Data Science



AI in 2022: What Should We Expect and Watch Out for?

Gartner predicts that the valuation of the global Artificial Intelligence (AI) market will reach $62 billion in 2022. This indicates that we will see further AI-driven innovations, research on AI, and better AI products and/or services. The recent AI industry trends promise us great progress in 2022.

Compared to the previous years, we have already come a long way having made much progress with the help of AI in fields such as medical science, aeronautics, space exploration, finance, and manufacturing. Companies are coming up with great technologies that incorporate AI to provide services as effectively as possible to their end users. New innovations are being introduced, and products are being made better and faster (to use) every year.

For example, media streaming platforms such as YouTube or Spotify recommend videos and music based on the music you like. This is done by an AI algorithm that identifies similar songs to the current song you are listening to and then understands the pattern of some of the same songs you already listen to. These, as well as services such as search engines, email platforms and office suites, are becoming more powerful by incorporating additional features and having the capacity to consider more dimensions of the user data before making recommendations. 

This was an example of AI being used to provide amazing services, but what about companies that do not deal with AI for their products? AI can help different types of businesses make solid data-driven decisions. This can help companies identify opportunities, avoid risks, and make a play for greater profit margins. 

Insights from data are crucial to gain an edge over the competition. AI allows companies to process, analyze, and visualize all this data extremely fast, especially when businesses need to make decisions in real-time, and one cannot conduct manual analysis of the data at hand.

2021 was a great year for AI, but 2022 is expected to be the best year so far. If we take a look at the global AI software market, the revenue of knowledge management systems has grown by 31.5% to $7189 million in 2022 compared to a 17.5% growth in 2021. Similarly, the global market revenue of virtual assistants has grown by 14.7% to $7123 million in 2022.

How AI will change in the next few years

Looking at recent trends in Artificial Intelligence, we can infer that we will use AI more in our daily lives and other business processes than its use in niche areas and specialized domains. 

For example, AI is being rapidly adopted by companies for RPA or Robotic Process Automation. Based on Gartner’s reports, it is expected that AI software spending will be the highest for autonomous vehicles, virtual and digital workplaces, knowledge management and using data from large populations.

Autonomous machines, robots and vehicles are also getting smarter and more efficient to the point where they are capable of replacing humans, well almost. Autonomous machines and robots in manufacturing barely make mistakes and are much faster than their human counterparts. Similarly, unmanned drones and autonomous vehicles can reduce accidents.

Tesla has recently stated that having the autopilot engaged reduces the chance of an accident by 10X. This is a huge statement in terms of trusting AI and a nod to the progress we’ve seen in the domains of computer vision and deep learning. 

We will also see AI being used a lot for smart homes and in general security or surveillance applications in our workplaces. The revenue of the global AI software market has been estimated to grow by 21.3% from 2021. In 2022, we will be seeing advanced AI incorporations evolve from experimental to essential.

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How AI will adapt

During the early incorporation phase of automation, many people were worried that AI would be replacing them in their jobs. While it might be true for repetitive jobs requiring manual labour, AI will also create many new jobs. Companies are planning to shift to augmented workforce and hybrid workforces that allow people to work alongside AI to carry out their tasks more effectively.

With hyper-automation, maintaining compliances is easy while increasing productivity and accuracy with the help of monitoring and automated evaluations. AI has also become crucial to preventing fraudulent activities and identifying suspicious behaviour. 

AI has been making a mark in the area of cybersecurity as well. Hackers have been getting access to data by unlawful means, and these hacking attacks are growing more rampant. Large corporations and MNCs are the favourite targets of hackers. This is why instead of manually evaluating their security systems and finding loopholes, these companies are incorporating AI into their data security systems. AI can find and flag the loopholes that compromise the security of data or networks extremely fast

Similarly, it is easy for AI to tend to compromised areas in real-time. For example, if a network is being attacked in real-time, AI can follow specified protocols that either allow it to shut down the network or change credentials. 

AI solutions and integrations need to also rapidly adapt to ‘as a service’ model, as many smaller businesses are willing to invest in AI-driven products. Smaller companies or medium-level corporations do not wish to get dedicated AI solutions and instead opt for subscription-based services. 

AI will also be extensively adopted into the telecommunication industry from 2022 onwards. AI’s market in telecommunications is estimated to grow at a CAGR of 47.33% from now till 2026.

What are the barriers that will AI face?

