When it comes to AI, the biggest gains live in the white spaces, the system boundaries created back when coordination was too expensive to happen.

Many companies approach AI by identifying tasks they can automate. The bigger opportunity is not making current processes cheaper. It's recognizing that AI enables coordination across fragmented parts of organizations that couldn't align before.

The GenAI gold rush is on, and companies making bets on new technologies should consider three paths to AI implementation: Buy off-the shelf, boost with proprietary data and build custom solutions.

With the gap between imagination and deployment shorter than ever, understanding agentic patterns is a critical step in mastering the emerging AI-driven marketplace. We review six key patterns needed to drive value for customers and enterprises.

In her seminal AI report, Mary Meeker looks back at a seeming paradox from the first Industrial Age to underscore how the enormous productivity potential of artificial intelligence is poised to unleash entirely new categories of human activity.

Can AI shopping assistants close sales like a human expert? Our test shows they can, and how! Perplexity leads the pack, delivering expert-level, contextually nuanced product knowledge while ChatGPT impresses. Amazon's Rufus and Google Gemini trail behind. As shopping shifts from keywords to conversations, brands must adapt or risk invisibility in the AI-mediated future.

We tested AI shopping agents from Amazon and Perplexity to see how they fare helping prepare a family for Iceland's famously fickle Laugavegur Trek. Our quick takeaway? Highly capable LLMs such as Perplexity have the clear upper hand over bots like Rufus, at least for the moment, in providing expert-level guidance for complex purchasing, even if Perplexity's buy flow remains a tad glitchy. 

Complexity theory provides a cogent framework for understanding how agentic AI can drive corporate reinvention.

Agentic ecommerce moves beyond recommendation algorithms to focus on what the buyer is actually looking for.

Organizations adopting agentic tools need to reinvent themselves according to the KPIs of tomorrow.

As AI agents become mainstream, leaders need to prepare for a profound shift in human-machine collaboration.

Realizing the full potential of AI agents presents a curious challenge: learning from mistakes.

In this season of tech predictions, Human+Machine has proven prescient about the nonlinear roots of AI superpowers, writes David Golub.

Agentic AI is transforming product development, and it starts by using familiar tools like ChatGPT and Claude to create testable prototypes.

Does the morning briefing at your company probably look a lot like it did five years ago? Teams gather (virtually or physically), discuss market trends, share insights and make decisions. But here's the uncomfortable truth: if you're not already using AI agents to make your company smarter, you're falling behind the market. Goodbye, Human-Only Market Intel The shift to AI-powered market sensing isn't just another technological trend – it's a fundamental reimagining of how or

The AI revolution isn't about machines replacing humans — it's about forging partnerships that amplify human capabilities. 

RAG represents a significant architectural advancement in LLM deployment.

Exciting research is transforming how AI agents communicate, bringing dramatic speed mprovements to enterprise AI solutions.