AlignMinds Technologies logo

Top 10 Programming Languages for AI Development

Recent studies show that businesses are investing more in artificial intelligence.

According to studies conducted by DataProt, 37% of businesses employ AI in their operations. The industry will be earning $126 billion by the year 2025 and the market value is expected to cross $267 billion by 2027.

Another study, conducted by Oberlo, states that 91% of top businesses have already invested in Artificial Intelligence. Also according to them, around 62% of customers are ready to share data if it improves their experiences with a business.

As artificial intelligence and related development are becoming more popular, the programming languages used for developing such software are also becoming popular.

If you are someone who has an interest in developing AI solutions, understanding the programming languages used for AI development will be compelling to you.

Best programming languages for AI development

When it comes to AI development, there are several programming languages you can choose from. Among them, here are major 10 programming languages that are used extensively in AI and machine learning development in 2022.

1. Python

Python is a high level, general-purpose programming language. It uses significant indentation to improve its code readability. Using language constructs and an object-oriented approach Python helps with developing clear and logical code for small to large scale AI projects.

Python was released in the year 1991 by Guido van Rossum. Ever since its inception, the language has been used in desktop apps, web apps, networking apps, scientific computing, machine learning apps and data science applications.

The libraries offered by Python such as Tensorflow, Keras, PyTorch, Scikit-learn, PyBrain and MXNet etc. make it one of the popular choices for AI development. Since Python offers rich text processing tools and uses modular architecture for scripting, it has also become a popular choice for Natural Language Processing (NLP).

A few of the leading companies that use Python include Google, Amazon, NASA, Reddit, Instagram, Intel, IBM, Facebook, Netflix, JP Morgan Chase and so on.

2. R programming language

R is a very popular programming language for statistical programming, especially data analysis and statistical computing. The language was created by statisticians Ross Ihaka and Robert Gentleman in 1993. As of March 2022, R is ranked at 11th position in the TIOBE index.

R is primarily written in C, Fortran and R itself. It comes with a command-line interface and offers support for multiple third-party user interfaces like RStudio and Jupyter.

R’s S heritage enabled it to have best-in-the class object-oriented programming facilities. R supports procedural programming with the use of functions and object-oriented programming with generic functions.

Due to its advantages, R is considered the primary programming language for statistical computations in domains such as biology, sociology, finance and medicine. The advantages of R can be extended through user-created packages that offer statistical techniques, graphical devices, import/export, reporting etc. The packaging system allows researchers to organize data, code and files in a systematic way for sharing and archiving. It is the ease of using such packages that drives the popularity of R as the best programming language for data science.

The alternatives to R programming language are SPSS, Stata and SAS, However, they are commercial statistical packages while R is a free software under the GNU General Public License.

Renjin and FastR used in the Java Virtual machines is a Java implementation of R programming language. The runtime engine “TERR” that is part of “Spotfire” is developed in R.

R is used by most of the leading companies including Facebook, Twitter, Google, Microsoft, Uber, Airbnb etc.

3. Java

Java is one of those programming languages that everyone has heard of.

This high-level, class-based, object-oriented programming language was designed in the year 1995 by James Gosling and became popular in the industry due to its write once, run anywhere (WORA) principle. WORA simply means that a compiled Java code can be run on all platforms that support Java without recompiling.

Java is one of the most used programming languages for client-server web applications. Even though it shares similarities with C and C++ in terms of the syntax used, Java has fewer low-level facilities than both.

Apart from web applications, Java is also used in Android apps, Artificial Intelligence and machine learning applications, search algorithms, server-side programming, neural networks and multi-robot systems. Its scalability, low dependencies, platform independence and support for Java Virtual Machines have made Java a popular general-purpose programming language.

When it comes to AI development, Java offers several libraries and frameworks such as Apache OpenNLP, Java Machine Learning Library, Neuroph, Deep Java Library, MLlib and so on.

Java is used by several companies including the noteworthy ones such as Google, Uber, Netflix, Airbnb, Instagram, Amazon, Spotify, Slack etc.

4. Rust

Designed by Graydon Hoare in 2010, Rust is multi-paradigm, a general-purpose programming language designed for performance and safety. Even though it is syntactically similar to C++, Rust guarantees memory safety unlike the former. Another benefit of Rust is that it offers memory safety without garbage collection and reference counting is only optional.

Rust offers low-level memory management as well as high-level features such as functional programming. Since it offers speed, performance and safety, Rust is gaining increased popularity day by day. It has been adopted and implemented by mainstream companies like Amazon, Dropbox, Facebook, Google, Microsoft and Discord. Google announced Rust as an alternative to C/C++ for their Android open-source project.

Here is a list of recent adoptions we have seen in the industry.

