Specialized models are the future. Generic models are like general practitioners, but the world needs experts. We're seeing AI being tailored for sectors like healthcare, finance, and agriculture. It's not just about optimization; it's about creating AI that speaks the language of the industry it's in.

Countries and corporations alike are seeking greater control over their AI infrastructures. It is not just about data privacy anymore; it is about strategic autonomy. This trend is reshaping global tech alliances and could lead to a more fragmented but innovative AI landscape.

Interactions are becoming less about clicks and taps and more about natural engagement. Think AI that understands not just words, but context, emotion, and intent across text, voice, and even gestures. Brain-computer interfaces are also making strides.

As AI systems become more integral, they're also becoming targets. The focus is shifting towards not just cybersecurity but AI robustness—building models that can withstand and adapt to threats. New frameworks are being developed for continuous verification and trust assurance.

Quantum computing promises to turbocharge AI capabilities. While still in nascent stages, quantum algorithms could solve complex problems beyond the reach of classical computers, processing and analyzing data at unprecedented speeds.

There's a growing demand for AI models to be less of a black box. XAI is about transparency—developing models that provide insight into their decision-making processes. This is crucial in fields like finance and healthcare.

Processing data closer to the source—on devices like smartphones or IoT gadgets—is becoming essential. Edge AI reduces latency, enhances privacy, and lowers bandwidth usage.

Ethical considerations are taking center stage. Bias in AI models has real-world implications. Governments are stepping in, aiming to set global standards for AI ethics and governance.