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  • Writer's pictureAndriy Link

AI vs ML vs DS

In the last year, there has been a rise in the popularity of Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS). Most companies have even started planning to engage in digital transformation using each of the technologies mentioned. Gartner believes that 91% of businesses are on the verge of implementing a digital initiative, and about 87% of senior business leaders prioritize digitalization as the biggest perspective to grow.

The interest towards AI, ML, DS over past 7 days all around the world.
Google Trends 2023

AI, ML, and DS are concepts that are closely interconnected, at least at first glance. Therefore, Sencury would like to make these notions a little clearer for you to get the most value from them.


What Makes AI, ML, and DS Different?

Artificial Intelligence (AI)

Artificial Intelligence, or AI for short, is the ability of a machine (computer) to think, learn, and act like a human. Hence, a computer copies human behavior in a way that is smart and intelligent.

Artificial Intelligence, or AI for short, is the ability of a machine (computer) to think, learn, and act like a human. Hence, a computer copies human behavior in a way that is smart and intelligent.

What is AI Used For?

The main use cases of Artificial Intelligence include:

  • Customer experience

  • Supply chain

  • Human resources

  • Fraud detection

  • Knowledge creation

  • Research and development

  • Predictive analytics

  • Real-time operations management

  • Customer services

  • Risk management and analytics

  • Customer insight

  • Pricing and promotion

If you choose AI for your business enhancement, you will receive a better customer relationship, cost-effectiveness, increased efficiency with operations, higher security and safety, and focus on new products and services.

Read more about AI here: Top Information Technology Trends 2023


Machine Learning (ML)

Machine Learning, or ML for short, is the subfield of AI that focuses on giving computers the ability to learn from examples without being previously programmed.

Machine Learning, or ML for short, is the subfield of AI that focuses on giving computers the ability to learn from examples without being previously programmed.

What is ML Used For?

There are lots of Machine Learning applications. You can train algorithms for:

  • Image recognition

  • Speech recognition

  • Automatic language translation

  • Medical diagnosis

  • Stock market trading

  • Online fraud detection

  • Virtual personal assistant

  • Email spam and malware filtering

  • Self-driving cars

  • Product recommendations

  • Traffic prediction

If you choose ML for your business growth, you will receive advancements and continuous improvement, automation of almost everything, identification of trends and patterns per your need, and a wide range of applicability.


Data Science (DS)

Data Science, or DS for short, is a broad field of disciplines that uses scientific methods, processes, algorithms, and systems to extract all the possible knowledge from data that is structured or unstructured.

Data Science, or DS for short, is a broad field of disciplines that uses scientific methods, processes, algorithms, and systems to extract all the possible knowledge from data that is structured or unstructured.

What is Data Science Used For?

Everything that is related to data and data analysis is, in one way or the other, a part of the data science routine. For example,

  • Mathematics

  • Statistical modeling

  • Statistical computing

  • Data technology

  • Data research

  • Data consulting

  • Real-world applications

  • Advanced computing

  • Visualization

  • Hacker mindset

  • Domain expertise

  • Data engineering

Applying to DS any business can benefit from the ease of job hunting, product customization, cost and time optimization, and advantages of AI.


AI vs ML vs DS: How they Work Together?

Data Science uses AI and ML to interpret a type of old data called historical, recognize patterns, and make predictions. Here, AI and ML offer data analysts valuable insights to work with.


With the help of ML, Data Science achieves the next level of automation. Moreover, these two cooperate in many ways. For example, Data Science produces statistics. ML is dependent on data as ML algorithms are trained on data to produce better input (predictions).


Key Differences in AI, ML, and DS

If to visualize AI, ML, and DS in the form of robots, Machine Learning will be the smallest one as it is a subset of AI and a tool for DS. Artificial intelligence will be the middle robot as it includes ML and helps DS analysts with valuable insights. Data Science is the biggest robot, as it leverages AI and ML to produce research, industry expertise, and statistics for better business decisions.

If to visualize AI, ML, and DS in the form of robots, Machine Learning will be the smallest one as it is a subset of AI and a tool for DS. Artificial intelligence will be the middle robot as it includes ML and helps DS analysts with valuable insights. Data Science is the biggest robot, as it leverages AI and ML to produce research, industry expertise, and statistics for better business decisions.
DS vs AI vs ML

Sencury’s Services of AI, ML, and DS

Artificial Intelligence and Machine Learning are the future technologies that will shape many industries as well as enhance their business workflows. Sencury's team focuses on AI and ML projects with special attention to customer requirements, reasoning, learning, and goal-oriented outcomes. Together with DS, these technologies allow you to make better decisions and enhance performance optimization. Everything depends on the technology that suits your case best. Each can give you a great headstart for growth.


Choose Sencury to become a market leader and essentially grow your business. AI, ML, and DS are the future of technological progress and automation processes.

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