By Daniel W. Rasmus, Serious Insights

It was a pleasure to correspond with June Zhu, the visionary CEO of ChargerGoGo, to discuss the evolving landscape of mobile charging and the launch of their ambitious new platform, GoGoSpark. As urban environments become increasingly data-driven, Zhu is positioning ChargerGoGo not just as a hardware provider, but as a critical layer of “connected infrastructure” for local venues. 

Our conversation delved into how AI-powered decision support and the distributed charging networks are creating a “post-work” entrepreneurship model, where smart hardware and real-time analytics do the heavy lifting for small business owners.

By Daniel W. Rasmus, Serious Insights

In 2026, enterprise AI will stop behaving like a feature and start behaving like infrastructure. This is the core assertion about the evolution of AI agents from our 2026 State of AI: Observations and Recommendations Report, which was sharply reinforced this week by a press release from nexios.ai. That shift isn’t just about more AI in more places. It’s about organizations moving from using models to operating with intelligence. The moment AI becomes infrastructure, with all the associated debt, drift, audit trails, and politics that infrastructure implies, it also becomes fundamental to how an organization works.

By Daniel W. Rasmus, Serious Insights

The reaction to Claude’s new Cowork feature in public markets says as much about investor psychology as it does about what Anthropic shipped. For months, software investors have been living with a background fear that “AI inside the app” is just a temporary comfort blanket. Then an agent shows up that extends beyond workflows, sitting above them to facilitate intent as input, acting as a competent colleague — starting to demonstrate that AI is no longer personal chat but actual personal assistance.

By Daniel W. Rasmus

Many factors can derail “trends”, and a bias toward seeing a trend can blind trend watchers from recognizing other patterns, especially contradictory ones. The year-end trend posts are less about prophecy than pattern recognition. The useful question isn’t “What’s next?” It’s “What changed in the operating conditions that will impact decisions I make in the near-term?” For 2026, the answer is blunt: AI stops being a tool story and becomes an infrastructure story. That shift pulls budgets, governance, architecture, skills, geopolitics, and energy into the same room, and they don’t necessarily all get along.

By Daniel Rasmus, Serious Insights for Techspective.com 

In many boardrooms, a dangerous delusion is taking hold. Executives are championing artificial intelligence by painting illusions of a seamless, frictionless future where knowledge workers become instantly more productive, creative, and compliant. In this case, however, it is AI that’s….

By Rex M. Lee, Security Advisor

Cybersecurity expert Rex Lee spoke at the 2025 Regional Cybersecurity Week Summit in Rabat, Morocco, representing Smart Africa and sharing strategies for cybersecurity and digital sovereignty.

By Robert Enderle, Enderle Group

The entertainment world has been set ablaze by the “Tilly Norwood” controversy and for good reason. The revelation that a beloved character in a well received show was not a real person but a fully AI-generated “synthetic actor” has become a flashpoint for a debate raging in Hollywood (AI Commissioner example). For many actors, it represents an existential threat that their craft is on the verge of being rendered obsolete by code. While their fear is understandable, history shows us that trying to ban a transformative technology is a fool’s errand. 

By Daniel W. Rasmus, Serious Insights

Rasmus highlights key lessons from industry leaders on successful AI deployment in organizations. Drawing from discussions with experts like Saanya Ojha of Bain Capital Ventures, Moveworks President Varun Singh, and thought leaders from TigerGraph, Semedy, and TopQuadrant, the article emphasizes designing AI projects with clear success metrics, including measurable ROI. Despite the MIT NANDA report noting that most AI pilots fail to reach production or deliver ROI, the takeaway is not AI’s failure but the need for organizations to ground AI initiatives in business realities. Success hinges on narrow project scopes, workflow integration, robust data foundations, and scalable design principles that ensure accuracy and governance. Knowledge graphs, enhanced by techniques like GraphRAG, play a vital role in contextualizing and scaling AI to meet enterprise needs, offering a practical playbook for achieving sustainable AI returns.

By Rob Enderle, The Enderle Group for TechSpective

In the complex world of enterprise IT, decisions around software support often feel like a Faustian bargain. Companies invest millions in mission-critical applications from giants like Oracle, SAP, and now, increasingly, VMware. With that investment comes the assumption that the vendor’s own support will be the most effective lifeline. However, a growing number of enterprises are discovering a powerful alternative: third-party support providers like Spinnaker Support. Far from being a niche solution, third-party support is emerging as a strategic imperative, offering significant advantages, particularly as organizations navigate the transformative landscape of Artificial Intelligence (AI).

By Daniel W. Rasmus

Technological revolutions rarely arrive on schedule. They come with fanfare, bold promises, and heavy investment, but their impact often hides in the shadows before it bursts into the open. Artificial intelligence now finds itself in this awkward in-between space. Boardrooms are abuzz with talk of generative AI strategies; enterprises are pouring billions into pilots and partnerships; employees are experimenting with chatbots and copilots. Yet in measurable business terms, most of these efforts appear to fail to deliver returns on the investments.