Today we are witnessing a massive surge in the adoption of artificial intelligence across industries and this is set to impact workplaces around the world.
To leverage the power of AI, companies require skilled professionals and AI experts. Apart from hiring AI experts, companies must also upskill their employees to harness the power of AI technology. Upskilling the staff in AI will allow companies to become tech-driven and automate tasks.
The emergence of large language models (LLMs) and generative artificial intelligence tools (like ChatGPT) has opened the doors to new fields and job opportunities. While AI may replace many manual/repetitive roles, it has also introduced new roles that require advanced technical knowledge.
According to an IBM report in 2022, about 60% of Indian and Chinese IT companies use AI applications. Upskilling is the best way to take advantage of the widespread use of AI.
In-demand AI skills of 2023
Let’s take a look at some AI skills that are becoming popular this year. Empower your employees with these game-changing skills and tools.
Programming languages
You may have heard about coding languages such as Python and Java but did you know they are also popular in the field of AI? Python is a simple but powerful programming tool that helps in data analysis. Java, R language, and C++ can also be used for machine learning and statistical analysis.
Neural networks
Neural networks are a series of algorithms that mimic the working of the human brain and identify relationships from vast amounts of data. There is a wide range of applications for this, such as market research, risk assessment, medical diagnosis, and facial recognition.
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Deep learning
Deep learning is another popular part of machine learning, which is based on neural networks. It combines many neural networks to help in image classification, speech recognition, and natural language processing without human intervention.
Deep learning analyses large data sets, identifies images and makes predictions. So, it can be incorporated to create chatbots and translations and provide personalised experiences for users.
Big data
With the help of algorithms, Big Data extracts chunks of data to find valuable insights that can help optimise one’s business. This is also referred to as data mining as information is filtered to be analysed.
Data science
Data science is the field that primarily deals with Big Data. It is used to analyse trends and find out meaningful insights from the data sets extracted. This skill involves using principles of mathematics, statistics, computing, and artificial intelligence in order to study the data. Businesses use the insights provided to enhance their operations.
Natural language processing
Have you wondered how chatbots and voice assistants like Siri or Alexa are made? It is all thanks to NLP or natural language processing. NLP is a branch of AI that deals with assisting computers with the ability to understand human linguistics in spoken and written (text) forms.
In simple words, it helps computers understand natural language just like humans do. This field has a wide range of applications in business intelligence and medical research.
Key soft skills for a career in AI
As an AI professional, you need to know both technical and communication skills to thrive in what you do. Here are some abilities you must have to build a career in the AI industry.
Critical thinking
Critical thinkers are efficient in pointing out mistakes and paying attention to precise details. Questioning the information given to you helps you identify any areas that can be improved. This ability can be handy while dealing with technical problems or managing team projects.
Creative mindset
AI is not all about technology but is also about how uniquely it can be employed. So, AI professionals often need to brainstorm creative ways to come up with a multitude of solutions for a problem.
Cooperative attitude
Just like in many other roles, AI professionals too need to have strong communication, teamwork and cooperative skills. The skills are especially useful when working with a team on a project. They can boost productivity as everyone is aligned and in sync with the work.
Ability to handle pressure
Data scientists work on tight deadlines to derive real-time insights and statistics. This means professionals must work well under pressure without letting time constraints affect their focus.
Edited by Swetha Kannan
