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AI is bringing transformation potential to multiple industries and the number of businesses adopting artificial intelligence grew by 270% in four years and is expected to reach $267B by 2027 globally. Growing at this enormous rate, the implementation of artificial intelligence among different industries is set to accelerate dramatically.
As Mark Zuckerberg states,
“In a way, AI is both closer and farther off than we imagine. AI is closer to being able to do more powerful things than most people expect- driving cars, curing diseases, discovering planets, understanding media. Those will each have a great impact on the world, but we’re still figuring out what real intelligence is.”
We are not building artificial brains or artificial people any more than an aircraft manufacturer is trying to build an artificial bird. They just want to construct something that flies but we are building machines and software performing elementary cognitive tasks that require intelligence. Such mechanisms and applications have already become part of our everyday lives with devices controlling cars, understanding human language leveraging simultaneous transition.
This is just the beginning of what’s coming in our lives next. Let’s dive right into the biggest Artificial Intelligence trends and innovations for 2022.
Metaverse, a combination of prefix “meta” implying transcending with the word “universe”, describing a hypothetical synthetic environment linked to the physical world. The word was first coined in a piece of speculative fiction named snow crush, written by Neal Stephenson in 1992. In this novel, Stephenson defines the metaverse as a massive virtual environment parallel to the physical world, in which users interact through digital avatars.
The main characteristic of the emerging metaverse is the overlay of unfathomably vast amounts of sophisticated data that provides opportunities for the application of AI to release operators from boring and tough data analysis tasks such as monitoring, regulating, and planning.
AI plays a significant role in the creation and operation of the metaverse. Specifically, AI applications in the metaverse are divided into three categories as an automatic digital twin, computer agent and the autonomy of avatar. The metaverse supported by AI is expected to drive seven technology layers empowering spatial computing, decentralization, human interface, microelectromechanical systems (MEMS), scaffolding to creators, and sophisticated forms of machine storytelling.
What sounds like science fiction right now can be a part of our everyday lives in just a few years. Pioneering companies have already developed quantum AI models and are working feverishly to get them ready for the market. Quantum computers are scaling up both in size and reliability and are getting close to showing real-time advantage with the help of machine learning and artificial intelligence.
According to recent statistics, spending on quantum AI will surge from $260M in 2020 to $9.1B by 2030. It stands to be one of the most disruptive technologies and competitive advantage will be based on which companies can leverage the potential of quantum AI to solve key business problems and generate important insights about customers, strategies, and operations to transform their business.
The superpower of AI is not in modeling what we already know but in creating solutions that are new. Such solutions exist in high dimensional, extremely large, and complex search spaces. Variants of evolutionary computation and population-based search techniques are well suited in finding them, making it possible to find creative solutions to real-world problems.
Evolutionary computation is an AI technology on the verge of a breakthrough as a way to take machine creativity to the real world. In the near future, we will see applications of creative AI where human creativity is augmented by evolutionary search in discovering complex solutions in various industries and creative fields such as art, music, games, journalism and many more.
Low code and no code are shifting the balance between business and technology professionals. It is dramatically different than a decade ago and is trending at a feverish pitch. This trend represents a step towards the decade-long goal in computer science to automate coding.
The value proposition of disruptive low code AI technology gives companies the agility and flexibility to adapt to the fast-changing industry reality while accelerating the time to market of new applications to keep up with the market.
Low code is a software development technique that promotes faster app delivery with little to no coding required, accelerating the process of getting apps to production. They are a collection of software tools that allow the visual development of apps using intuitive modeling with a Geographical User Interface (GUI).
Businesses using such low code platforms for AI development benefit from intuitive user experience, better product scalability, and massive cost cuts on development. Along with low code platforms, no-code development platforms are generally perceived as “extraordinarily disruptive”. It is predicted that by 2024, more than 65% of apps will be developed using the low code and no code AI approach.
In the last couple of years, we’ve seen a lot of ransomware attacks and what it has done to the tech industry. Cyberattacks have particularly impacted business resilience, it’s no longer the case of encrypted computers and is impacting massive amounts of business, costing hundreds of millions of dollars. The world economic forum identified cybercrime as potentially posing a more significant risk to society than terrorism so as machines take over more of our lives, it inevitably becomes more of a problem.
