Over the course of 2025, we published a lot of content exploring the ideas, challenges, and opportunities shaping modern business technology. As we wrap up the year, we felt a few of those topics were worth revisiting. So, at the risk of issuing the dreaded holiday montage episode — you know, the one that shamelessly recaps earlier material — we decided to look back at the ideas that resonated most with our readers. But, rest assured that this isn’t just a greatest-hits reel for the sake of nostalgia.
Instead of putting together more of a traditional top-10 list, this review highlights the top-rated blog article from each month in 2025. Taken together, these highlighted articles offer a useful snapshot of how quickly key topics like AI, data platforms, and modernization evolved over the course of a very busy technology year. When you line these posts up month by month, the pace of change is pretty staggering, and that’s exactly why we felt this kind of recap was worth doing.
January: Unlocking the Power of SAP Data with Microsoft Fabric
It’s probably no surprise that the year kicked off with a strong focus on data. As organizations got more serious about AI adoption in 2025, many quickly realized that success starts well before models and copilots. It starts with getting the data estate in order and putting the right platform in place to support what comes next.
This post resonated because it went beyond simply moving SAP data from point A to point B. It explored how Microsoft Fabric brings together everything needed to collect, transform, and enrich enterprise data, and then take the next steps with analytics, data science experimentation, and even MLOps pipelines. For many SAP customers, this was a practical look at how to turn long-trusted operational data into something that could actually power AI-driven use cases. In hindsight, it was a fitting way to start the year. Before AI can deliver real value, the data and the platform behind it have to be ready.
February: SAP BDC and the Future of All-in-One Data Platforms
February picked up right where January left off. With data firmly in the spotlight, SAP made a major move by announcing SAP Business Data Cloud (BDC), signaling a clear push toward more unified, all-in-one data platform experiences. It was one of those announcements that immediately sparked comparisons and conversations across the ecosystem.
This post struck a chord because it didn’t just recap the news. It put SAP BDC in context alongside other modern data platforms like Microsoft Fabric, Google BigQuery, and Snowflake, and explored what “all-in-one” really means in practice. For many organizations, the question wasn’t which platform was better, but how these platforms are converging around similar goals: simplifying data access, reducing fragmentation, and creating a stronger foundation for analytics and AI. February reinforced a theme that would keep coming up all year. The data platform is no longer just infrastructure. It’s becoming a strategic layer that shapes how quickly businesses can move.
March: SAP & Microsoft Copilot Studio: UX Reimagined
By March, the conversation started to move up the stack. This month, we turned our attention to how users actually interact with all of this information in their day-to-day work. That’s where agents and copilots entered the picture, and where the idea of user experience took on a whole new meaning.
This post explored how Microsoft Copilot Studio can be used alongside key systems like SAP to completely rethink how business processes are executed. Instead of forcing users to navigate complex screens and workflows, copilots allow people to interact with line-of-business applications using natural language, right in the flow of work. The real shift isn’t just about a nicer interface. It’s about empowering users, reducing friction, and reshaping processes around how work actually gets done. March made it clear that as agents mature, UX isn’t just being improved. It’s being reimagined.
April: SAP Analytics Glow-Up: Replacing BOBJ and Lumira with Power BI
April pivoted the conversation towards business intelligence (BI), and it definitely struck a nerve. We were hearing from a lot of customers who were taking a hard look at their BI portfolios and asking a very reasonable question: why are we maintaining so many reporting tools? Between SAP BOBJ, Lumira, and various third-party platforms like MicroStrategy, BI sprawl had become expensive, complex, and hard to govern.
This article resonated because it focused on simplification. It walked through how Power BI makes it possible to consolidate analytics content into a single, modern BI platform without sacrificing depth or flexibility. For SAP customers, that meant a clear path away from legacy tools. For others, it was an opportunity to reduce licensing costs and streamline how insights are delivered across the organization. April’s takeaway was simple and timely. A cleaner BI portfolio isn’t just easier to manage, it’s easier for the business to actually adopt and use.
May: Do More with Less: Building the Business Case for AI Automation
By May, the AI conversation needed a bit of a reality check. Interest was high, expectations were even higher, and many leaders were left wondering where to actually start. This article took a deliberately pragmatic look at AI automation, focusing less on hype and more on how to build a business case that would hold up under real scrutiny.
Rather than assuming AI belongs everywhere, this post walked through where to look for meaningful automation opportunities, what factors really matter when evaluating them, and how to weigh cost, complexity, and impact. The goal was simple: help organizations decide when AI automation makes sense and when it doesn’t. In a year full of big promises, May’s message resonated because it helped teams answer the most important question of all. Is the juice actually worth the squeeze?
June: Rewiring the Enterprise: A2A, MCP, & the Future of Agentic AI
By June, the conversation around agents shifted from individual copilots to something much bigger. This post looked ahead to a future where agents don’t just assist users, but operate as first-class citizens within the enterprise, working alongside people, systems, and even other agents.
