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Biggest AI and Machine Learning Trends that Will Shift Tech Investments in 2022

Machine Learning trends continue to enthrall analysts all over the world. It’s true that AI adoption is on the rise but the real push into 2022 comes from the evidence-based approach to building a more sustainable and human-friendly environment. According to a recent report, 56 percent of the global business leaders have stated AI adoption in at least one function. Leading AI companies such as NVIDIA, Microsoft, Google, Amazon Web Services (AWS), and Tencent Cloud made remarkable investments in the last 2-3 years to develop cutting-edge capabilities in AI Machine Learning, data science, and automation domains.

Today, artificial intelligence (AI) and machine learning (ML) trends have become the key barometers for industrial development, enabling organizations to progress toward becoming the most disruptive and revolutionary enterprises in the world. In less than 5 years, AI and ML technologies are ruling every aspect of business function, including Marketing and Sales automation, SaaS development, E-commerce, blockchain DevOps, Cloud modernization, Drones and UAVs, and Space tech. Sundar Pichai, the CEO of Google, had stated that AI will have an even greater impact on the evolution of humanity as a species than fire or electricity. It may be a bold remark, but AI’s potential is evident in how it has been applied to space exploration, climate change mitigation, and cancer therapy development.

It may be impossible to envision the consequences of machines making judgments faster and more accurately than humans, but one thing is certain: new trends and discoveries will continue to emerge in 2022, pushing the boundaries of AI and machine learning.

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Here are the top eight AI and machine learning trends to watch in 2022.

A Productive Workforce

Since the inception of AI and machine learning, there have been fears and concerns that these disruptive technologies could supplant human labor and even eliminate some jobs. Working alongside machines with smarter cognitive functionality, on the other hand, increased individuals’ abilities and skills as organizations began to adopt these technologies and introduce AI/ML literacy into their workforce.

Companies that invest in AI by evaluating machine learning trends definitely stand a better chance when it comes to reaping ‘measurable benefits’ from AI investments.

For customer-facing teams, AI’s effect is far more enriching. AI and machine learning trends incline heavily toward delivering a better and more personalized customer expereinces.

According to PwC’s report, companies that have fully embraced AI see bigger and better outcomes in terms of their improved decision-making cost savings, and a rise in productivity.

Top AI adoption centers in a productive workforce management plan involve the use of high-tech capabilities for:

  • Contact center automation
  • Services center optimization
  • Product engineering, innovation, and features upgrades
  • Predictive services management
  • Predictive intelligence and business analytics
  • Customer segmentation using AI
  • Voice search for Enterprise Content discovery
  • Risk Modeling and analytics
  • Fraud detection
  • Back-office automation using OKRs and image recognition

For example, in marketing, AI/ML tools are already being used to help firms identify possible leads and the business value that potential consumers may provide.

Furthermore, AI and ML technologies in engineering provide predictive maintenance, which is the ability to predict and inform the servicing and repair needs of enterprise equipment. Furthermore, AI/ML technology is commonly employed in disciplines of expertise, such as law, to sift through ever-increasing volumes of data and locate the most relevant information for a given task.

More AI means more benefits
More AI means more benefits (Source PwC)

The Metaverse 

Immersive content is a huge market for global AI centers. Marketers are spending more on creating ‘metaverse’ assets using what we call headless commerce capabilities, built using blockchain-based content management systems. Many startups are heading into the metaverse universe with headless e-commerce capabilities designed using AI and machine learning.

The metaverse is a virtual world, similar to the internet, where people may collaborate and have immersive experiences while working and playing together. Since Mark Zuckerberg, Facebook’s CEO, spoke about combining virtual reality (VR) technology with the Facebook platform, the concept of the metaverse has been a hot issue.

Without a doubt, AI and machine learning will be a metaverse lynchpin. These technologies will enable a company to construct a virtual world in which its users may interact with virtual AI bots and feel at ease. These virtual AI creatures will help people select the appropriate products and services, as well as relax and unwind by playing games with them.