AI is very good at analyzing network traffic as it learns and recognizes patterns that might suggest nefarious intentions. Cybersecurity using artificial intelligence will facilitate the detection and response to threats and malware by using previous cyber-attack data to determine the best course of action. AI will automate identity and access management security measures by recognizing patterns of attacks, suspicious email activity, identifying vulnerable network endpoints and generating automated reviews for human analyst review.
With the Covid 19 outbreak, medical technology is on the verge of being revolutionized by artificial intelligence. In nearly all areas of patient care, from cancer, radiography, risk assessment to chronic diseases, AI is expected to unleash its potential to deliver more efficient and accurate treatments.
A common use of AI in healthcare involves NLP (Natural language processing) applications featuring deep learning models that can understand and classify clinical documentation. They can analyze unstructured clinical notes on patients, giving incredible insights into improving methods, understanding quality, and better cures for patients. In a few years, clinicians will migrate tasks that require human skills with AI-based systems and applications that provide the highest level of cognitive function.
Artificial is significantly helping eCommerce businesses get closer to their customers. With the power of AI, eCommerce platforms today are able to utilize large datasets regarding customer behavior and usage patterns. These AI-induced self-learning algorithms can create personalized shopping experiences for online buyers. The highlighting trends of AI-powered eCommerce are Real-time product targeting, visual search, voice recognition, chatbots, and assortment intelligence tools.
Ecommerce portals such as Flipkart, Amazon, eBay are already making use of artificial intelligence to grow their business effectively. Acknowledging the recent development and innovation that AI has brought in the field of eCommerce, it can be said that businesses will see a drastic positive change in the coming years.
eCommerce was amongst the early adopters of AI, and in the near future, there are two significant areas where AI will be a high influencing factor –
(i) How retailers communicate with their customers.
(ii) How retailers function backstage.
Let’s explore the top AI eCommerce trends that’ll impact online users and businesses.
AI will continue to contribute to the new norm of an eCommerce website, i.e., the Semantic search engines. Instead of displaying results merely based on keyword inputs, NLP (Natural Language Processing), and AI together will be able to help in understanding synonyms of the searched text. Furthermore, NLP & AI enabled semantic search engines can quickly identify typos, suggest auto-correction, provide a dynamic display of targeted merchandising; enabling the customers to choose from more relevant search results. Also, AI has extended the way through which consumers search for products by introducing options like Voice Search in a mobile phone or computer.
Chatbots with their human-like capabilities to interact with their online visitors 24/7, not only act as sales assistants in a physical store assisting users with their needs but they also suggest the users for the best products after taking inputs from them. Moreover, these bots can correspond with the users in their native language by tracking their location as they can be trained to communicate in multiple languages. AI allows these Chatbots to evolve as smarter assistants and can enable them to communicate with human-like responses through text, voice, images.
Rakuten’s Fit Me Chatbot is one of the best examples of an evolved chatbot that can suggest the best fit apparel to the users based on the input received on their body shape. Get ready for a future-ready online bot fashionista who’ll guide you with the best fashion advice and will take your online shopping experience to the next level.
As AI & Machine Learning team up, marketers can expect great assistance in content extraction and creation with aptness. AI assistance, along with machine learning, is enabling marketers to sell their products more efficiently by enhancing marketing material and content. Also, through analyzing years of user conversation, AI can assist marketers in identifying and creating standardized FAQs.
Further, while AI excels in exhilarating the online retail experience, warehouse management is also flourishing with AI-powered robots performing tasks like sorting of the parcel, packaging, and categorization. AI is also playing a role by delegating and assisting the delivery personnel, using real-time traffic information, AI helps the fulfillment staff to reach out to the user with faster delivery by suggesting the best route.
Speaking about the best route, our attention is drawn towards the logistics industry that is one step ahead in reaping the AI benefits due to the boom in eCommerce. Now, let take a peek at some of the major industries where the use of AI technology will impact a wider section of mankind upgrading them to a better quality of living.
The Logistics & Transport market is incredibly dynamic and competitive, and it is anticipated that we will soon be able to run a 20,000-square-foot distribution center with AI enabled robotic crew. Also, with the assistance of AI, Anticipatory logistics is soon going to be trending in the logistics industry. By using information extracted from the algorithms running on Big Data, predicting demand even before the consumer places an order is definitely going to help logistics professionals for improving the quality and efficiency of their services.
