AI in IoT refers to embedding artificial intelligence into connected devices and systems. It enables machines to learn from data, make real-time decisions, and optimize processes autonomously.

The cost can range from $10,000 to $200,000+ depending on the project's complexity, scope, technology stack, and integration level.

Most projects take 3–12 months. Timelines depend on factors like device connectivity, AI model training, edge integration, and testing cycles.

Generative AI creates simulations, synthetic data, and optimizes system behavior in real time. It helps predict outcomes, test scenarios, and personalize responses dynamically.

It enables predictive maintenance, real-time automation, efficient operations, and data-driven insight, resulting in cost savings and smarter decision-making.

Challenges include data security, device compatibility, and latency. Solutions involve edge computing, strong encryption, and robust AI model training.

Look for proven experience in AI + IoT, strong portfolios, industry-specific knowledge, post-deployment support, and client testimonials.

Edge computing processes data closer to the device, reducing latency and ensuring faster decisions. It's crucial for time-sensitive and secure IoT operations.

Implement data encryption, multi-level authentication, regular firmware updates, and anomaly detection to protect against threats.

It’s a privacy-first AI method where models are trained across multiple devices without transferring raw data, ensuring security and personalization.