Lot of countries AI missions are more on soft skilling and depending heavily on data centers. We need to create money value in both Software and hardware level in 2026. AI tools are matured now and Governments should encourage local hardware memory and compute as well ( edge computing ). For example if any AI course offered in india is charging more than 1 lakh rupees its should be mandatory to include hardware in the package like mobile or tablet or laptop. Governments across world has to encourage exchange offers in mobile, tablet and laptops for AI practioners with GPU devices. For small things we should not depend on data centers and government incentives should include hardware devices as well. Agentic AI framework reduces lot of load on data centers and its good to orchestrate it smartly and Governments should encourage it. Pega was giving personal editions before similar strategy and tactic must be applied to AI courses as well.
AI courses in 2026 should include an edge computing device, such as a laptop or tablet with AI capabilities, as part of the course package. This helps learners run AI models locally instead of relying only on cloud data centers. It gives hands-on experience, improves practical skills, and supports faster, more efficient AI development.
Strong point on edge computing. Not every AI workload needs to depend on centralized data centers, especially as local devices become more capable.
Governments should encourage access to AI-ready hardware alongside skills development, while allowing flexibility rather than mandating a device with every course. The real goal should be broader access to compute, practical experimentation, and architectures that intelligently balance edge and cloud resources.