DoT Blog

  Logo Image Courtesy of Oracle Oracle’s latest announcement doesn’t sound like just another product release; it’s a statement. With its new AI Data Platform, Oracle is telling the enterprise world that the time for siloed data and experimental AI is over; we’re now entering an era where AI needs to live inside business data, not beside it. Unveiled at AI World 2025 , the Oracle AI Data Platform aims to unify data management, AI model integration, and automation, all within a single environment. According to the company, it combines data lakehouse and analytics capabilities with built-in generative AI tools, vector indexing, and an “agent hub” for building intelligent applications. So, the message is clear: Oracle wants to make AI an operational layer across business workflows, not an add-on.   From Data Storage to Intelligence Activation For years, enterprises have struggled to connect their data systems to AI models efficiently. Oracle’s approach focuses on bringing AI to t...

Logo Image Courtesy of OpenAI When OpenAI announced its partnership with Broadcom to design custom AI chips, it felt like another line being drawn in the sand of the AI hardware race. For years, OpenAI has relied heavily on Nvidia ’s GPUs to power its models, along with more recent deals involving also AMD , but this new collaboration signals something different; it’s a step toward vertical integration, toward owning more of the stack, going from algorithms all the way down to silicon. Let’s think about the scale here: the plan is to eventually deploy ten gigawatts of custom accelerators. To put that in perspective, that’s the output of around ten nuclear reactors. The numbers aren’t just flashy; they tell us how OpenAI sees its future, one where AI models demand unprecedented amounts of computers and where renting time on someone else’s chips isn’t enough. And the logic makes sense; Nvidia may be the king of GPUs, but relying on one vendor for something as strategic as compu...

  Logo Image Courtesy of IBM Business intelligence (BI) has always carried a big promise: giving organizations a way to clearly see the status of the business, to make sense of their data, and to ground decisions in facts rather than gut instinct. Over the years, we’ve moved from static reports to interactive dashboards and from dashboards to self-service tools, and yet, despite the evolution, the underlying complaint has remained consistent: BI adoption rarely matches the hype. Tools are powerful, but some users still struggle to trust, interpret, and act on the insights they generate. IBM’s recent launch of Watsonx BI introduces a new frame: BI not as a tool but as an agent. This subtle linguistic shift is meaningful; instead of thinking about BI as a system, you go with running a report and building a dashboard—the vision of BI coming to you, responding conversationally, surfacing trends proactively, and explaining not just “what” but “why” and “what next.” If dashboards were t...

  Image by Negative Space  (Pexels) Ok, so generative AI continues to dominate headlines, but what’s more telling is how quickly it’s cementing itself in real business strategies. Well, according to a recent Yahoo Finance report , the global chatbot market is expected to hit $15.5 billion by 2028, driven largely by the ubiquity of conversational AI tools. The numbers themselves are striking, but even more so is what they represent: a shift from AI as an “innovation experiment” to AI as a structural pillar of modern organizations. Customer service, sales enablement, and education are just a few of the areas being reshaped by chatbots and conversational platforms. In many ways, the chatbot market is just the tip of the iceberg. Recent surveys suggest that 95 percent of U.S. companies already use generative AI in some capacity, and production-level use cases have doubled in a short timeframe. We no longer talk about cautious pilots in innovation labs; we’re seeing generative AI t...

  Image by geralt (Pixabay) When I first read the Light Reading article “ AI looks increasingly useless in telecom and anywhere else,”  I had to pause. Not because the argument was new—I’ve seen plenty of skepticism about AI—but because of the tone. It doesn’t just question AI’s utility, but it paints a picture of a lobotomized society , drifting into an “AI psychosis” where people see machines as sentient companions. Boy, it’s an arresting way to start, but also, perhaps, too convenient a metaphor. The author compares our intellectual reliance on AI to muscles wasting away from disuse, citing early studies that show people who lean too much on generative AI may grow less critical, less precise, and even a little sloppy. It’s a provocative analogy, but one that, in my view, overreaches. Yes, there are legitimate concerns: copy-pasting AI outputs without scrutiny is a real problem, and treating chatbots as friends, or worse, as oracles, can be dangerous, but to equate this with...

  Logo image courtesy of ThoughtSpot Today, analytics is not about data, reports, and dashboards anymore. It is not even about insights. It seems ThoughtSpot is aiming for something bigger: agents that think, act, and close the loop, all on your data stack. If the last few years in analytics were about self-service and natural language, 2025 is clearly about something new: AI agents. Not just tools that explain business, but ones that act on its behalf, and ThoughtSpot, the company that once positioned itself as the Google of BI, is now doubling down on that vision with the launch of its Agentic Analytics Platform. This is not just rebranding. It seems to be a strategic repositioning, backed by AI agents, real-time cloud-native architectures, and native integrations, especially with Databricks and Snowflake . It is also a signal that ThoughtSpot wants to move way beyond charts and dashboards and instead become a living, breathing part of the new enterprise decision loop. ...

  Logo image courtesy of SAP As SAP’s Sapphire 2025 conference wrapped up in Orlando, it was with a message that’s loud and clear: Business AI isn’t coming; it’s already here, and SAP wants to be the platform that makes it tangible, safe, and enterprise-grade. From major announcements around AI partnerships and cloud data orchestration to real-time intelligent applications and developer-friendly innovations, SAP didn’t just talk about their view on digital transformation; they gave it structure, context, and an operational plan. The question now is, are enterprises ready to execute? So, let’s unpack what happened at Sapphire 2025, beyond the surface gloss, to understand what SAP’s AI-first future means for business leaders, developers, and the broader enterprise ecosystem. AI as the Operating System for the Enterprise So, the core theme this year?  AI not as a bolt-on, but as an operating system for how enterprises run. And it appears this is not just marketing. It’s backed b...