, pub-7580744294872774, DIRECT, f08c47fec0942fa0 Top 10 (AI) artificial intelligence solutions in 2022

Top 10 (AI) artificial intelligence solutions in 2022

Top ten (AI) artificial intelligence  solutions in 2022

Artificial intelligence (AI) and its subdomains are among the numerous drivers of the IT ecosystem's fast development. Gartner defines AI as the use of "advanced analytical and logic-based approaches" to replicate human intelligence. 

AI is a comprehensive system with multiple applications for people and businesses across sectors.

Top 10 (AI) artificial intelligence  solutions in 2022

As seen by the variety of solutions available today, there are several ways to use AI to assist, automate, and enhance human work. 

These services claim to simplify complicated operations with speed and precision, as well as to drive new applications that were previously impractical or impossible. 

Some people aren't sure if the technology will be used for good or if it will be better than humans in some business situations, but its widespread use and appeal can't be denied.

What exactly is artificial intelligence software (AI)?

AI software may be characterized in a variety of ways. First, a simple definition would be software capable of replicating intelligent human behavior

But from a broader perspective, it's seen as a computer program that smartly learns data patterns and insights to solve specific client pain points.

The AI software industry encompasses not just technologies with built-in AI processes but also platforms that enable developers to create AI systems from the ground up. 

Chatbots, deep and machine learning software and other platforms with cognitive computing characteristics might all fall under this category.

To give you an idea of the scope, AI includes the following:

  • Machine learning (ML): A computer's ability to take data and learn from it in order to develop insights.
  • Deep learning (DL): a step beyond ML that is used to recognize and learn from patterns and trends in massive amounts of data.
  • Neural networks: interconnected units that, like the human brain, are intended to learn and detect patterns.
  • Natural language processing (NLP): NLP enables AI to read, comprehend, and process human language.
  • Computer vision is the process of teaching computers to gather and analyze relevant data from photos and videos.

These characteristics are used to create AI software for a variety of applications, the most prominent of which include knowledge management, virtual help, and autonomous cars. 

With the massive amounts of data that businesses must go through in order to satisfy client needs, there is a greater need for quicker and more accurate software solutions.

As predicted, the surge in enterprise-level AI usage has boosted the worldwide AI software market's development. 

According to Gartner, the growth will be $62.5 billion in 2022, a 21.3% rise over the value in 2021. According to IDC, this industry will be worth $549.9 billion by 2025.

An AI solution must perform four important functions

Whether it powers surgical bots in healthcare, detects fraud in financial transactions, improves driver assistance technology in the automotive industry, or personalizes learning content for students, the overarching goal of AI solutions can be divided into four broad functional categories that include:

1. Increase the automation of procedures:

The automation function of AI applications achieves AI's fundamental goal of reducing human interference in job execution, whether dull and repetitive or complicated and demanding. 

An AI solution may be used to identify the next stages in a process and execute it flawlessly by gathering and understanding large amounts of data given to it. 

This is done by building a knowledge base out of both structured and unstructured data with the help of ML algorithms.

One poll showed that 80% of businesses want to use intelligent automation by 2027. This shows that process automation is still a big deal for businesses.

2. Data interpretation and analysis

The creation of knowledge bases of structured and unstructured data, followed by analysis and interpretation of such data before providing predictions and recommendations based on its results, is a basic role of AI systems, particularly for organizations. 

This is known as AI analytics, and it uses machine learning to analyze data and identify patterns.

AI is at the heart of defining how data is produced, identifying new insights and patterns, and anticipating business results, whether the analytic tools are predictive, prescriptive, enhanced, or simply descriptive. 

AI is also being used by businesses to enhance data quality.

3. User participation and personalization:

Relationship building has become the holy grail of consumer acquisition and retention. 

According to McKinsey's research, one definite method to achieve this is via personalization and interaction. 

AI technology enables businesses to deliver customized offerings to clients while also anticipating and resolving their issues in real-time. 

This role is manifested in programs such as conversational chatbots and product suggestions based on learned consumer behavior.

Many firms are still catching up with technology. According to Gartner, 63% of digital marketers fail to make the most of personalization technologies. 

From their survey of 350 marketing professionals, they found that only 17% are actively using AI and ML solutions across the board, even though 83% think they work.