What made this topic resonate was the focus on emerging standards like A2A and MCP, and how they lay the groundwork for agent adoption at scale. These standards point toward a more open, interoperable world where agents can communicate, coordinate, and safely take action across complex organizational landscapes. June offered a glimpse of what’s coming next. A future where agentic AI isn’t bolted onto systems as an afterthought, but woven directly into how modern enterprises are designed and operated.
July: Burn the Ships: Reflections on Enterprise Software's Big Bet on Agentic AI
If June was about the mechanics of agentic AI, July zoomed out to look at the mindset shift happening across the enterprise software landscape. This post explored how Microsoft and other major vendors are no longer treating agents as experimental features, but as a core part of their long-term product strategy.
Satya Nadella's “burn the ships” theme captured a growing reality. Enterprise software leaders are making decisive bets on widespread agent adoption, rethinking application architectures, user experiences, and even business models around an agent-first future. July’s takeaway was hard to miss. Agentic AI isn’t a side project or a passing trend. It’s becoming the lens through which the next generation of enterprise software is being built.
August: From Tribal to Transferable: How Fabric Data Agents Capture Expert Knowledge
August shifted the conversation from technology capabilities to people and knowledge. This post introduced a new class of data agents built on Microsoft Fabric, designed not just to answer questions, but to learn how an organization’s data should be analyzed and interpreted.
What made this idea resonate was the focus on institutional knowledge. Instead of relying on a small group of experts who “just know” how the numbers work, Fabric Data Agents make it possible to train agents the same way you would onboard a new analyst. Over time, those agents begin to reflect shared business context, assumptions, and best practices. The result is a more transferable, always-on source of insight that helps preserve expertise, reduce bottlenecks, and make critical knowledge available 24x7.
September: Rethinking Best Run Processes: Filling in ERP Processing Gaps
September turned a critical eye toward something many organizations quietly struggle with. Even the best ERP systems are built around standardized, “best run” processes that don’t always reflect how work actually happens on the ground. This post explored how embedded AI is starting to close those gaps.
Rather than forcing businesses to contort themselves around rigid workflows, AI-enabled capabilities make it possible to rethink how ERP and other line-of-business processes operate. Intelligent agents can handle exceptions, adapt to context, and fill in the gray areas where traditional automation falls short. September’s takeaway was a powerful one. When AI is embedded directly into business processes, ERP stops being a system of record and starts becoming a system that actively helps work get done.
October: Bowdark & Backburner Join Forces to Launch BrightOps Labs
In October, we turned the focus inward for a moment and shared some big news of our own. We formally announced our strategic partnership with Backburner Labs and the launch of BrightOps Labs, a move that reflects how we see technology continuing to evolve.
More than a partnership announcement, this post speaks to a larger shift we see happening across industries, especially manufacturing. The lines between information technology and operational technology are blurring fast, and real innovation increasingly happens where those worlds meet. BrightOps Labs was born out of that convergence, bringing IT and OT together to create more immersive, connected experiences from the shop floor to the back office. October marked a milestone, not just for us, but for how we believe organizations will approach technology moving forward.
November: Low-Code Isn’t Dead — It’s Just Getting Smarter
November pushed back on a narrative we’d been hearing more often. That low-code had peaked and was about to be replaced by “real” AI-driven development. Coming out of the Microsoft Power Platform Community Conference, the opposite felt true.
This post recapped several key announcements from PPCC and explored how AI is reshaping low-code rather than sidelining it. Concepts like “vibe coding” point to a future where intent, context, and guardrails work together to dramatically improve the quality of low-code solutions. Instead of widening the gap between pro code and low code, AI is helping bridge it, making low-code more expressive, more scalable, and easier to pair with traditional development practices. November’s message was clear. Low-code isn’t going away. It’s growing up.
December: 10 Ways to Turn Everyday Data into Uncommon Value
December brought the conversation right back to where the year began: data. After a year of talking about platforms, agents, processes, and AI, this post zoomed out and focused on a simple but powerful idea. Organizations are sitting on far more valuable data than they realize, including data that has often been ignored, underused, or written off entirely.
This article resonated because it showed how emerging technologies are lowering the barrier to entry. Modern data platforms, AI-assisted analytics, and intelligent agents are making it easier than ever to extract insight from everyday operational data, even data that wasn’t originally designed for analytics or AI. Ending the year here felt fitting. The tools may be getting more advanced, but the real opportunity is learning how to turn ordinary data into uncommon value.
Closing Thoughts
Looking back across the year, a few themes stand out clearly. We started with data, moved through platforms, agents, user experience, and process transformation, and ultimately circled back to data again, this time with a much broader perspective. What changed along the way was not just the technology itself, but how organizations like yours are thinking about it. AI moved from possibility to practicality, agents shifted from novelty to strategy, and platforms evolved from infrastructure to enablers of real business outcomes.
Taken together, these posts tell the story of a fast-moving year where convergence became the rule rather than the exception. Data, AI, low-code, ERP, IT, and OT are no longer separate conversations. They’re interconnected pieces of the same puzzle. As we head into the next year, the opportunity isn’t just to adopt new tools, but to rethink how work gets done when intelligence is embedded everywhere. If 2025 taught us anything, it’s that the organizations willing to connect these dots thoughtfully will be the ones best positioned for what comes next.
