The future of AI isn’t just agentic; it’s deep personalization. Rather than simple recommender systems that correlate user behavior to identify patterns and apply those to individual workflows, large language models (LLMs) and AI agents can analyze users directly to create deeply personalized experiences. It’s this kind of aggressive customization users are increasingly demanding — and the savviest enterprises who provide it (and soon) will win. The goal is: “Don't try to randomize, or guess who I am. I tell you, this is what I care about,” Lijuan Qin, head of product, at Zoom AI, explains in a new Beyond the Pilot podcast. How Zoom is incorporating personalizationZoom is one company that has adapted to this trend: Its generative assistant, AI Companion, goes beyond [...]
Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]
Across 116 enterprises, agents are in production and so are the incidents: A majority have already had a confirmed agent security event or a near-miss. Two-thirds of enterprises enforce scoped permiss [...]
Across 170 enterprises, AI infrastructure has moved decisively into production — two-thirds now run AI workloads live and three in 10 run them at scale — while the ability to account for what that [...]
Visa's president of technology, Rajat Taneja, walked the VB Transform 2026 audience through aiming Anthropic's Mythos at Visa's own payment network. The model stitched minor weaknesses [...]
Across 107 enterprises, agentic orchestration is not a choice of a single platform.The typical enterprise runs three orchestration platforms at once, and selects them for flexibility across models rat [...]
Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model [...]
Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incide [...]
Across 108 enterprises, trust in automated agent evaluation rose sharply in July — and the failure rate it is supposed to predict did not move at all. The share of organizations that fully trust aut [...]
Enterprise companies are running AI agents ahead of the controls needed to manage them — and they deployed that way knowingly. That is the central finding from VentureBeat Research's June surve [...]