4. Business efficiency

Along with the growing automation of conventional operations, AI enables previously unimaginable services and capabilities. 

AI is laying the groundwork for new products and businesses that will continue to pop up. This includes things like cars that don't need drivers and customer services that use natural language.

In 2022, the following are the top ten artificial intelligence (AI) software solutions

AI software solutions include generic platforms for a variety of applications as well as products for more specific, industry-specific use cases. 

The following sample list includes a cross-section of both. 

There are several solutions on the market today, with 56% of firms using AI for at least one business function.

The following are 10 examples of AI software solutions that will be available in 2022.

Google Cloud AI

Google's dominating cloud service offers a slew of tools to help developers, data scientists, and infrastructure professionals. 

A variety of voice and language translation tools, vision, audio, and video tools, and deep and machine learning capabilities deliver AI capability to experienced technology practitioners as well as mass consumer markets. 

In Gartner's Magic Quadrant for Cloud AI Developer Services in 2022, Google was ranked as a leader.

IBM Watson data science

IBM, like Google, provides a platform for developing and training AI algorithms. 

The IBM Watson Studio offers a multicloud architecture, enabling developers, data scientists, and analysts to collaborate "create, operate, and maintain" AI models. 

The studio gives subject-matter experts the tools they need to collect and prepare data or build and train AI models. Auto AI, AI that can be explained, deep learning, model drift, models, and model risk management are all examples of these tools.

It also gives these experts the option of deploying AI models on-premises or on the public or private cloud (IBM Cloud Pak, Microsoft Azure, Google Cloud, or Amazon Web Services). 

IT departments may open source these models as they develop them using integrated Waston technologies such as the Natural Language Classifier. Its hybrid environment may potentially give additional data availability and agility to developers.

Salesforce Einstein

Salesforce has been named a leader in Gartner's Magic Quadrant for CRM Customer Engagement Center thirteen times in a row, and the International Data Corporation (IDC) has named it the #1 CRM system for eight straight years.

 Salesforce Einstein is a program that uses artificial intelligence (AI) to help businesses find patterns in customer data.

This platform includes AI technologies that enable Einstein bots, prediction builder, forecasting, commerce cloud Einstein, service cloud Einstein, marketing cloud Einstein, and other tasks. Users and developers of new and current cloud apps may include the predictive and suggestive features of the platform in their models. 

For example, at the launch of Salesforce Einstein in 2016, Einstein's general manager, John Ball, said that the company made Einstein to "enable sales professionals to find better prospects and close more deals through predictive lead scoring and automatic data capture to turn leads into opportunities and opportunities into deals."


Oculeus offers a solution tailored to the industry. Oculeus provides a range of software-based solutions that may assist service providers, network operators, and companies in the telecom sector to safeguard and defend their communication infrastructure against cyber attacks. 

According to Arnd Baranowski, founder, and CEO of Oculeus, AI and automation are used "to learn about an enterprise's routine communications traffic and continuously monitor it for deviations to a baseline of anticipated communications activity." Suspicious traffic may be recognized, examined, and banned in milliseconds using its AI-driven technology. 

This is done before any serious financial harm is done to the firm, and it safeguards the telecommunications service provider's brand name."

The 2021 assessment of worldwide telecommunication fraud losses conducted by the Communications Fraud Control Association (CFCA) showed losses of more than $39.89 billion, a 28% increase over the previous year. 

Likewise, network security and operators are seeing an increase in fraud threats and assaults.

These findings, among other things, highlight the necessity for organizations to adopt a proactive defensive strategy that outwits attackers, which Oculeus promises to deliver with its AI-powered telecommunications fraud prevention products. 

According to Baranowski, Oculeus' AI-driven approach to telecom fraud prevention comprises not just "...stopping fraudulent telecommunications traffic before any serious financial harm is inflicted," but also comprehensive automated technologies that fully sort out risks.


Edsoma is yet another specialized application. Its AI-based reading application software includes real-time, proprietary voice detection and recognition technologies developed to identify children's reading strengths and limitations. 

This follow-along technology recognizes users' spoken words and speaking pace to assess whether they are accurately uttering the words.

 If they mispronounce anything, a corrective program might help them get back on track.

