Artificial Intelligence is practically discussed across every concern upon the social spectrum today. The featured discussions tend to predict where and when it could be applied. Over 80% of the companies all around the world are either investing or are intensively engaging in technology in some fashion or form. To effectively pursue their dreams, there has been significant demand in terms of hiring AI and machine learning specialists. Despite the high level of demand, it has been noticed that companies did not define a specific set of criteria for job roles, neither the dissemination of responsibilities. Most of these roles are for Ph.D. specialists, who have had done research across data science and machine learning, able to present some very abstract engineering capabilities.
It appears that the role of Artificial Intelligence would have to become more than research and development, as time would go on. It has the potential to increase the efficiency and effectiveness of the entire workforce to levels not seen before. But, to do so, companies should at least have to clearly state for what reason or purpose they want AI technologies to be employed. This has been compiled in terms of holistic viewing, as what roles and responsibilities differ among those individuals; and what outcomes with use of AI would gain traction to achieve it in an organizational setting.
The Role of an AI Engineer
The role of an AI engineer has already been defined and adapted by many in the business world for obvious reasons. While researchers can propose ideas, with regard to Artificial Intelligence being implemented across products and processes, an engineers would be the ones to actually realize them in practice on a continuous basis. The skills with respect to any AI Engineer have started to formulate: the creation of unique architectures for scaling, deployment, and integration of AI upon the existing systems, are some of the most common applications. To be specific, any AI engineer would then need to possess skills across programming and other fields outside of AI.
Experiential Data Expert Role
The connection that exists between data science, machine learning and AI are all intrinsically conjoined together to comb through a wide collection of data and find something unique. Instead of just building models that humans need to make sense of, the data is essential for system to be taught, and therefore machine learning methods are applied. To this end, it would require an extensively experienced Data Analyst, whose skills and capabilities based upon a multi-point perspective of understanding and interpreting data and its proper channels.
The Role of an AI Translator
This role would also need to be filled within company hierarchy to perform the translation of all the possibilities of AI research and consolidation to be effective. This generally means that the personnel would not require to understand every particular aspect of the problem at hand with respect to AI. AI translator would help business to understand, and strategize their functions and processes accordingly with help of AI.
While many more job roles also need to be established in the future, as AI technology continues its evolution and exploration. These roles are essential for any organization looking to earn profit and achieve excellence by applying AI techniques.