Along with its growth AI adoption will also face some roadblocks. Some of which include: 

    • Talent shortages in IT: There is a massive shortage of talented AI and Machine Learning (ML) developers and engineers. It is a very competitive market when it comes to grabbing talent with AI and ML skills. Now is the best time to pick up an Artificial Intelligence course and upskill to more rewarding and cutting-edge roles. 
    • A shortage of high-quality data: AI-driven systems and models require massive amounts of reliable data  to function properly. Strong data pipelines need to be built that can use both structured and unstructured data from hundreds of sources. There is a shortage of both flexible data pipelines as well as high-quality data that can be used to train AI models. We need more scalable data lakes as well as data storage and access methods.
  • Regulatory and ethics barriers: When it comes to depending on AI or using AI, there will always be regulatory and ethical concerns. There will always be AI prohibited in certain countries or sectors. AI models must also adhere to various regulatory frameworks of other platforms and be compliant when using user data.
  • Lack of exposure to automation: All kinds of processes can be automated and mostly everywhere. Business leaders do not yet know how to use AI and automation for their individual processes.

What are the solutions to these barriers?

The solution to the talent shortage is the promotion of AI-focused education (like AI courses online) by large corporations as well as reputed institutes. With enough talent, companies will not have a hard time scoping for it and strong talent pools will  result in more advanced innovations.

Data shortages can be handled with the help of adopting flexible data pipelines that can connect to thousands of sources. It is a great idea to manually generate high-quality data or dedicate a period of time just to scrape high-quality data from existing sources.

The issues with regulatory frameworks and ethics can be easily managed by incorporating automated frameworks that keep both developers and the AI model in check. Companies can also choose to hire regulatory consultants and analysts to check their models before deployment.

For the last shortage that we mentioned, this can only be solved with marketing campaigns by MNCs and IT giants. Campaigns that promote the benefits of incorporating AI need to reach business heads, manufacturing unit owners and other industrialists. With proper exposure, business leaders will move towards adopting AI into their processes.

What are the limitations of AI?

In terms of financing and investments, many are betting on AI and AI-driven solutions. However, AI has 3 fundamental limitations:

  • A lot of AI solutions are still a luxury and not a necessity. Rather than spending money on shifting to AI solutions, many factory owners and business heads wish to stick to manual processes. Until AI solutions become extremely affordable and require minimal investment to install, they cannot be adopted everywhere, especially in countries where labour is cheap. 
  • One of the main limitations of AI will always be high quality and relevant data. At this point, generating or sourcing usable data has also become expensive. 
  • Many people still do not trust AI and fear that AI will take over. Their fear ranges from AI going berserk to AI stealing their jobs. Many people are still scared to let AI handle driving or other mechanical tasks.


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What is the potential of AI?

AI has the potential to be incorporated into every sector, every process and almost any task. AI can be used for analytics, robotics, manufacturing, agriculture, finance, marketing, IT development, education and customer service.

Here are some examples of AI being used in various industries:

  • To monitor crops and apply insecticides in an automated fashion in agriculture
  • To assist production with autonomous robotic arms that detect parts that need to be put together
  • Automated analytics and daily business reports
  • Advanced chatbots for technical assistance.

Top 5 AI trends for 2022

Here are the top 5 trends for AI in 2022:

  • In healthcare and medical science: AI has helped  make tremendous headway in medical science with faster drug development and genome research. By adopting AI, hospitals can utilise their resources and medical professionals more effectively as well. AI has already helped in learning about diseases and viruses, but now we are able to test them in virtual environments. 
  • Customer service, NLP and NLG: AI has been used for providing automated customer service for quite some time now. But with advanced NLP (Natural Language Processing) and NLG (Natural Language Generation), companies might shift to fully AI-powered customer service. We can also expect better services from our voice assistants such as Siri and Google Assistant. 
  • Creative AI: AI has generally been used for exploratory and repetitive tasks; however, companies have now started finding success in developing AI that is creative. We will soon see more AI-created artwork, music and content. 
  • Fully-autonomous machines: Tesla has already announced that they will be making their auto-pilot fully autonomous. Similarly, engineering companies have started developing autonomous machines that do not require any human supervision. Machines in factories still need to be controlled and managed by humans; however, this will soon change with fully-autonomous machines. 
  • Security and surveillance: Many companies have started investing in AI-based security or surveillance systems. Video analytics and face detection are also popular AI-driven services that are being extensively adopted recently. In 2022, we will see more innovations in this domain as well as see more companies adopt these services. 

Due to the incorporation of AI in all kinds of business processes, it is estimated that there will be much more collaborations between the operations, business and IT teams. AI will make jobs much easier to do and ensure the automated maintenance of industrial machines in factories. Hyper Automation is the driving force behind the new holistic approach towards business and production processes.

The current trends in Artificial Intelligence imply that we will see AI being adopted in healthcare, art and our daily lives even more. Advanced AI solutions replacing older chatbots and manually controlled machines are two other dominant Artificial Intelligence trends we will experience.

It is crucial to upskill on AI, especially due to the fantastic opportunities and prospects this domain offers. There are many solid AI courses in India that you can use.

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