According to Edsoma creator and CEO Kyle Wallgren, "After the electronic book is read, the child's voice is transcribed in real-time by the automatic speech recognition (ASR) system, and instantaneous findings, including pronunciation evaluation, phonetics, timing, and other features, are delivered." 

These indicators have been produced to assist instructors and parents in making informed decisions.

This technology aims to increase children's oral reading fluency abilities and offer them the resources they need to develop a healthy reading culture. 

Edsoma aspires to capture a piece of the $127 billion worldwide edtech industry. Edsoma aims to provide future-focused learning driven by AI by exploiting real-time data to enable real-time literacy.


Appen was an early pioneer in providing data needed throughout the development lifecycle of AI technologies. This platform offers and improves language processing, text, and alphanumeric data, as well as picture and video data.

The first step in getting data ready for AI processing is data sourcing, which gives automated access to more than 250 pre-labeled datasets. The second step is data preparation, which includes data annotation, data labeling, knowledge graphs, and ontology mapping.

The third stage addresses model creation and development requirements with the assistance of partners such as Amazon Web Services, Microsoft, Nvidia, and Google Cloud AI.

 The last phase combines human assessment with AI system benchmarking to provide developers with a better understanding of how their modes perform.

Appen has a linguistic database of over 180 languages and a worldwide talent force of over 1 million people. The most popular of its numerous features are its AI-assisted data annotation platform.


Cognigy is a low-code conversational AI and automation platform that was just named a leader in Gartner's Magic Quadrant for Enterprise Conversational AI Platforms for 2022. 

As the need for a better customer experience (CX) grows, more businesses are turning to conversational analytics solutions to delve deep into their customers' text and speech data and unearth insights that guide smarter choices and automate processes.

As a result, Cognigy automates natural communication between staff and consumers across multimodal channels and in over 100 languages. 

Also, its technology lets businesses build AI-powered speech and chatbots that can answer customer problems with the same accuracy as a real person.

Cognigy Insights is an analytics component that gives organizations data-driven insights on how to enhance their virtual agents and contact centers. 

Furthermore, the platform enables customers to implement the technology either in the cloud or on-premises. 

Gartner likes this platform because it has customer references, is flexible, and will last for a long time. It also helps organizations create new service experiences for customers.


The Synthesis AI solution provides synthetic data, allowing developers to build more competent and ethical AI models. 

Engineers may use this platform to deploy their models by sourcing a variety of well-labeled, photorealistic photos and videos.

These photos and movies have been meticulously annotated with labels ranging from depth maps to surface normals, and segmentation maps to 2D/3D landmarks.

Some of its product solutions include virtual product development and the ability to construct more ethical AI with extended datasets that care for equal identity, appearance, and representations. 

This technology may be used in API documentation, teleconferencing, digital people, identity verification, and driver monitoring use cases.'s technology may be a good match, with 89% of tech leaders thinking that synthetic data would alter their sector.


Tealium data orchestration platform is marketed as a universal data hub for companies looking for a powerful customer data platform (CDP) for marketing interaction.

Through its customer data integration system, this CDP supplier provides a slew of solutions that help organizations engage with their consumers more effectively. 

Tealium's products include a tag management system (Tealium iQ) for organizations to monitor and unify their digital marketing deployments, an API gateway to allow corporate interconnectivity; an ML-powered data platform (Tealium AudienceStream), and data management solutions.

Forrester recently funded a full economic impact study, estimating ROI on reference customers.


Coro offers comprehensive cybersecurity solutions for mid-market and small-to-medium-sized businesses.

The platform employs artificial intelligence to detect and remediate malware, ransomware, phishing, and bot security threats across all endpoints, minimizing the requirement for a specialized IT workforce. 

Furthermore, it is based on a non-disruptive security approach, enabling it to provide security solutions to enterprises with limited security budgets and experience.

This cybersecurity-as-a-service (CaaS) provider shows how artificial intelligence (AI) can help higher-level services be delivered to lower-level corporate market segments.

The wave of AI innovation

As AI-powered technologies evolve and more businesses use them, IT directors must consider how the solutions they choose fit into their overall business objectives. 

With so many companies trying to make money off of AI, customers need to be careful when choosing their solutions.

According to IDC, the fastest-growing categories in the AI industry will continue to be AI platforms and AI application development and deployment. 

This list gives businesses a place to start when figuring out which techniques and solutions will work best for them.

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