Among the numerous emerging technologies dominating the business landscape, two globally embraced technologies are AI and Machine learning.

However, one of the most common predicaments around artificial intelligence and machine learning is that people consider machine learning (ML) synonymous with artificial intelligence. But in reality, machine learning is a subset of AI, aiming to enhance the overall proficiency of the AI technology by equipping it with advanced learning capabilities and responsiveness as businesses increasingly adopt IoT-based technologies and solutions to improve data intelligence, better comprehend data, and making data-driven judgments that reciprocate business value and growth.

machine learning statistics

Further, looking at the predictions, it’s easy to conclude that ML technology will expand its capabilities and dominate the coming year 2023 by playing a promising role in some of the most exciting innovations. As for business leaders, it’ll become increasingly important to leverage machine learning in business, become data intelligent and responsive, and have a competitive advantage in the business landscape.

Therefore, to help business leaders better understand the capabilities of Machine Learning in the coming years here’s a detailed rundown of some of the most promising Machine Learning trends we can expect in 2023-24.

Top 7 Machine learning Trends 2023-24

machine learning trends 2023

1. Foundation Models

In recent years, Foundation Model is one of the artificial intelligence models that have gained traction.

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For those who aren’t aware of Foundation models, let us tell you.

A foundation model is a deep learning AI algorithm pre-trained with pervasive data sets.

In contrast to narrow artificial intelligence (narrow AI) models that only perform one task, foundation models are fine-tuned and trained with numerous data varieties to perform multiple discrete tasks and seamlessly transfer knowledge from one task to another.

Considering the increasing adoption of technologies to derive and process data, one of the most notable trends for the coming year will be an accelerated pace of Foundation Models, wherein AI projects become more manageable and more scalable for large enterprises to execute.

2. Multimodal Machine Learning

Multimodal AI, or Multimodal Machine learning, is an emerging trend with the potential to revolutionize the entire AI and machine learning in the business landscape.

Simply put, Multimodal machine learning is primarily a vibrant multi-disciplinary research field that suggests that the world around us can be experienced in multiple ways (called modalities). Thus, the technology aims to build computer agents with more innovative capabilities, from understanding, reasoning, and learning to leverage multiple communicative modalities, including linguistic, acoustic, visual, tactile, and physiological perceptions.

Even though the concept is new, with leaders gradually realizing its potential of enhancing the overall efficiency of AI technology, multimodal machine learning is another machine learning trend that we will witness prospering in 2023-24.

3. Metaverse

Moving into Industry 4.0, the line between our physical and virtual lives continues to blur, leading businesses to another potential technology of the digital landscape – Metaverse.

As Metaverse proffers unprecedented ways for businesses to interact and collaborate with end-users virtually, in addition to supporting an entirely new virtual economy where users can engage in numerous brand activities, tapping into the Metaverse will increase customer engagement, thus resulting in enhanced acquisition and growth.

And amidst the accelerating adoption of Metaverse, AI and Machine learning will play a crucial role in bridging the gap between the physical and virtual worlds as AI will help create virtual environments, dialogue, and images by using NLP, virtual reality, and computer vision. In contrast, Machine learning will enable a seamless analysis of virtual patterns, help automate distributed contracts and distributed ledgers, and support other blockchain technologies to allow virtual transactions.


4. Low-Code or No-Code Development

According to numerous studies, enterprises leveraging AI and machine learning will support the corporate economy in 2023-2024. However, for businesses planning to benefit from emerging technologies, one of the significant challenges would be the intrinsic skill gap.

But since every challenge has a solution, the need for the right tech talent will be bridged by another emerging AI and Machine learning trend – Low-Code, No-Code Machine Learning Platforms.

machine learning low code no code

Employing Low-code/no-code machine learning platforms will empower businesses to utilize the power of machine learning and build robust AI applications from pre-defined components. Thus paving the way for intelligent, efficient, agile, flexible, and automated app development.


