Thinking of AI as a Career?

Artificial Intelligence (AI) is one technology that is seeing a spur post-Covid-19. Several businesses consider AI as a critical ingredient to resiliency and sustainability. In 1956 the term artificial intelligence was used for the first time to determine the ability of machines to perform human-like tasks. Over the decades, it has matured to a level where it is outperforming human intelligence. Factors driving the adoption of AI technology include increased computing power, the ability to handle large volumes of data, and advancement in AI software.

Artificial intelligence facilitates organizations in converting data into meaningful information and enables them to minimize the redundancy level from the process. Workers working side by side with AI tools have increased their productivity and met organizational priorities. Besides that, it enables business organizations to move closer to their customers, streamline business operations, automate tasks, and increase revenue. Businesses of any size today use AI to foresee and manage any disruption.

Artificial intelligence has completely changed the perception of organizations on conducting their regular operations and how they interact with machines. It is getting better at mimicking human behavior by utilizing advanced technology such as face recognition, OCR, dialogue generation, image classification, etc. The field is expanding quickly, and it is going to pervade businesses in many ways. Driverless cars, chatbots, voice-based navigation systems are some exceptional examples of AI applications.

As per MarketWatch, the AI market will touch USD 4417.8 million by 2025. Another study indicates that by 2030 AI will contribute $15.7 trillion to the global economy. Businesses implementing AI across various processes have increased the demand for AI specialists. Major industries that observe the high adoption of AI include automotive, education, healthcare, finance, entertainment, manufacturing, supply chain management, IT, and others.

Who Can Pursue AI as a Career?

Students or professionals from any discipline with a background in mathematics, computer science, or programming language can pursue a career in AI. The top-level AI jobs require a master’s degree or Ph.D. After successful completion of the basic graduation with mathematics and programming language, students can opt for higher education in AI such as M.Eng, MS, or Ph.D. AI can be chosen for a BS qualification as well. Many of these courses will cover subjects in depth in machine learning, robotics, and natural language processing.

AI aspirants often get confused between AI and Machine learning. Machine learning is a subset of artificial intelligence, which is further segmented into neural networks, natural language processing (NLP), and deep learning. Machine learning enables machines to learn from data automatically without being programmed explicitly.

Career Opportunities for AI aspirants:

• AI engineer: AI engineers use programming algorithms to create AI models that behave like a human. It requires combined expertise in programming, data science, software development, and data engineering.
• Machine learning engineer: Machine learning engineers use ML techniques to enhance the performance of AI models. They are involved in developing and maintaining software programs that operate automatically and support the machine learning process. They are well versed in applying predictive models and managing large data sets.
• Robotic scientist: Robotic scientists are responsible for programming robots to do particular tasks. They see themselves in diverse roles, from designing prototypes to researching robots’ real-life applications. They use AI algorithms to make robots work independently and assist humans in performing various tasks.
• Data scientist: Data scientist converts a high volume of data into insightful action. Data scientists usually use machine learning techniques and predictive modeling to identify the trends and relationships in data sets.
• Data Engineer: The role of a data engineer is to build and manage the organization’s entire data ecosystem. They are responsible for converting raw or unstructured data into structured data. Besides that, they have to define data pipelines that help them to collect data from various sources and process them in real-time. Some of their work overlaps with data scientists and data analysts, such as conducting complex project analyses. In a large organization, they have to work side by side with data scientists and data analysts.
• AI data analysts: The key responsibility of AI data analysts is to perform data mining, data cleaning, and data interpretation. They populate analytic data reports in the form of dashboards and data visualization, which helps the organization to make critical business decisions.
• Business Intelligence Executive: The role of a business intelligence executive is to ensure that business data is correctly gathered, stored, and analyzed. They have to develop methodologies to enhance the data analysis process. The BI executive derives data insights to create strategies that influence future business operations.

What Are the Skills that Support AI Learning?

To make a career in AI, you must possess some skills and qualifications. These skills are essential to groom yourself as an AI expert. Without these skills, the learning curve would be steep and lengthy.

1) Mathematical skills: A comprehensive knowledge of linear algebra, calculus, logistic regression, and algorithms is essential to becoming an AI specialist.

2) Statistical skills: Clarity on concepts such as Bayesian networking, Markow models, univariate and multivariate statistical analysis help analyze various AI models.

