6 Era Altering AI And ML Trends To Watch Out For In 2022

6 Era Altering AI and ML Trends to Watch Out for in 2022

by Vatsal Ghiya — 3 years ago in Artificial Intelligence 5 min. read
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Artificial Intelligence doesn’t need to be a grim topic to discuss. Replete with possibilities to become the most transformative tool in the years to come, AI is fast shaping into an assistive resource instead of staying on course as an overwhelming tech. Clubbed with Machine Learning algorithms and principles of Data Mining, AI is rapidly moving towards a summit way too steep for human contemplation.

But then, AI and Machine Learning discussions need not be as complex as the tech itself. AI, in its entirety, is expected to be an industry and business commonplace in the next few months to come, and therefore, it is important to check out some era-altering current trends in AI that might gain a lot of traction moving into 2022.

What is The Basis for Enlisting Recent Trends in AI in 2022?

Tech trends are perceptive stepping stones that give us a sneak peek into the future. For enlisting AI and ML trends in 2022, it is therefore important to understand that global firms are already contemplating AI-driven projects over the course of the next year, and riding on these positive speculations, the AI and ML market seems to be riding rapidly towards the $9 billion market valuation.

And for a tech space as big as this, it is only appropriate to know some of the raging trends in advance to pre-empt innovation faster than most.

6 Future AI Trends that Require Detailing

The concept of machines evolving beyond contemplation and being able to think independently is already huge. But then, trends are better descriptions of how machine learning and thinking abilities can actually make their presence felt in the real world.

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Trend 1: Augmented Workforce and Intelligence

Have you ever come across a thought that what would happen if machines become intelligent enough to replace humans, especially when the focus is on amplifying workforce productivity? Well, that might be a thing to worry about in the future. For now, at least in 2022, we might see the evolution of augmented workforces, a space where humans and intelligent machines will coexist.

Unsure about how an augmented workforce would pan out! Here are the key pointers relevant to the same:

  • Cohesive cognitive functionality, with machines helping humans grasp the concepts better
  • Quicker and more accurate lead generation
  • Pre-emptive maintenance schedule for industrial components
  • Faster information procurement
  • Generation of smarter tools for eliminating errors
  • Better business forecasting
  • NLP-powered fraud detection systems
  • Better aggregated financials

Trend 2: Improved Healthcare

Also, the following benefits of an augmented workforce might vary depending on the industry you plan on influencing with AI and ML insights. On digging deeper, we would see that augmented workforce and augmented intelligence also have roles to play in Healthcare AI, with doctors benefiting significantly from faster threat detection and intelligent imaging resources.

One such use case has to be the insanely accurate CT scanning space, where AI can be an instrumental resource to improve speed and lower overall costs. However, efficient data annotation services are important to consider for this trend to hold.

Also, with virtual healthcare getting a more persistent nod in the post-covid era, virtual monitoring and crowd detection technologies are expected to work hand-in-hand with the realigned healthcare domain.



Trend 3: Conversational AI and Hyper Automation

As 2021 draws to an eventful end, 2022 might just see companies focusing way more on data quality. While the approach to training AI and ML models still primarily hinges on data quantity, with credible data collection and annotation firms coming into the picture, quality will also be a factor.

And if a company plans on launching conversational AI models like Siri and Bixby, it would be important to strike the perfect balance between volume and quality to make the models successful.

And is Hyper Automation even a word? Well, it would be, in 2022, courtesy of the AI and Data Science confluence. And if you aren’t privy to the more technical terms, Hyper Automation is more about seamless task automation with advanced technologies put to use, more so with Conversational AI models to assist.

Coming to the tech stack forcing the Hyper Automation revolution, it all boils down to RPA (Robotic Process Automation), ML, Cognitive learning, and obviously, AI. Also, if you are into specifics, this intelligent form of automation is expected to be an asset in:

  • Driving faster system integrations
  • Improving employee productivity
  • Amplifying the entire customer support setup with the integration of intelligent chatbots
  • Facilitating conversation and intent analysis to understand customer sentiments better

Trend 4: AR, VR, and the Metaverse

The concept of Metaverse and its connection to Web 3.0 is making companies reinvent the wheel. And with 2022 already knocking at the doors, the focus will initially be on developing the best Augmented and Virtual Reality offerings to be more Metaverse-relevant.

And what’s heartening to see is that even today, almost 90% of the top brands are stoked enough to incorporate AR & VR tech for pushing marketing campaigns. With experienced service providers offering better AR & VR data collection and annotation services, Augmented and Virtual Realities will soon rival the reality we are currently inhabiting.

Trend 5: Improved Focus on Data Annotation

Did we just say data annotation? Yes, we certainly did, as data labelling will hold the key to better AI and ML models in the months to come. But that’s not it. Data annotation, despite being very much there, is still a sluggish and time-consuming process. In 2022, riding on the innovations adopted by leading data annotation firms, the process of labelling will shift towards a more automated format.

The focus, therefore, will be on speed labelling, smart validation of data sets, and pre-labelling to make the sequencing and clustering faster than ever.

Also read: Top 5 Automation Tools to Streamline Workflows for Busy IT Teams

Trend 6: Autonomous Vehicles

Wait, aren’t autonomous vehicles already around? Yes, they are, but 2022 will see a massive rise in their global adoption, courtesy of AI-powered tech and the inclusion of improved self-driving capabilities. With Computer Vision is slowly moving up the ranks to improve the perceptive abilities of machines, experienced data annotation firms are progressively trying to make self-driven cars more intelligent. And moving into 2022, the primary focal points would include:

  • Improved on-road categorization
  • Better object detection and localization
  • Semantic segmentation for better object understanding, and more

And that’s not it. We are expecting the first-ever Autonomous Ship to surface in 2022. Now that’s as big as it can get.

Wrap-Up

But wait! Are these the only future AI trends that we need to watch out for going into 2022. Not exactly as you should even keep your eyes open for the likes of Creative AI, improved Conversational AI, and Explainable AI in the future. However, these tech trends might take some time to settle down, and if you are only interested in the immediate future, i.e., the next few months, these six trends might see increased global adoption, riding on the able shoulders of Artificial Intelligence and Machine Learning.

And if you are an organization looking to strengthen offerings with new AI-drive resources whilst making good use of any of the relevant trends, it is important to connect with credible and experienced data collection, data annotation, and data cleansing firms to get the data sets prepared, well in advance. As in the end, it all boils down to the quality of data fed into these intelligent AI and ML setups.

Vatsal Ghiya

Vatsal Ghiya is a serial entrepreneur with more than 20 years of experience in healthcare AI software and services. He is the CEO and co-founder of Shaip, which enables the on-demand scaling of our platform, processes, and people for companies with the most demanding machine learning and artificial intelligence initiatives.

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