5. Transformers or Seq2Seq Models

Another AI and Machine learning trend that we will witness rising is Transformers, a.k.a Seq2Seq models. Seq2Seq models are primarily a type of artificial intelligence architecture that enables seamless transduction (or transformation) of data using an encoder and decoder and then gives out another output of the data in the form of an entirely different sequence.

Simply put, transformers are widely utilized in natural language processing tasks and analysis of the sequence of words, letters, and time series, to cater to complex Machine Language problems like Device Translation, Question Answering, creating Chatbots, Text Summarization, etc.

6. Embedded Machine Learning

With the rising adoption of IoT technologies, automation, and robotics, embedded systems have gained even more importance, and in the coming years, we might witness a more expanded utilization of this emerging machine-learning phenomenon.

Embedded machine learning (or TinyML) is initially a subfield of machine learning that enables the flawless functioning of machine learning technologies on different devices. Simply put, running machine learning models on embedded devices to make more informed decisions and predictions is termed embedded machine learning.

The embedded machine learning system is far more efficient than cloud-based systems and proffers various benefits, from reducing cyber threats and data theft and economizing the bandwidth and network resources to eradicating the data storage and transfer on cloud servers.

7. Machine Learning in Healthcare

We all might agree that healthcare is an ever-evolving industry. New technologies and tools are introduced constantly to pace the entire healthcare industry and its functioning.

As the ability to find and analyze patterns and insights by leveraging machine learning in healthcare gains traction and global adoption, in 2023-24, healthcare providers will have access to many more opportunities of taking a predictive approach to building a unified system empowering improved diagnosis, drug discovery, efficient patient management, care delivery processes.


Gartner’s Top Technical Segments Employing Machine Learning Trends in 2023

During a recent conference, Gartner and numerous renowned tech analysts contemplated the primary trends we might witness in 2023, especially those deriving economic and technological changes.

Amongst the others, the top trends employing machine learning were:

1. Creative AI and Machine Learning

One of the significant trends that gained popularity in 2022 was the utilization of AI for generative texts, code, images, and even videos. Continuing the rising popularity, experts have predicted that creative Ai and machine learning for fashion, creativity, and marketing will again be in high demand for various industry implementations in 2023.

2. Distributed Enterprise Management

When the pandemic made it imperative for enterprises to shift towards a hybrid working model, managing the diversified workforce and efficiency became one of the significant challenges for IT leaders. Considering the current work perceptions, Gartner predicts that AI and Machine learning will help companies manage their workforce and efficiency and grow with diversified forces.

In fact, according to Gartner, 75% of companies can increase their income by 25% with distributed enterprise compared to standard companies.

3. Autonomous systems

The coming year will pave the way for the rising demand for Autonomous systems, i.e., Robust software platforms equipped with the ability to self-manage and self-learn by dynamically reading, analyzing patterns, and data and adapting to algorithms using machine learning technology.

4. Hyper-automation

Another prediction for 2023 by Gartner elaborates on the rising need to become sustainable by moving towards automation and adapting to new technologies and tools. And since automating mundane tasks and complex business operations will require data, patterns, and analysis, workplace innovation will certainly only be possible by employing AI and machine learning in business.


5. Increased focus on Cybersecurity

The advent and adoption of tools and technologies have made enterprises and their IT infrastructure vulnerable to cyber attacks. Thus Gartner predicts that the coming years will bring significant focus on cybersecurity and states that in 2024, the business with responsive and cyber-intelligent operations and processes will be able to reduce cyber financial losses from individual situations by 90%.

Wrapping it Up!

With all of that read, it’s no exaggeration to conclude that AI and Machine Learning will be two of the most rapidly evolving technologies expanding their reach and capabilities.

As for business leaders who are planning to tap into the intricacies of both the promising technologies – AI and Machine Learning, the best way is to get in touch with one of the top digital transformation consulting firms, with a proven track record of helping leaders leverage the best of technology for their business.

At Copper Mobile, our expert business transformation consultants can help leaders explore potential opportunities to put forward their first step toward employing AI and machine learning in business and improving overall efficiency, productivity and revenue. Reach out to us today!