  • Microsoft Azure IoT Edge, a platform used to run Azure services and artificial intelligence on IoT devices, uses rust to create some of its components.
  • The blockchain platform Polkadot is written in Rust.
  • TerminusDB is written in Prolog and Rust
  • AWS’s Firecracker and Bottlerocket use Rust.
  • Google Fuchsia, an operating system by Google, uses Rust for its components.
  • Figma is written in Rust.
  • The Servo parallel browser engine developed by Mozilla in collaboration with Samsung is written in Rust.

5. Prolog

Prolog, which derived its name from “Programming in Logic”, is a logic programming language mainly used in artificial intelligence and computational linguistics. It was designed by Alain Colmerauer and Robert Kowalski in 1972.

Unlike many other programming languages, Prolog inherits first-order logic and is intended mainly as a declarative programming language. The logic is declared in the form of relations represented by facts and rules.

Even though Prolog was one of the first logic programming languages, hence one of the oldest, it still holds its position in the industry. There are several free and commercial adoption of Prolog such as Tabling (used in systems like B-Prolog, XSB, SWI-Prolog, YAP, and Ciao), hashing (used in WIN-PROLOG and SWI-Prolog) and Tail Call Optimization (TCO). 

Prolog has been mainly used as a primarily logic language for expert systems, term rewriting, type systems, automated planning, theorem proving and natural language processing. This programming language is best suited for an AI solution that features rule-based logical queries such as searching databases, voice control systems, and filling templates. IBM Watson is one such system. 

IBM Watson. Image credit:

6. C++

C++ is one of the well-known programming languages due to the popularity of C, the programming language it inherits from.

Designed by Bjarne Stroustrup as a general-purpose programming language in 1985, c++ has seen significant expansion over the years. Now it supports object-oriented, generic, and functional features besides low-level memory manipulation. 

The main advantage of C++ is its performance, efficiency, and flexibility as it was designed as a programming language for building resource-constrained software and large systems. The language is used extensively in building desktop applications, servers (mainly for e-commerce, web search and databases), video games and performance-critical applications such as telephone switches and space probes.

C++ offers several AI and ML libraries such as Caffee, Microsoft Cognitive Toolkit (CNTK), TensorFlow, DyNet, OpenNN, FANN, Shogun and mlpack library.

The popular companies that use C++ include Walmart, Google, Accenture, Twitch, Telegram and Lyft.

7. Lisp

Lisp, a name derived from “LISt Processor”, is the second-oldest high-level programming language still in use and is only one year younger than Fortran. Designed by John McCarthy in 1958, this family of programming languages has a long history with the presence of several distinctive dialects such as Racket, Scheme, Common Lisp and Clojure.

Designed primarily as practical mathematical notation for computer programs, Lisp later became the most favoured programming language for Artificial Intelligence. Several inventions in the field of programming are pioneered by Lisp and they include tree data structure, dynamic typing, conditionals, automatic storage management, recursion, self-hosting compiler, higher-order functions and read-eval-print loop. Apart from these, Lisp offers several features such as rapid prototyping, dynamic object creation, flexibility, garbage collection and information process capabilities.

CLML (Common Lisp Machine Learning Library), mgl, Antik and LLA are the popular AI and ML libraries offered by Lisp.

iRobot, The Mimix Company, NASA (in their PVS), Rigetti Quantum Computing, Grammarly, Mind AI, Carre Technologies, NuEcho, Kina knowledge, Emotiq and Anaphoric are a few examples of companies that are using Lisp in their products or operations.

Logo of Lisp programming language

8. Julia

Julia is a high-level, high-performance, dynamic programming language well suited for AI solutions that deal with numerical analysis and computational science.

Designed by Jeff Bezanson, Alan Edelman, Stefan Karpinski and Viral B. Shah in 2012, Julia supports concurrent, parallel and distributed computing.

Advantages of Julia include

  • It can direct call “C” and “Fortran” libraries without glue code.
  • Compiles all code by default to machine code before running it.
  • Automatic memory management/garbage collection
  • It uses easter evaluation
  • Offer libraries for floating-point calculations, random number generation, linear algebra, and regular expression matching.

Julia offers several packages for Artificial Intelligence and machine learning. Few of them are Flux.jl, Knet.jl, Mocha.jl, TensorFlow.jl, ScikitLearn.jl, TextAnalysis.jl, MXNet.jl, DecisionTree.jl, Merlin.jl, and LossFunctions.jl. Find the complete list here.

9. Haskell

Named after great logician Haskell Curry, Haskell is a general-purpose, statically-typed, purely functional programming language. Primarily designed for research, teaching and industrial application, Haskell boast of pioneering innovative features like type classes that enable type-safe operator overloading.

According to the number of Google searches conducted for tutorials, Haskell was the 28th most popular programming language in 2021.

