Kiteworks released new manufacturing specific findings from its Data Security and Compliance Risk: 2026 Forecast Report, revealing a stark imbalance in how manufacturers govern AI systems.
The research shows that while manufacturing organizations lead globally in production critical AI controls such as human oversight and real-time monitoring, they remain dangerously underprepared for adversarial AI threats, regulatory scrutiny, and supply chain AI failures that will define risk exposure in 2026.
“Manufacturing has built AI governance for reliability, not hostility,” says Tim Freestone, chief strategy officer, Kiteworks. “That works when failures are accidental. It fails when threats are intentional. AI systems don’t just break. They get attacked.”
Key takeaways:
· Manufacturing leads all sectors in human oversight of AI systems at 63% and AI data gateway monitoring at 56%.
· Only 7% of manufacturing organizations conduct AI red teaming or adversarial testing, less than half the global average.
· Adversarial AI attacks will exploit the red teaming gap. With 93% of manufacturers untested against adversarial inputs, AI systems will be compromised through model poisoning, data manipulation, and inference attacks.
· Compliance documentation gaps will drive regulatory exposure. Only 15% conduct privacy impact assessments and just 19% maintain evidence quality audit trails, leaving manufacturers unable to prove compliance as AI oversight expands globally.
· OT and AI convergence will outpace IT centric governance frameworks.
· Supply chain AI risk will remain under-governed.
“Manufacturers have world-class supply chain discipline, but AI has entered the ecosystem faster than governance,” says Patrick Spencer, SVP of Americas marketing and industry research, Kiteworks. “When supplier AI systems fail, the impact shows up on the production line, not in a policy document.”