Natural Language Processing (NLP)

NLP is one of the most widely utilized AI technologies nowadays. As robots begin to understand human languages, we can now just converse with them, this technology dramatically lowers the need for typing or interacting with a screen. Furthermore, AI-enabled gadgets can now convert real human languages into computer codes that may be used to run applications and programs.

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OpenAI’s release of GPT-3, the most advanced and largest natural language processing model ever constructed, marks a significant step forward in language processing. It has roughly 175 billion ‘parameters,’ which are data points and variables that robots use to process language. GPT-4, a more powerful successor to GPT-3, is currently being developed by OpenAI. 

This advancement brings us closer to constructing machines that can learn the language and have conversations that are indistinguishable from human talks.

Sentiment analysis, process description, machine translation, automatic video caption production, and chatbots are some of the NLP technologies that are projected to gain prominence.

Improved Cyber-Security

The World Economic Forum recently said that cybercrime is a greater threat to society than terrorism. Cybercrime becomes rampant, and cybersecurity solutions become sophisticated, as more intelligent but complex robots connected to a large network gain control of every aspect of our life.

AI and machine learning tools have the potential to help solve this problem. AI/ML algorithms, for example, can scan greater network traffic and spot patterns of illicit virtual activity. This is likely to be the site of some of the most significant AI/ML technology advances in 2022.

Open Source DataOps: Low-code and No-code Technologies 

In many companies, a scarcity of skilled AI developers or engineers is a fundamental impediment to AI adoption. Technologies like no-code and low-code come to the rescue. In theory, these solutions seek to provide easy interfaces for developing highly complicated AI systems.

Users can now create web pages by dragging and dropping graphical elements together using web design and no-code user interface (UI) tools. Similarly, no-code AI enables developers to create sophisticated AI systems by simply combining pre-built modules and feeding them industrial domain-specific data. In addition, NLP, low-code, and no-code technologies will eventually allow us to instruct complicated machines using our speech or written commands. AI, machine learning, and data technologies will become “democratized” as a result of these breakthroughs.

The Creativity Domain

Humans are creative by instinct. With machine-level creativity, we are creating a whole new galaxy of tech-enabled features for our lives and businesses. As a result, artificial intelligence is getting closer to being as intelligent as humans. Cognitive intelligence to create artificial neural networks or artificial human brains have expanded the boundaries of data science in the new year 2022.

As we study more about NFTs and user-generated digitally-enhanced artistic content created using gamification channels and mobile applications, we can only imagine what the future holds for AI-based content creation. AI can already be used to generate art, music, plays, and even video games. The introduction of GPT-4 and Google Brain in 2022 will change the frontiers of AI and machine learning capabilities in the realm of creativity. Our artificially intelligent machine pals can now be expected to display more natural creativity.


More firms will automate multiple yet repetitive operations involving vast volumes of information and data in 2022, thanks to AI and machine learning technologies. Robotic process automation (RPA) and intelligent business process management software will be used to increase the pace of automation in numerous industries in the future years (iBPMS). This AI and machine learning movement enable organizations to reduce their reliance on human labor while also improving the accuracy, speed, and dependability of each process.

AI at The Quantum Level

AI-powered by quantum computing will soon be used by modern enterprises to address complicated business challenges faster than classical AI. Quantum AI makes data analysis and pattern prediction faster and more accurate. As a result, it aids various firms in recognizing unanticipated issues and developing effective solutions. As a result, quantum AI will transform a wide range of industries, including healthcare, chemistry, and finance.

AI/ML Future Growth

All of these AI and machine learning trends will soon have an impact on businesses all over the world. These disruptive technologies have the potential to change every industry by supporting organizations in accomplishing their business goals, making critical decisions, and generating creative goods and services. 

By 2027, the AI/ML sector is predicted to increase at a CAGR of 33%. According to estimates, by 2022, firms would have implemented at least 35 AI initiatives in their operations.

Data specialists, data analysts, CIOs, and CTOs should consider taking advantage of these opportunities to extend their existing business capabilities and leverage these technologies.

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