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The Rise of AI in Management: What Job Seekers Should Know

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Author:anushka singh

Published: 5/19/2025

Last Updated: 7/3/2025

- By Anushka Singh

Artificial intelligence, or AI, is one of the fastest growing technologies today. The integration of AI in management jobs has been rapid. Here is what job seekers should know.


What is AI? 

Artificial Intelligence, or AI, refers to the technology that enables computers and other machines to perform complex human-like tasks like problem solving and decision making. It is a broad term that includes a wide range of technologies such as natural language processing [NLP] and machine learning.     


Uses of AI 


Type of Application

Uses

General Application

Automating tasks

Improving efficiency

Data handling

Personalise user experiences

Deep analysis

 

 

Specific Application

Healthcare: medical diagnosis and preventive solutions  

Finance: fraud detection and risk assessment.

Marketing: personalise marketing campaigns and measure campaign performance.        

Business Intelligence: data collection, data analysis and data visualisation. 


 


AI in management jobs is generally used with the aim of improving overall business performance. Its applications range from project management to recruitment and hiring.


Types of AI 

Artificial intelligence, or AI, is generally classified on the basis of its capabilities and technologies. Some of its major types include:  

1. Capabilities based Artificial Intelligence 

  • Narrow AI: also called Weak AI. As the name suggests, Narrow AI is used to perform specific tasks that are designed within a narrow context.  


  • General AI: also called Strong AI. It can use previous learning and training to perform human-like capabilities.


  • Superintelligent AI: Superintelligent AI is the most advanced form of capability-based artificial intelligence. It is capable of outperforming human beings on all parameters, including accuracy, problem-solving, creativity and more.

Most forms of Strong AI and Superintelligent AI are still in the research and development [R&D] stages. 


2. Technology based Artificial Intelligence 

  • Machine Learning: Machine learning, or ML, uses data to make analysis and predictions. ML generally runs on algorithms that require little to no programming. Example: the Instagram algorithm runs on Machine Learning.


  • Natural Language Processing: Natural Language Processing, or NLP, is capable of understanding, interpreting and emulating human language. Some common uses of NLP include translation and chatbots.  


  • Expert systems: the main job of expert systems is to solve problems and have decision-making capabilities the way humans do. This type of AI tends to emulate humans that are experts in their sector or domain.   


  • Computer vision: computer vision AI uses deep learning to analyse and interpret the visual world in a human-like way. It relies on techniques such as image processing.


Other noteworthy types of AI include:

  • Reactive machine AI: Reactive Machine AI is used to perform extremely specific tasks. It doesn’t retain memory.


  • Theory of mind AI: Theory of mind AI is capable of understanding human emotions and beliefs. At this stage, it is still more of a theoretical concept.  


  • Limited Memory AI: Limited Memory AI uses data, both past and current, for decision-making processes. It tends to have a short-term memory.   


How AI is affecting management jobs 

AI in management jobs has undeniably been a game changer. Here’s how – its impact has been both positive and negative. 


Impact of AI in Management – the good and the bad


Pros

Cons

Automation: AI has been extremely helpful in automating regular tasks that are more repetitive in nature.

Job Security: Many companies have replaced their existing employees in favour of AI. Hence, it threatens job security.

Improved accuracy: AI tends to perform tasks with more accuracy and efficiency.

Ethical implications: there have been cases of AI plagiarising existing work. While other people have expressed concerns about the safety and security of the data that AI is collecting.  

Lack of bias: Human judgements can easily be clouded with emotions or biases. But AI’s judgement is more objective in nature due to lack of bias. 

No scope for improvement: Humans can always improve with more training and development. But the quality of AI’s output remains the same, so there is little to no scope for improvement.  

24/7 availability: Humans normally work only in their office hours. But AI is always available, irrespective of office hours.  

Lack of creativity

Better user experience: AI can use past data and consumer behaviour to optimise the user experience.

No human touch: In many jobs such as marketing, sales and customer service, people still prefer to have a human touch. AI doesn’t have that.



Adapt with the rise of AI in management: how to keep up 

Despite its widespread integration across different industries, AI can’t completely replace humans. Here’s how people in management jobs can adapt to the rise of AI:  

  • Upskilling regularly: AI has created the demand for new skills such as AI literacy and data analysis. By learning these skills, people can gain an upper hand.


  • Learn by trial: Whenever possible, managers should seek out projects that involve working with AI to get more familiar.


  • Collaboration: Collaborate with experts from the AI field on a regular basis. And also try to be actively involved in AI-related communities.  


  • Growth-orientated mindset: Mindset matters a lot in management jobs. So, instead of viewing AI in a negative light, think from the perspective of learning and growth opportunities.  


  • Organisational culture: As managers, make attempts to create an organisational culture that fosters innovation and growth. Then, employees will be open to working with AI.


  • Address AI-related concerns: Implement ethical frameworks and other relevant tools to address all the concerns that employees have about artificial intelligence.  

 

Conclusion    

AI and humans should work together in harmony, instead of over reliance. With continuous learning and upskilling, this advanced technology can be of great help for those in management jobs.   





Frequently Asked Questions (FAQs)

Q1: How is AI trained?

Ans: AI is fed with large data sets and then asked to produce results. Some common training techniques for AI include supervised learning, semi-supervised learning, unsupervised learning and deep learning.

Q2: Can I learn AI without a coding background?

Ans: AI does require a coding language. You can use online courses to get basic programming knowledge.

Q3: Is AI safe?

Ans: While AI does have some valid safety concerns, you can easily mitigate these risks by having proper safety measures in place.

Q4: Will AI replace any jobs?

Ans: It depends on the nature of the job. While AI has definitely automated some roles, it has also generated new jobs like automation consultants and data scientists.

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