3) Programming language and data science: As an AI professional, you have to create predictive models using a high volume of data. Deep knowledge of databases (Cassandra, MongoDB, Hadoop) and programming languages such as Python, Java, Lisp, R, C++, Julia, MATLAB can assist in configuring and implementing algorithms in AI models. Programming languages like Python have explicit libraries that assist in executing scientific and logical methods in AI models.

4) Communication skills: Cultivating communication skills is vital for you. As an AI expert, you have to communicate about the AI models to stakeholders, clients, and team members.

What Is the Role of AI Experts?

• Develop AI models that emulate human cognitive skills.
• Collaborate with data engineers to build AI models.
• Apply AI principles and techniques such as machine learning, neural networks, and computer vision to automate various business processes and solve domain-specific challenges.
• Create AI models and convert them into APIs so that other applications can interact with them.
• Perform statistical analysis using the right tool to support organizations in decision-making and find common pitfalls.
• Validating and verifying AI models.
• Assessing data quality.
• Enhance existing AI models.
• Coordinate with stakeholders and product managers to identify business problems and propose a viable AI solution.

Various Applications of AI

• Manufacturing: AI is revolutionizing the manufacturing industry by solving long-standing issues such as high maintenance costs, unorganized supply chains, and poor product quality. They use AI to predict equipment maintenance, automate workflow, track inventory, train employees, etc.
• I.T sector: IT companies can automate many repetitive tasks using AI/ML technology. From writing codes to identifying bugs, AI can assist programmers in increasing their productivity. Besides, that AI can be used to automate software testing and helps to save the QA team valuable time. There are many other use cases of AI in the IT industry, such as identifying security threats in the network, tracking software licenses, planning IT maintenance, etc.
• Automotive: Autonomous vehicles are creating buzz around the world, and AI has a major role in making it a reality. From parking assistance to speed control and identifying objects around the vehicle, AI is taking the automotive industry to the next level.
• Banking and finance: The application of AI in the banking and finance sector is diverse. For instance, banks can use AI to segment customers based on their needs and behaviors. They can use this data to sell their products and enhance customer experience. Further, they can use AI to detect fraud, make loan decisions, track regulatory compliance, etc.
• Health care industry: AI is reshaping the healthcare industry, and it has numerous applications. It is used to diagnose critical disease, drug discovery, reduce dosage error, virtual nursing assistant, automated image diagnosis, and so on.
• Retail sector: AI can be used in a myriad of ways in the retail industry. AI chatbots can assist customers in searching products, locating nearby stores, offering discounts through push notifications, placing orders, or even answering FAQS on return policy, brand information, product availability, etc. Whereas, retailers can use AI for managing customers’ complaints and tracking their preferences.
• Logistics and transportation: AI has transformed logistics and transportation entirely. It is used to forecast product demand, modify orders, and manage transportation routes. AI-enabled data analytics allow business owners to track the entire product journey from start to end. Some startups are also offering innovative solutions such as drones to enhance last-mile delivery, and AI can assist in delivering goods without any error.

Tips to Become an AI Expert

There are various ways to specialize in AI skills.

• You can register for advanced AI courses and also try your hands on AI open projects such as TensorFlow, PyTorch, Keras, Theano, etc.
• Build a strong portfolio by actively participating in various community hackathons and online forums.
• If you are fresher in AI, then get an entry-level job that deals with data science and related fields that help in gaining knowledge in AI.
• Read popular research papers on Google Big Table, Google file system, and Google AI blog to sharpen your AI knowledge.
• Since the Linux operating system is widely used for developing ML (Machine Learning) applications, it is recommended that you have good command over Unix tools such as grep, cut, tr, awk, sort, etc.
• Can do a short course on Python.
• Try and understand a few basics of database management systems.
• Learning a few basics of variables, statistics, and probability might help.
• Good knowledge of Algorithms will help in understanding Machine Learning better.

What Is the Payscale for AI professionals?

The salary of an AI professional could vary between $65,760 — $122,000 per year in the United States and can exceed based on the experience level and expertise. Payscale can vary based on geographic location. Besides that, the AI role envelopes broad categories such as AI engineer, research scientist, software engineer, data scientist, BI developer, big data architect; the pay scale varies based on the position.

The Future Scope of Artificial Intelligence

The market stabilized companies like Amazon, Apple, Google, Facebook, Microsoft, etc., have enormous demands for AI specialists. With increasing digital touchpoints and with the increasing demand for intelligence generated automatically through machines, more and more companies — small, medium, and big, will have to rely on AI experts.