According to SecurityWeek, the key to securing AI software is not how quickly organizations adopt AI, but how mature that adoption is. The article argues that where developers sit on the AI adoption scale has a real impact on how security risk is addressed. This suggests that a rushed, immature rollout may leave gaps that a more measured, mature approach would avoid.
For security and privacy teams, this means evaluating the maturity of AI practices before assuming standard security measures are sufficient. A developer team early in its AI journey will face different risks than one that has integrated AI deeply into its workflows. The article implies that security strategies should be calibrated to that maturity level rather than driven by speed.
Ultimately, the takeaway is that maturity—not velocity—should be the guiding metric for AI software security. Organizations that slow down to assess and mature their AI adoption are better positioned to manage the associated risks. This perspective reframes the conversation from racing to implement AI to building a secure foundation for it.