Also, with transparency becoming one of the most integral aspects of the consumer experience, companies are emphasizing on adding more visibility of their operations. Thanks to the modern AI-based solutions, real-time tracking of fleet and workforce from the first mile to last mile to the long haul is made possible. Using heat maps and trend lines, businesses can now analyze the entire supply chain operations and also compare the planned vs. actual SLA’s.
SAP Conversational AI is a collaborative end-to-end platform for creating chatbots. AI chatbot is a uniquely designed software that simulates user conversation with a natural language through messaging applications. They use machine learning and Natural language Processing (NLP) along with Enterprise resources (ERP) to deliver human alike conversational experiences. System applications and products (SAP) enable answering FAQs and provide personalized recommendations according to user behavior.
SAP Conversational AI makes it easy to connect your bots to almost all popular messaging channels along with dialog management features, conversational natural language processing, and detailed API documentation. Sales and marketing departments will be leveraging SAP conversational AI to measure marketing campaign results and different marketing processes such as email responses after cold calls to generate leads. Furthermore, stats suggest that by 2022, 75-90% of queries are projected to be handled by AI chatbots.
Artificial intelligence in the automobile industry is expected to cause a profound disruption by augmenting business growth and streamlining production capabilities.
The trends most likely expected are voice engine optimization, payment-by-vehicle, brand-specific AI systems, and advancements in privacy and security.
It is believed that autonomous vehicles could generate $800 billion per year in revenue in 2030 and $7 trillion per year by 2050. With Tesla already rolling down the streets, driverless cars are fast becoming a reality. Automotive AI leveraging the development of smarter cars faster than ever before by analyzing patterns imitating human behavior and mining data. Cognitive capabilities are expected to utilize dynamic operating conditions that are designed to mirror the way humans would think and communicate with each other using artificial intelligence.
Renewable energy seems to be our only hope for the future. However, amongst the leading sources of renewable, solar, and wind are dependent on the weather – which is unpredictable. Furthermore, the advancement in storage technology might seem promising, but it’s still not up to the mark. There are chances of renewable energy falling short of demand that might eventually lead to the consumption of energy through fossil fuels, which actually defeats our purpose to shift to renewable in the first place.
Cutting demand for renewable energy when the supply is low and pumping it up when there is plenty available could be a solution. The use of demand-side flexibility can be made possible by advanced load control through equipment and appliances. For example, large air conditioners or industrial furnaces can be switched off at the time of low power generation and can consume more energy during excess supply.
While this could possibly be a breakthrough idea, there could be few glitches while implementing the same. Before deciding whom to tie up with, the grid has to know how many devices are available and how much can they contribute to the storage of energy. Also, safeguarding the energy consumption data collected from these devices can’t be ruled out, in order to avoid misuse or misinterpretation.
Thanks to machine learning and AI technologies most of these issues have been taken care of, and by applying it to the data generated by advanced sensors and smart devices beyond the meters, the grid operators can predict the behavior of individual appliance and the storage life too. As per the recent research by Infosys, it is said that 48% of the renewable energy and utility industries consider AI to be the ultimate source for their success, whereas 46% are in the process of integrating AI.
Thus, with the intervention of AI’s assistance for restoring Renewable Energy, in-depth research and development is being conducted over the exploitation of sources of renewable energy through:
Further, AI can assist the industry to enhance safety, efficiency, and reliability. The visibility of energy leakage, equipment health, and consumption patterns has improved with the help of predictive analytics through sensor data, again – all this is possible due to AI. The near future may envision the launch of new service models by renewable energy suppliers with the help of AI, which would eventually expand the renewable marketplace with increased participation.
Artificial intelligence is now table stakes for modern business, IT companies must harness artificial intelligence trends and technology to outmaneuver uncertainty and meet new surreal ecosystem expectations. As AI approaches rise, developers brace for new challenges. People rapidly create things, rapidly deploy things and rapidly regret things. Each subsequent generation of technology makes it easier to build bad solutions fast.
According to Sundar Pichai,
AI will affect humanity more than fire, electricity, and the internet.
This may sound like a zealous claim but within the realm of possibility, the potential is clear.
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