NetFoundry’s 2026 State of Secure AI Access survey says security leaders expect AI deployments to raise their attack surface by about 14% over the next year, while nearly all report poor visibility, 90% worry about shadow AI, and only 15% feel very confident in current tools.
The reason is plain: AI systems are not just another app. They stitch together models, APIs, cloud services, data sources, and partner platforms, and each link adds another place an attacker can reach. The access often rides on static secrets, service accounts, and other machine identities that can sit around with more privilege than they need, while tools built around human users miss that motion.
For teams rolling out copilots or agents that can read data and call APIs, the exposure sits in the machine-to-machine layer, not just on endpoints. In sectors like healthcare, pharmaceuticals, and technology, that can turn AI adoption into a control problem long before it becomes a malware problem.