The several features offered by Haskell include lazy evaluation, pattern matching, lambda expressions, list comprehension, type classes and type polymorphism. Since Haskell is purely a functional language, functions have no side effects.

Popular applications of Haskell include Agda (proof assistant), Cabal, Darcs (revision control system), Git-annex, Pandoc, TidalCycles, Cryptol, Facebook’s anti-spam programs and Cardano blockchain platform.

10. Smalltalk

This object-oriented programming language was specifically designed for constructionist learning. It is a dynamically typed reflective language which means that using Smalltalk, developers can create software programs that have the ability to examine, introspect and modify their own structure and behaviour.

Smalltalk’s reflective features help developers with advanced debugging in the most user-friendly way. In fact, Smalltalk ranked second in the list of “most loved programming languages” in the Stack Overflow Developer Survey in 2017.

Designed by Alan Kay, Dan Ingalls and Adele Goldberg in 1972, Smalltalk has influenced so many programming languages such as Python, Ruby, Java and Objective-C.

Even though it was created mainly for AI-related studies, Smalltalk lost its position in front of other popular AI programming languages such as Python and R. However, Smalltalk is picking up the pace by introducing more libraries for AI and ML development and natural language processing. For example, Pharo has a numerical package called PolyMath that is almost equal to NumPy of Python.

Due to its conciseness, object purity, simplicity and better OOP implementation, Smalltalk has started regaining the attention it always deserved as an AI language.


The adoption of artificial intelligence and machine learning is growing at a fast pace. There are several programming languages used in AI and ML development. However, languages like Python and R are the most popular. To meet the growing demand of the industry, there are several other programming languages that are expanding their capabilities to become the best AI programming language of tomorrow.

Technology Trends to Watch Out for in 2022

2021 saw many technology trends as a continuous response to the COVID pandemic that emerged in 2020. Industries were in shock during the first quarter of 2020. But towards the end of the year, most of the industries were able to take control of the situation and we saw somewhat an accelerated growth during the year 2021.

In 2021, most industries optioned for technology adoption and it helped them tremendously. The industries that took advantage of digital transformation included manufacturing, transportation, healthcare, education, financial services, media, and retail. Since customers were mostly confined within their homes, we saw some big jumps in emerging technologies in industries like education, media, retail, and healthcare.

2021 is already over and we are now in 2022. Most of us will be wondering what to expect this year especially in technology industry since it was the driving force behind all emerging trends for past couple of years. To help the curious minds, we have curated a list of emerging technology trends for the current year, 2022.

Major technology trends to watch out for in 2022


The word “automation” is not new to any of us. We have been hearing about automation and how different industries are adopting it to improve their productivity, efficiency, cut costs and boost profit margin. However, as different industries are seeking out more ways to adopt automation, automation is also seeing a diversification.

In the beginning, it was the manufacturing industry that recognized the benefits of automation. Later, the service industry also adopted automation in the form of CRMs, inventory management software, payroll software, invoicing software and so on. These days automation has reached every nook and cranny of a business. People have become familiar with terms like self-driving vehicles, autopilots, smart wearables, smart home notifications etc. We are also seeing an increase in consumer numbers for IoT devices as they are becoming more affordable and convenient.

According to McKinsey,

“By 2025, more than 50 billion devices will be connected to the Industrial Internet of Things (IIoT), generating 79.4 zettabytes of data yearly.”

We can expect more growth in the field of automation and IoT in coming years as the potential is limitless and we have only touched the tip of the iceberg.


Facebook renamed itself to Meta in October last year. The tech giant rebranding itself after a decade and a half reflects the potential of metaverse.  While AR (Augmented Reality) and VR (Virtual Reality) are not a new trend in 2022, the coming together of physical, augmented, and virtual world to form a single and seamless entity, where people can hang out with friends, meet new people and places, do shopping, participate in entertainment and professional activities alike, is something new and yet to experience. Of course, the idea has been lingering around for a while and we even had a chance to see few demos and experimentation, the Metaverse was still in its conception stage. But we can expect some breakthroughs soon especially since trillion-dollar companies like “Meta” have recognized that it is the future.

Enhanced Search Optimization

The pandemic forced so many physical stores to close down. Businesses around the globe, irrespective of their industry, discovered that it is difficult to find customers in traditional ways since movement of the people are mostly restricted. It forced businesses to migrate from offline business model to an online business model with a focus on websites and apps to connect with their customers.

However, the results were not promising since most businesses were out of reach for the customers. Their websites and apps failed to show up in search results and were undiscoverable for potential clients. It forced businesses to put more focus on search optimization and become discoverable for their customers.

Due to the comfort and convenience it offers, people are still preferring online shopping even after the restrictions are lifted. We can expect the trend to stay the same for a while at least until there is some incentives for customers to prefer the traditional way for shopping. So, currently businesses are forced to find new search and discoverability strategies to attract sales.

