Council Post: Careers for the future of AI

AI has the potential to solve some of the world's biggest problems—from climate change to epidemics. This makes careers in AI not only innovative but also fulfilling and socially responsible. Even more so, in 2023, professionals in this field are likely to remain top priority because they offer a combination of high demand, high earning potential along with the chance to make a positive impact on the world.
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Following the raging popularity of ChatGPT, the question of whether AI will take away jobs has changed to whether ChatGPT will take away our jobs. However, as logical as that query might be, there is more in the world of AI that remains to be discussed. Opportunities for entrepreneurs and innovators to create new products and services that can disrupt existing industries and create new ones are ubiquitous in the field. Additionally, AI has the potential to solve some of the world’s biggest problems—from climate change to epidemics. This makes careers in AI not only innovative but also fulfilling and socially responsible. Even more so, in 2023, professionals in this field are likely to remain top priority because they offer a combination of high demand, high earning potential along with the chance to make a positive impact on the world.

AI might be misunderstood for taking away jobs, but this article will focus on the jobs that the field is helping create with its innovations. 

Prompt Engineering

The process of designing and optimising the input prompts required to train AI models is known as prompt engineering. Researchers and engineers can direct the model to focus on particular features of the input data and enhance its performance on specific tasks by carefully constructing the input prompts. For instance, in natural language processing, prompt engineering can train a language model to produce more grammatically accurate or coherent writing. Additionally, it can be used to train models that concentrate on particular features of the input data, such as sentiment analysis or named-entity recognition. Overall, AI models can perform better and be more valuable for certain applications with prompt engineering.

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The mission of OpenAI is to develop secure artificial intelligence for the benefit of all people. They have created a number of potent AI models, including GPT-3, which can comprehend and produce human language. One can create an API—or application programming interface—to use these models. Other programmers can also access the model’s capabilities and utilise it in their applications with the help of an API thus created. It can also be monetised by way of providing API as a service for a monthly or yearly subscription fee for access.

Data Detective

Sherlock Holmes in a data set would definitely be something to look forward to. This kind of work might be suitable for someone with experience in law enforcement and fundamental data skills, or even an inquisitive graduate with data literacy hoping to land an entry-level job in a promising field. Analysing the data that is available and determining which components are most useful in meeting the reporting needs of your client is what the work entails. Sorting and arranging the data in such a way that it will be relevant to the customer’s needs and is easier to comprehend.

Edge Computing Master

Large companies will require assistance keeping up with the computing industry’s fast pace. Designing and supervising the implementation of edge computing solutions for IoT devices is the responsibility of an edge computing master. Working with chipsets, operating systems, middleware, and applications may be required. A bachelor’s degree in computer science or an adjacent discipline as well as expertise in network engineering, software development, and systems administration are typical requirements for this position.

Quantum Machine Learning Analyst

One of the positions that AI will likely produce in the near future is a quantum machine learning analyst (QML analyst), which is a developing field of study that combines machine learning and quantum physics to build a hybrid system. An expert who can conduct research and build applications for next-generation solutions using the fields of quantum information processing and machine learning may be suitable for this position. A thorough understanding of quantum technologies will also be necessary for this role in order to improve the performance and the speed of machine learning algorithms and identify quicker answers to business problems.

Cyber City Analyst

A cyber security analyst’s primary responsibility is to protect a company’s network and systems from internet threats. This entails researching future IT trends, creating backup strategies, examining suspicious activities, reporting security flaws, and instructing the rest of the company on security procedures. Cyber security analysts also have the responsibility of implementing security controls and threat protection mechanisms. They may even mimic security attacks to find any potential vulnerabilities that might exist within the firm. Since hackers constantly employ new strategies and technology, cyber security specialists must keep up with the countless developments in their digital arsenal.

With all these newly developing concerns, AI has advanced far from its early uses of solving trivia questions and playing chess to being prepared to solve—and occasionally create—complex problems for society and industry. As a result of newer technology, more specific and in-demand AI roles will emerge, raising the bar for hiring managers. As is often remarked, change is the only constant and artificial intelligence is already reflective of this continuity and evolution.

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here.

Anirban Nandi
With close to 15 years of professional experience, Anirban specialises in Data Sciences, Business Analytics, and Data Engineering, spanning various verticals of online and offline Retail and building analytics teams from the ground up. Following his Masters from JNU in Economics, Anirban started his career at Target and spent more than eight years developing in-house products like Customer Personalisation, Recommendation Systems, and Search Engine Classifiers. Post Target, Anirban became one of the founding members at Data Labs (Landmark Group) and spent more than 4.5 years building the onshore and offshore team of ~100 members working on Assortment, Inventory, Pricing, Marketing, eCommerce and Customer analytics solutions.

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