By Bob Violino for CIO.com

CIOs with an eye for AI’s promise of improved productivity often find their efforts hindered by data quality, skills gaps, and sabotage, among other factors.

Artificial intelligence — and generative AI in particular — is fast proving to be a useful solution for increasing productivity across the enterprise but several common barriers to success remain.

The sooner IT leaders can identify and overcome these issues, the faster they will enable their organizations to get more value from AI-based systems.

By Rich Staples 

With all the buzz around Generative AI, it’s easy to forget that it’s just one type of artificial intelligence. Time Series, Geospatial, Computer Vision, and Graph AI are also growing fast—sometimes even faster than GenAI— particularly in sectors where real-time predictions and pattern recognition are business-critical.

Take Computer Vision: you've seen it in action in manufacturing, retail, and in medical imaging. But Time Series AI? It's not grabbing headlines, yet it's quietly driving massive outcomes behind the scenes. So What Is Time Series AI?

There have been growing calls to counter China's rise in technological advancements, especially in realms like AI. But what exactly are the risks to Americans? NTD spoke with Rex Lee.

Interview with Rex Lee, My Smart Privacy

By Rex M. Lee, Security Advisor & Investigative Tech Journalist, My Smart Privacy

Despite strong privacy laws like Europe’s GDPR and California’s CCPA, Big Tech exploits mobile apps to bypass protections, turning smartphones into data-harvesting tools. Here’s how they do it—and why it matters for your privacy. 

May 13th, 2025

TechTalk Summits proudly celebrates Advisory Board Member Shahidul Mannan, Chief Data, Analytics, and AI Officer at Orlando Health, for his inclusion in Orlando Business Journal’s 15 People to Know in Aerospace & Technology. A leader in AI and data analytics, Shahidul drives innovation in healthcare and beyond.

By Daniel W. Rasmus

As organizations embrace the democratization of AI, they often overlook the messy realities lurking just beyond the pilot projects and training sessions. Giving end users the tools to build and deploy their own AI agents sounds empowering—and in many ways it is—but without careful design, clear governance, and shared intent, it also invites a wave of unintended consequences. Before celebrating the creativity unleashed by user-developed agents, it’s worth stepping back and asking: how might this new autonomy create conflict, confusion, and risk inside the enterprise? Here’s a closer look at how agents can go wrong.

By Rob Enderle for TechSpective

Artificial intelligence (AI) is rapidly transforming our world, impacting everything from healthcare and transportation to finance and entertainment. As AI systems become increasingly sophisticated, it is crucial to ensure their development and deployment align with ethical principles.

By Security Advisor Rex M. Lee

In this third installment of our AI series, we unpack the rapid rise of artificial intelligence (AI) since 2000, spotlighting breakthroughs, risks, and the future of advanced systems like Artificial General Intelligence (AGI), Artificial Superintelligence (ASI), and quantum AI. Whether you're new to AI or a seasoned user, understanding its trajectory is critical to navigating its impact. 

By Daniel W. Rasmus, Serious Insights 

As we move deeper into the era of artificial intelligence, it is important to not just tie knowledge management to the development of AI, but to resist knowledge management principles to establish a foundation for where the conversations between AI teams and KM practitioners need to take place. This post offers an simple answer to the question, What is Knowledge Management?

By Daniel W. Rasmus, Serious Insights 

AI was supposed to help. In many ways, it does. But in just as many—and often more—it generates new layers of complexity. The visual “How AI Creates New Work and Wastes Time” captures six operational stress points that consistently appear in AI rollouts. They aren’t theoretical. They reflect the real work happening under the radar.