Decision intelligence

Decision intelligence is a new discipline that can help such organizations with their organizational decision-making process. It can support and enhance human decision-making using intelligence and analytics to inform, learn from and create a set of processes to find the right decision. It combines various disciplines like data science, engineering, social science, decision theory and managerial science. We will be seeing decision intelligence in action more often in the coming years.

Distributed business

A distributed business or distributed company is a business that has a remote workforce and consumers connected via digital technologies. It is a digital-first, remote-first business model that encourages hybrid workforce and virtual services to improve employee and consumer experience. Ever since the pandemic there is an apparent shift in employee and consumer preferences and distributed business model can help companies to meet the expectations of both.

Cyber AI

Hacking, breaches, data theft etc. are becoming widespread despite technological advancements. Hackers are leveraging the advancement in technology to find loopholes in systems and create novel ways to get access to them. In 2022, businesses need to be proactive than ever to counter such cyber threats.

Thankfully, artificial intelligence and machine learning help to build models that can learn their own and detect novel patterns in a system. Processes like “Anomaly detection” etc. are a big step towards achieving this goal. Such models can not only detect an unusual pattern, but they can also contain them, notify about such events to concerned parties and use the data to improve themselves.

Distributed ledger and Blockchain

Decentralization is happening in all fields. Data storage and processing are also undergoing a major transformation. The traditional, centralized databases are giving way for distributed ledger (shared ledger or DLT) and blockchain models that are more secure and safe.

Industries like finance and banking are taking full advantage of these technologies as they offer more efficient transactions. The transactions and their details are recorded in multiple places at the same time making them impossible to be lost.

DLT is still an emerging technology if we compare its potential to the current rate of adoption. Since it can help to deter issues like hacking, unauthorized access, data theft etc., we can expect it to become an emerging trend in 2022.


Businesses are moving from legacy environments to the cloud at a faster rate. The necessity to go virtual and remote forced most businesses to ditch legacy models and find alternative solutions.

Since the tech industry foresaw the rise of cloud a long time ago, most of the new solutions like productivity tools, businesses suits, even games and media services are already cloud-based. Along with the necessity to go for a decentralized and distributed model, the potential for much better compatibility and integration are forcing companies to build their infrastructure and solution using cloud tech.

Wordless Passwords

Are you someone who always click on the “forgot password” button every time you try to log in to a platform? If yes, here is good news. The traditional, character-based passwords are giving way to more sophisticated biometric passwords. The use of fingerprint, face recognition, iris scan and voice authentication etc. are becoming popular as an authentication mode. They are not only secure but also convenient compared to traditional passwords that are based on alphabets, numbers, and special characters that we always manage to forget.

Also, service providers like Google etc. are moving towards more convenient authentication methods like signing in with your phone or authenticator app where you do not have to remember any password or code but to tap on the matching code that appears on your device/app.

Fewer keys

The introduction of the Apple Pencil was revolutionary. Even though stencils were in use for a long time, Apple Pencil offers something more than a pencil. They are integrated very well with the devices and designed in a way that is convenient to users. It can undertake different functions based on pressure, tilt, the application that is currently open, double-tap, or for navigation and everything else including notetaking and drawing.

In short, we are moving from an era of keyboards and input tools to a new era that enables us to interact with devices just like how we interact with other human beings.


Technology is moving its focus from experience to immersion. Until now each component in a system had its own set of functions that focused on delivering a specific experience to users. However, the recent technology trends are moving towards immersive experience where each component is designed in a way to offer a realistic, more enjoyable and wholistic experience and eliminate any chances for interruptions. The vision is to narrow the border between the virtual and real world and deliver the experience the users want rather than they need.

The two industries that are more focused on this emerging trend are gaming and media. It is because these industries were always struggling to deliver “the right experience” to their users especially when the users’ interests span across history, science, and fantasy. For example, it always was a challenge for game developers to offer the experience of living in space or a treasure hunt in ancient times to its users even though the storyline and models were of the best quality. The fault was not in the quality of the design but the delivery of the experience.

Ever since AR and VR became more mature and there are significant improvements in rendering, physics, display and audio technology, the experience has become much better for the users. In 2022, we can expect this trend to become widespread and more industries adopting it to improve customer satisfaction.


There are some exciting technology trends we can expect in 2022. Some of the names associated with these tech trends may seem familiar to you. Even if they are familiar, we are yet to see the adoption of such technologies on a scale that is large enough to make an impact on our day-to-day life. 2022 seems like to be the year we are going to experience them in our regular life.

AlignMinds is an award-winning technology consulting company that specializes in product engineering in mobility and cloud platforms. We offer best in class consulting in web and mobile app development, AI, AR, IoT, cloud, blockchain and cybersecurity. Are you looking for a technology partner for your next project? Contact us now!