLM, real estate firms

As your team adopts AI, the biggest question on any CTO’s mind is simple: Is our proprietary data safe? When rolling out generative AI like Gemini to multiple team members, protecting your intellectual property, customer data, and internal communications isn't just an IT preference—it's a compliance mandate. Here is what you need to know to ensure your Gemini deployment is secure, private, and leak-proof. 1. Choose the Right Subscription (The Golden Rule) The single most impo

This blog will focus on the how and the why of using analytics and AI to better price residential real estate units.