Top 10 Artificial Intelligence (AI) Software Solutions of 2022

Among the many drivers of rapid growth in the technology ecosystem, artificial intelligence (AI) and its subfields are at the forefront. Gartner describes AI as the application of "advanced analytics and logic-based technologies" to simulate human intelligence. It is an all-encompassing system that provides numerous use cases for individuals and businesses across a wide range of industries.

There are many ways to leverage AI to support, automate and augment human tasks, as seen with the variety of solutions available today. These products promise to simplify complex tasks with speed and accuracy and inspire new applications that were previously impractical or possible. Some have questioned whether the technology will be put to good use, or whether it will become more effective than humans in certain business use cases, but its popularity and pervasiveness are unquestionable.

What is artificial intelligence (AI) software?

Artificial intelligence software can be defined in many ways. First, a Lean description would consider it to be software capable of simulating intelligent human behavior. However, from a broader perspective, it is a computer application that can learn data patterns and insights to intelligently address specific customer pain points.

The AI ​​software market includes not only technologies with built-in AI processes, but also platforms that allow developers to build AI systems from the ground up. This can range from chatbots to deep and machine learning software and other platforms with cognitive computing capabilities.

To get an idea of ​​the scope, artificial intelligence includes the following:

• Machine Learning (ML): Allows computers to collect data and learn from it to generate insights.
• Deep Learning (DL): A further development of ML for detecting and learning from patterns and trends in large amounts of data.
• Neural Networks: Interconnected units designed to learn and recognize patterns, much like the human brain.
• Natural Language Processing (NLP): NLP supports AI’s ability to read, understand and process human language.
• Computer Vision: Teach computers to collect and interpret meaningful data from images and videos.

These capabilities are used to build artificial intelligence software for different use cases, the most important of which are knowledge management, virtual assistance and self-driving cars. As businesses must comb through vast amounts of data to meet customer demands, the need for faster, more accurate software solutions is increasing.

As expected, rising adoption of artificial intelligence at the enterprise level has led to accelerated market growth in the global artificial intelligence software market. Gartner expects growth to reach $62.5 billion in 2022, a 21.3% increase from 2021 value. By 2025, IDC expects the market to reach $549.9 billion.

Four Key Capabilities of Artificial Intelligence Solutions

Whether it’s powering surgical robots in healthcare, detecting fraud in financial transactions, enhancing driver assistance technology in the automotive industry or providing To provide students with personalized learning content, the primary purpose of artificial intelligence solutions can be divided into four major functional categories, including:

1. Automated processes

The automation functions of AI applications are consistent with AI The main goal is to minimize human intervention in performing tasks, whether mundane and repetitive, or complex and challenging. By collecting and interpreting the vast amounts of data fed into them, AI solutions can be leveraged to determine the next step in the process and execute it seamlessly. It leverages the power of ML algorithms to create a survey showing that 80% of companies expect to adopt intelligent automation by 2027.

2. Data Analysis and Interpretation

The core function of artificial intelligence solutions, especially for enterprises, is to create structured and A knowledge base of unstructured data that is then analyzed and interpreted to make predictions and recommendations based on its findings. This is called AI analytics, and it uses machine learning to study data and draw patterns.

Whether the analytics tool is predictive, prescriptive, augmented, or descriptive, artificial intelligence is at the core of determining how to prepare data, discover new insights and patterns, and predict business outcomes. Enterprises are also turning to artificial intelligence to improve data quality.

#3. User Personalization and Engagement

Building relationships has become the holy grail of customer acquisition and retention. A McKinsey study shows that one sure way to achieve this is through personalization and engagement. Artificial intelligence technology enables businesses to provide personalized services to customers and predict and address their concerns in real time. This capability is present in programs such as conversational chatbots and product recommendations generated from learned customer behavior.

Many organizations are still keeping up with the technology. Gartner reports that 63% of digital marketers struggle to maximize their use of personalization technology. Their survey of 350 marketing executives revealed that only 17% are actively using AI and ML solutions, although 83% believe in their effectiveness.

4. Business Effectiveness

In addition to increasing the automation of traditional processes, artificial intelligence also enables new services and functions that were previously unfeasible. From self-driving cars and natural language services for consumers to medical breakthroughs that were previously only imaginable, artificial intelligence is becoming the foundation for new products and markets and will continue to unfold.

Top 10 Artificial Intelligence (AI) Software Solutions of 2022

Google Cloud AI

Google’s dominant cloud offering includes support for development Various tools for people, data science, and infrastructure use cases. A variety of speech and language translation tools, visual, audio and video tools, and deep and machine monetization capabilities bring AI capabilities to both skilled technology practitioners and the mass consumer market. Google is named a leader in the 2022 Gartner Magic Quadrant for Cloud AI Developer Services.

IBM Watson Studio

Like Google, IBM provides a platform for building and training artificial intelligence software. IBM Watson Studio provides a multi-cloud architecture for developers, data scientists and analysts to collaboratively "build, run and manage" artificial intelligence models. With capabilities ranging from AutoAI to explainable AI, DL, model drift, model manipulation, and model risk management, the studio provides subject matter experts with the tools they need to collect and prepare data or create and train AI models.

It also gives these professionals the flexibility to deploy AI models in public or private clouds (IBM Cloud Pak, Microsoft Azure, Google Cloud, or Amazon Web Services) and on-premises. IT teams can open source these models as they are built using embedded Watson tools such as natural language classifiers. Its hybrid environment also provides developers with more data access and agility.

Salesforce Einstein

Salesforce has been named a leader in the Gartner Magic Quadrant for CRM Customer Engagement Centers for 13 consecutive years and ranked No. 1 by International Data Corporation (IDC) for eight consecutive years. CRM solution, Salesforce offers an advanced suite of sales, marketing and customer experience tools. Salesforce Einstein is an artificial intelligence product that helps companies identify patterns in customer data.

