When mathematics and statistics align and work in tandem, the result is a good AI product that could be deployed in automation and computing. In the last five years, the automation industry has evolved and grown rapidly, ushering in an era where machines and artificial intelligence perform most roles for humans at work and sometimes perform these roles even better than humans. As we move towards information sharing, processing, and automation, the world has recognized the value of AI in automation and cloud computing.
As we advance and get reliant on automation and AI, we see a threat in the immediate future wherein most jobs could be performed by machines and robots, and human involvement is replaced as a consequence. To support this thought, according to a McKinsey & Company report, 50 percent of all tasks and jobs are ripe for automation in the future, and 6 out of 10 jobs today have activities in them that are more than 30 percent automatable.
But in the current scheme of things, AI has proven to be a boon in terms of efficiency and cost-saving for enterprises, AI has assisted us to automate so many of the mundane tasks that used to take immense time to complete manually. AI has added so much value in various spheres of our professional life, from touch-free attendance systems, payroll computing, and working with teams from the comfort of your own home, to data analysis. Such value addition proves that AI is not a menace but rather a useful human-made instrument with the potential and skills to stretch human thoughts and perspectives to new heights. To understand the value proposition and size of the opportunity in the AI domain, according to a PwC estimate, AI will contribute $15 trillion to the global economy by 2030; this value is more than the total economies of India and China combined!
With the fast adoption of artificial intelligence in our everyday lives, we are at a stage where we are wondering how to capitalize on AI while avoiding being a target of it. With the vast amount of potential that AI holds, multitudes wish to join this bandwagon but are perplexed about where to begin and how to create a profession out of AI. To support and encourage your journey into AI, I would like to quote an extract from Bernard Marr, a world-renowned futurist, influencer, and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. “97 million jobs involving artificial intelligence (AI) will be created between 2022 and 2025.”
To make the journey into the world of artificial intelligence and mammoth potential easier, the below script is a step-by-step approach to ensure one has the right resources and enablers to become an AI specialist.
Who is an AI expert?
AI specialists are familiar with the numerous programming technologies and tools accessible in the AI business. Data science enthusiasts who collaborate with firms from a variety of sectors to devise new and inventive methods of enhancing efficiency and integrating AI technology into day-to-day operations to attain a more streamlined working environment that is an enabler for productivity and growth.
Data scientists usually collect information and data from data pools and employees based on their needs and generate customized intelligent outcomes that boost efficiency in decision-making and bring in competency across the enterprise.
The question at hand is, “How do you become an AI expert?” or “What talents are necessary to master the art of AI?”
This may appear to be a difficult question, yet the solution is straightforward.
Qualifications needed to be an effective AI programmer
First and foremost, when it comes to AI for automation, besides having an analytical mind, proficiency in mathematics, and an understanding of statistics, a background in computer science is immensely essential. As AI is entirely controlled by computers, having knowledge or a degree in disciplines connected to computer science is a big technical advantage in terms of AI learning. This implies that to program AI, one must begin as a developer with proficiency in coding and knowledge of programming languages such as Python, Java, and C++.
In addition, one should know the principles and fundamentals of how computers work—in other words, the mechanical knowledge that underpins inputs and outputs, as well as how to understand the strengths and limitations of a system and its results. Machine learning and AI have several limitations, either owing to a lack of data or a lack of technological developments within an environment to enable AI deployment. Identifying these constraints, adapting to the tech ecosystem present in the work environment, and designing solutions around them are essential elements of AI knowledge.
Once the above fundamentals are in place, one needs to decide the area of machine learning or artificial intelligence they wish to work in. AI has several applications in diverse sectors. To name a few, AI is widely used in the following fields:
1. Manufacturing Automation
2. Data Analysis
3. Statistical Research
4. Product Development
7. Financial Sector
According to a TCS research study, more than 80% of organizations employ AI/ML in some form or another in the above sectorial domains.
Key skills that provide a more creative approach
Along with the credentials for becoming an AI expert, there are a few innovative techniques that help an AI expert become exceptional. For developers to produce completely novel AI/ML products and services, one must have a high degree of interest in understanding the process of decision-making and the outcomes/results commonly produced by human involvement. This understanding assists one to automate a machine that expedites the attainment of better productivity for the specific critical tasks in enterprises and corporations. Although the programmed machine performs the majority of problem-solving duties, there are still troubleshooting procedures that require a person to have a mathematically solid approach to identify and support the AI program at work. Such characteristics, along with a high level of rational thinking, result in superlative AI programming.
Finally, whether you have a strong vernacular or not, being able to communicate with your coworkers about new concepts, ideas, or technical revolutions is a vital element and requirement in the AI domain. Human resource and IT experts search for talent that can comprehend and grasp situations efficiently; basically, anyone with a problem-solving mind is sought after.
You don’t have to be concerned if you’re wondering how successful a career as an AI specialist may be, as AI is an industry by itself, as statistically mentioned earlier. This boom is not to be missed and we predict the next 10 years to be the era of AI and everything AI.
The article has been written by Abhishek Agarwal, President-Judge India & Global Delivery at The Judge Group