DoT Blog

  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...

  Logo image courtesy of Boomi Boomi’s annual conference, Boomi World 2025, wrapped up in Dallas this May, and it brought with it more than just shiny slides and enthusiasm. The data management company laid out a series of announcements that signal its evolution from a pure-play iPaaS (Integration Platform as a Service) provider to a more AI-infused automation and connectivity platform. While the buzz was, of course, clearly around AI, Boomi also made notable strategic moves in data integration, API governance, and cloud partnerships, all of which deserve attention from enterprise IT and business stakeholders trying to modernize their integration architecture. In this regard, as Steve Lucas, Chairman and CEO at Boomi, mentioned:  “Today’s enterprises are overwhelmed by digital fragmentation and data sprawl; the future belongs to organizations that can intelligently connect everything and automate anything — and Boomi is THE platform that makes it happen. With these innovations...

  A couple of days ago, IBM announced its intent to acquire DataStax , a lead provider of real-time artificial intelligence (AI) applications built on open-source Apache Cassandra . The acquisition aligns with IBM's growing focus on reinforcing its competitiveness in AI and data management, particularly as it seeks to enhance its Watsonx AI platform .  The move signals IBM's commitment to leveraging open-source technologies for enterprise AI applications, aiming to reinforce its position in the AI-driven data management landscape. Why is IBM acquiring DataStax? IBM’s acquisition of DataStax seems to be part of the company’s strategy to bolster Watsonx, IBM’s AI and data platform, by enhancing its ability to process and manage unstructured data.  With DataStax’s expertise in providing real-time AI applications and scalable data solutions, IBM aims to provide businesses with improved tools for handling vast amounts of data securely and efficiently. While unstructured data—...

  In recent years, the term “AI agent” has gained significant attention within the technology industry, as well as the broader public discourse. While concepts like artificial intelligence (AI) and machine learning have become increasingly familiar, AI agents represent a quite distinct and evolving area of development in the AI sector. But what the heck are they? Well, the purpose of this article aims to provide a clear, foundational understanding of what AI agents are, where they come from, and why they are considered a crucial step forward in artificial intelligence research and application. It will also discuss current uses, potential benefits, key technical underpinnings, and the societal and ethical considerations that come into play as AI agents become more integrated into our infrastructures and daily lives. Defining AI Agents Image by geralt ( Pixabay ) A First Definition Let us start with a basic definition. So, in essence, AI agents are autonomous software entities, des...