Banning local governments from contracting with Chinese-created AI tools Preventing AI companies from selling consumer data Fortifying anti-deep fake protections Allowing parents to access their child’s conversations with these chatbots Requiring attorneys to certify whether they used AI to write legal briefs Prohibiting utility companies from charging Floridians to subsidize data centers Allowing local governments to refuse AI data centers Preventing AI data centers being constructed construction in agricultural areas Policymakers can take steps to protect the public from the new technology with a “State AI and Bot Framework” incorporating the same strict "never trust, always verify" policy as human users, requiring continuous authentication, least-privilege access, and real-time monitoring to prevent exploiting gaps in systems, which often struggle with bot- driven attacks mimicking human behavior at scale. Establish effective and constant coordination between legal compliance teams and cybersecurity teams to find balanced approaches. Implement a tiered assessment program that distinguishes among AI used for citizen- facing decision-making or broad-based “answer anything” type systems (e.g., chatbots), AI used exclusively for threat detection and security-based decision- making, and employee use of AI platforms for content creation or citizen
engagement.
Strong Identity Verification: Every entity, human or machine, must be rigorously authenticated and authorized at every access attempt. Principle of Least Privilege (PoLP): This foundational security principle ensures that all entities have only the minimum access rights necessary to perform their specific tasks. Microsegmentation: GenAI attacks are fast and adaptable, meaning perimeter defenses will likely fail. Dividing the network into small, isolated segments to control lateral movement and enforce granular policies across applications and physical operational technology devices. Continuous Monitoring for Applications and API’s: All digital traffic and AI behavior are monitored for anomalies in real time, allowing for rapid detection and response to potential threats. Firewall for AI: Real-time input/output security for compliance, privacy, and safe generative AI interactions. This security layer protects users interacting with AI from threats like prompt injection, data leaks, and misuse by inspecting both user inputs (prompts) and AI outputs in real-time, using AI to identify malicious patterns, filter sensitive data, enforce policies, and block harmful content before it reaches the user or the model.
Require model transparency documentation (e.g., data- lineage maps, validation, and testing reports, etc.) that satisfy specific the specific AI Act and NIST documentation requirements while still protecting proprietary detection logic. From a compliance perspective, “It ain’t compliant if you can’t prove it!” Adopt privacy-preserving telemetry, such as hashing, tokenization, or differential privacy, whenever possible so security models can ingest high-fidelity signals without processing PII, which can reduce exposure. Establish a continuous monitoring and improvement loop. Align performance monitoring with regulatory mandates for post deployment monitoring, ensuring that drift and false-positive spikes are promptly addressed and documented. Enhanced scrutiny of technology companies with relationships enabling the development of powerful AI by Chinese companies, and their management of AI web traffic, including that from Chinese bots. Mandatory disclosure and approval process for any state systems integrating foreign AI services. Implementing technological framework in an AI environment involving several key practices:
14 – 2026 Legislative Edition – Florida Technology Magazine
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