Why this matters for mobile app security
As GenAI features are embedded directly into mobile apps, the model, prompts, and on-device inference flows become part of the app’s attack surface.
Security teams need to assume adversarial conditions on real devices, including tampering, instrumentation, hooking, repackaging, and automated abuse.
Protecting GenAI on mobile therefore requires strong runtime integrity, resistance to reverse engineering, and controls that reduce abuse without breaking user experience.
What you will learn
On-device GenAI is moving from experimentation to mainstream product roadmaps, including how endpoint devices will run small language models locally, when workloads should shift between device and cloud, and why security becomes a prerequisite as adoption scales.
- How on-device GenAI is expected to evolve, including increased hybrid execution across device and cloud.
- Why smaller, domain-specific models are expected to increase in local, on-device use.
- Why security is expected to become a key differentiator and baseline requirement for on-device GenAI adoption.
Promon note
Promon is mentioned in the report as part of an industry discussion.
“Endpoint devices will run small language models locally, blending with cloud resources when needed, to deliver on-device GenAI. But the product leaders must split workloads, use model compression and significantly improve security to win here.”
Gartner, Inc., Emerging Tech: The Future of On-Device GenAI, Ben Lee, 03 Oct 2025.
Disclaimer
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s business & technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a trademark of Gartner, Inc. and/or its affiliates.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Promon.
