AI thrives on data, but privacy regs like GDPR demand safeguards. Federated learning trains models without centralizing data. Differential privacy adds noise to outputs. Tools like TensorFlow Privacy implement epsilon controls. Homomorphic encryption enables compute on ciphertexts via Microsoft SEAL. Anonymization with ARX preprocesses datasets. Audit AI decisions with What-If Tool. This enables trustworthy ML in healthcare, finance while avoiding fines.