Several Top Names Call for Action on the Regulation and Prohibition of AI Superintelligence

Many high profile public figures, along with multiple AI "godfathers" and array of religious, media, and tech experts, have released a letter calling for a ban on AI "superintelligence that threatens humanity."

AI in Disaster Recovery: Mapping Technical Capabilities to Real Business Value

AI is no longer a speculative technology; it is a practical tool with clear, transformative implications for cyber resilience (CR) and disaster recovery (DR). While AI's potential is often overstated, its measured and strategic application can directly address some of the most persistent challenges in safeguarding organizational data and ensuring business continuity.

New Report Shows 95% of Companies Lack Return on AI Investments

While many companies are pouring money into corporate AI projects, a recent MIT report shows that 95% of these organizations are seeing zero return.

This is Your Brain on…AI

A new study emerging from MIT's Media Lab shows that ChatGPT, and other LLM-adjacent interactive solutions, could be actively harming our critical thinking skills.

From Promise to Progress: Closing the Gap in Enterprise AI with Process Intelligence

In the rush to embrace artificial intelligence (AI), enterprises across industries have encountered a harsh reality: transformation takes more than technology. Two years ago, generative AI captured the imagination of business and technology leaders alike, promising to revolutionize operations and decision-making. Yet today, many organizations find themselves with pilot projects that are failing to scale, and AI investments that are falling short of expectations.

Unclogging the AI Data Pipeline—Three Critical Bottlenecks Constraining AI Clusters

It's not just GPUs, but memory, storage, and networking capabilities that determine AI infrastructure performance and efficiency.

From Silver to Gold: Why the Semantic Layer Is the Future of Data Product Engineering

Modern data environments are becoming more complex. Data lives in cloud data warehouses and across lakes, SaaS platforms, real-time streams, and operational systems. The standard way to build an enterprise data lakehouse is to use the medallion architecture, where data is taken from the source system and transformed in stages.

From Prompt Attacks to Data Poisoning: Navigating LLM Security Challenges

In enterprises' frenzied rush to put large language models (LLMs) to work and get out to market with new applications, security has (perhaps understandably, at least initially) taken a backseat. But attackers are increasingly testing the security of LLM deployments, which are vulnerable to traditional cybersecurity risks such as system compromises and data breaches.

The New Enterprise Frontier: AI Reasoning and Agentic AI

While we sit in an enterprise culture enraptured by AI, it is hard not to think about what's next. With some leaders comparing the early dawn of AI to the birth of the internet, there is significant hope that AI will continue to grow and benefit business and society through future innovations.

New Report Shows Disconnect Between Business Investments in AI and Lack of Successful Execution 

Qlik, a global leader in data integration, data quality, analytics, and artificial intelligence, announced the findings of a new study conducted with Enterprise Strategy Group (ESG) that reveals businesses are moving aggressively to scale AI, but many lack a structured plan to build the data foundations necessary for long-term success.

5 Insights on the Future of Enterprise AI from Todd James at 84.51°

Todd James, chief data and technology officer at 84.51°, recently discussed the shift in perceptions of AI as an abstract technology to an impactful driver of business outcomes at the Gartner IT Symposium.

2025: The Year of Breakthrough AI? Tech Leaders Predict the Next Stages of Enterprise AI

AI's influence is being felt everywhere, from chatbots that help people shop online to talk of autonomous drones or other Internet of Things devices that can act independently. 2025 shows no signs of slowing what organizations may want to tap into or create AI solutions for.

Modern Data Management for the AI Era

It's well established that AI—both operational and generative AI (GenAI)—is changing the game for data management. Today's data environments need to support large (and not-so-large) language models that have to be constantly trained with inflows.

The AI Revolution: Bridging the Gap Between Potential and Readiness in the Data-Driven Era

AI talent is in high demand; AI reveals brain oscillations for memory and disease; AI may allow us to talk to whales; AI can help plan meals and other tasks; an AI platform for dentistry just raised $53 million. That was the tip of the AI news iceberg—in one day.

The Unseen Ethical Considerations in AI Practices: A Guide for the CEO 

Artificial Intelligence (AI) is only accelerating its adoption among global corporate enterprises, thus CEOs and business leaders are positioned at the confluence of innovation and ethics as it relates to implementing AI projects in their businesses. 

AI Agents Are the Next Wave of Enterprise AI

The interest surrounding artificial intelligence (AI) has never been higher, but AI agents are the next wave of innovation enterprises need to prepare for.

Embracing Generative AI: Strategic Insights for Successful Digital Transformation

The speed at which tech innovations are happening is mind-boggling. Many of these advances offer productivity, security, and management opportunities, but they also come with risks. When embracing digital transitions, many companies attempt to adapt without the proper infrastructure or fail to complete a full rollout. This dilemma of "how much is enough" is surfacing with generative AI, which companies are wrestling with in virtually every aspect of their businesses.