| |OCTOBER 20249CIORevieweffectively scaling solutions we, as technology leaders, can empower our organizations to become AI-ready. Investment NeedsThe arrival of 5G promises a revolution in connectivity, enabling advancements like self-driving cars, smart cities, and precision agriculture. These applications will rely on millions of sensors generating data from roads, fields, and potentially even livestock. Managing this data surge will require much more IT capabilities.Beyond storage capacity, 5G will drive demand for AI-powered analytics (utilizing GPU-equipped machines) and time-series databases for real-time data processing. Open-source solutions like Kafka and Docker will gain traction for virtualization and cloud applications. The need for faster response times will necessitate a shift towards distributed data centers at the network edge rather than centralized facilities.Network virtualization using software-defined structures will become crucial for efficient resource allocation. Additionally, AI will play a critical role in network optimization, not just in resource management but also in data management. Maybe this time, we create a hypothetical system, Artificial Intestine-AI2, inspired by the human digestive system, a second brain that intelligently filters and discards irrelevant data, mimicking the way our bodies process information. Bridging the Talent Gap The digital age demands a surge in skills related to AI, data analytics, and automation. The surveys reveal that while AI and machine learning skills are highly sought after, they are also among the most challenging to find. Turkey boasts a young population with a growing pool of AI enthusiasts who can design, implement and manage complex AI solutions.New OpportunitiesWith slicing brought by 5G or new service providers with private 5G services, new service providers will emerge. Looking at the work done by the world's largest companies, network providers are transforming into digital service providers and, especially cloud services are becoming more popular. In conclusion, with the increasing demand for applications requiring high speed and low latency and the growing data, there will be many opportunities, but that may be the subject of another article. Getting one or two AI models into production is very different from operationalizing hundreds of them
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