AI is now emerging from science fiction to become the frontier of world-changing technologies, this brings an urgent need for systematic development and implementation of AI to see its real impact in the next generation of industrial systems, namely Industry 4.0.
Today, large data centers and enormous storage capacities make things possible that were believed for years to be distant concepts. Two branches of artificial intelligence, machine learning and deep learning, use the possibilities of big data to optimize processes, find new solutions, and gain new insights.
From small and medium-sized companies to large international corporations, every organization accumulates data that it can make use of. With software, this data is consolidated and evaluated to make predictions. Machine learning recognizes characteristics and relationships and uses algorithms to derive generalizations from them.
Organizations need to understand and identify the clear problems that utilizing AI and ML solutions will potentially solve. They will need to think about how they can add AI capabilities to existing and future processes, products and services. Instead of simply painting a broad vision, they need to also be clear on what impact it will have on the business over the short and long term.
AI/ML experts, business analysts, data scientists, and subject matter experts in today’s market are hard to find and expensive. Developing, deploying, and maintaining an AI solution from scratch will require data engineers, software engineers, product/project managers and ML/AI experts.
Organizations need to upskill their workforce or hire specialists with deep knowledge of current AI technologies as well as their limitations. Organizations with a limited budget may not be in the position to hire the right talent that is required for an AI project but they can always train their present resources for efficiently utilising AI based technologies.