6 things every AI leader needs to get right in H2 2026
The pilot phase is over. Here are the 6 trends shaping AI strategy in H2 2026, from agentic infrastructure to physical AI and custom builds.
5 questions AI agent vendors hope you don’t ask
Most AI agent failures don't happen during the demo. They happen when APIs fail, context windows explode, costs spiral, and nobody can explain why the agent made a decision. Here are five questions that separate production-ready platforms from expensive experiments.
The AI-first GTM strategist: agents, workflows, and knowing when to stop
Most GTM teams deploy AI where it's most visible. The question worth asking first: is that actually where it's most ready?
Your data engineers may be more influential than you think
The data engineer has gone from a largely behind-the-scenes role to one of the most strategically important positions in a modern technology organization. The leaders who understand why are making significantly better infrastructure decisions than the ones who do not.
8 ways self-evolving AI agents are about to change how we build software
A new paper out of arXiv this week describes an AI system that builds, improves, and deploys its own specialist agents. Here is what that actually means for engineers and technical teams.
5 ways to prepare for physical AI, today
Jensen Huang called it "the ChatGPT moment for robotics." Deloitte says 80% of businesses plan to use physical AI within two years. Here is what you actually need to know, and do, to prepare…
What’s shaping frontier AI in 2026? Find out in London, May 21st
On May 21st, the Innodata GenAI Summit convenes in London for a single day of rigorous, practitioner-led exchange on the challenges defining frontier AI in 2026. Here is what the agenda covers, who is in the room, and why it's a must for AI professionals...
The rise of agent experience (AX)
AI agents are becoming active participants in commerce, logistics, and enterprise systems. This shift is creating demand for a new product layer built for machines rather than humans, where negotiation, semantic visibility, and autonomous execution matter as much as traditional UX.
Is the AI value gap wider than anyone is admitting?
AI is delivering real value—but only for a select few. Most organizations are still experimenting without meaningful impact.
What analytics engineering didn’t prepare me for in AI
From clean dashboards to messy intelligence systems.