Page 56 - 2617_JSSPS_C-8

Let us discuss about some of them in detail.

Soft Skills

It is said that AI can replace hard-skilled employees and employees with greater soft skills will always
remain in demand. Empathy, leadership, collaboration, creativity are some key skills that will always be
in demand.

Data literacy skills: It is said that ‘There is no good AI without good data’. AI analysis can be biased
if the data source is not reliable. Employees with strong data literacy can recognise the wrong
patterns which will be useful for AI training.

Collaboration skills: Organisations expect their employees to work in a collaborative manner.
Departments like Design and Marketing need to collaborate with each other to reach to user
experience and develop machines accordingly.
Critical thinking skills: The ability to think critically will be more important for employees, as such
people will come up with innovative ideas, solve complex problems using logic and reasoning.

Leadership skills: The workplace in future will have project-based teams, remote teams with
flexible structure unlike present day hierarchical structure. So, individuals will need traits like being
inspiring, helpful and the best versions of themselves to be better leaders.

Adaptability skills: With fast changing scenarios specially the advancement taking place in the field
of AI, employees with the ability of flexibility and adaptation will be much more at peace and will
take these developments as an opportunity to grow.

Technical Skills

Technical skills are the abilities or knowledge used for practical tasks in the field of science, technology,
engineering, etc. Following are some of the technical skills required in the field of AI:

Programming languages: In the field of AI, one must know how to work with programming
languages which is essential in order to design various machines. Java, C, C++, R, Python, etc. are
examples of such languages.

Machine learning algorithms: Machine learning is an essential aspect for creating AI system as
they enable the machine to learn from its past experiences without being explicitly programmed.
Thus, one must be proficient in such machine learning algorithms.
Artificial neural networks: Such networks mimics the functioning of the human brain. An
AI professional is expected to learn how to solve complex problems such as face recognition,
handwriting recognition and pattern recognition.

Mathematics and algorithms: Applied mathematics and algorithm is considered a necessary skill
in the field of AI. They should be familiar with problem-solving skills and analysis skills, along with
the knowledge of mathematics to solve complex AI-related tasks.

Signal processing techniques: AI systems are fed with huge chunks of data in various formats. In
order to extract meaningful information one must acquire the knowledge of solving problems using
advanced signal processing algorithms.

Premium Edition-VIII
54