The platform has a built-in set of artificial intelligence technology that supports functions such as Einstein Robot, Prediction Generator, Forecast, Business Cloud Einstein, Service Cloud Einstein, and Marketing Cloud Einstein. Users and developers of new and existing cloud applications can also deploy the platform’s prediction and recommendation capabilities into their models. For example, at the launch of Salesforce Einstein in 2016, Einstein's general manager John Ball revealed that by creating Einstein, the company "converts leads into opportunities and opportunities into deals through predictive lead scoring and automated data capture."

Oculeus

Oculus provides industry-specific solutions. For service providers, network operators and enterprises in the telecommunications industry who need to protect and defend their communications infrastructure from cyber threats, Oculeus offers a range of software-based solutions that can help them better manage network operations. According to founder and CEO Arnd Baranowski, Oculeus uses artificial intelligence and automation "to understand an enterprise's regular communication traffic and continuously monitor it for anomalies from the baseline of expected communication activity. With its AI-driven technology, it can Identifies, investigates and blocks suspicious traffic within milliseconds. This is done before any significant financial loss is caused to the business and protects the telecommunications service provider's brand reputation."

Communications Fraud Control Association (CFCA) 2021 The 2018 International Telecommunications Fraud Losses Survey found total losses exceeded $39.89 billion, an increase of 28% from the previous year. Likewise, cybersecurity and operators are experiencing more fraud threats and attacks.

Among other things, these insights amplify the need for enterprises to turn to a proactive defense approach to outwit their adversaries, which is exactly what Oculeus claims to deliver with its AI-powered telecom fraud protection solution. In Baranowski's words, Oculeus' AI-driven approach to telecom fraud protection not only "...stops fraudulent telecom traffic before any significant financial damage is caused," but also includes extensive automation tools to eliminate threats completely.

Edsoma

Edsoma represents another narrow use case. Its AI-based reading app features real-time, exclusive speech recognition and recognition technology designed to reveal children's reading strengths and weaknesses. This follow-up technology recognizes the user's spoken language and speaking speed to determine whether they are speaking the words correctly. If they pronounce words incorrectly, a correction program can help them get back on track.

As Edsoma founder and CEO Kyle Wallgren explains, once “…the e-book is read, an automatic speech recognition (ASR) system transcribes the child’s voice in real time and provides instant results, including pronunciation assessment, Speech, timing and other aspects. These indicators are compiled to help teachers and parents make informed decisions."

This technology is designed to improve children's oral reading fluency and provide the necessary support to instill in them a healthy reading culture. Edsoma seeks a piece of the $127 billion global edtech market. By leveraging real-time data to provide real-time literacy, Edsoma hopes to deliver future-proof learning powered by AI.

Appen

Appen has been one of the early leaders as a source of data needed for the entire development lifecycle of artificial intelligence products. The platform provides and improves image and video data, language processing, text and even alphanumeric data.

It follows four steps to prepare data for AI processing:

• The first step is Data Sources, which provides automated access to more than 250 pre-labeled datasets.
• Then there is data preparation, which provides data annotation, data labeling, knowledge graph and ontology mapping.
• The third phase supports model building and development needs with the help of partners such as Amazon Web Services, Microsoft, NVIDIA and Google Cloud AI.
• The final step combines human evaluation and AI system benchmarking to allow developers to understand how their model works.

Appen has a language database in more than 180 languages ​​and a global skills force of more than 1 million talents. Among its many features, its AI-assisted data annotation platform is the most popular.

Cognigy

Cognigy​ is a low-code conversational AI and automation platform that was recently named a leader in Gartner’s 2022 Magic Quadrant for Enterprise Conversational AI Platforms. As the demand for a better customer experience (CX) increases, more and more businesses are relying on conversational analytics solutions to dig deeper into their customers’ text and voice data to uncover insights that power smarter decisions and processes. Automated provision of information.

That’s why Cognigy automates natural communication between employees and customers through multimodal channels and more than 100 languages. Additionally, its technology allows businesses to build AI-powered voice and chatbots that can address customer concerns as accurately as humans.

Cognigy also has an analytics feature – Cognigy Insights – that provides businesses with data-driven insights to best optimize their virtual agents and contact centers. Additionally, the platform allows users to deploy the technology in the cloud or on-premises. The platform, which was specifically praised by Gartner for its customer reference, flexibility and sustainability, helps enterprises create new service experiences for customers.

Synthesis

Synthesis AI’s solutions generate synthetic data, allowing developers to create more capable and ethical AI models. When deploying models on this platform, engineers can obtain multiple well-labeled, photorealistic images and videos. These images and videos are perfectly tagged with labels such as depth maps, surface normals, segmentation maps, and even 2D/3D landmarks.

Virtual product prototyping and the opportunity to build more ethical AI using expanded data sets that explain the same identity, appearance, and representation that are part of their products. Organizations can deploy this technology in API documentation, teleconferencing, digital humans, authentication and driver monitoring use cases.

Tealium

Tealium’s data orchestration platform is positioned as a universal data hub for businesses looking for a powerful customer data platform (CDP) for marketing engagement. The CDP provider offers a range of solutions within its customer data integration system that enable businesses to better connect with their customers. Tealium's products include a tag management system (Tealium iQ) to track and unify its digital marketing deployments, an API hub to facilitate enterprise interconnection, a machine learning-based data platform (Tealium AudienceStream) and data management solutions.

The company recently sponsored a comprehensive economic impact study by Forrester to calculate return on investment for reference customers.

Coro

Coro provides total cybersecurity solutions to mid-market and small to medium-sized enterprises. The platform leverages artificial intelligence to identify and remediate malware, ransomware, phishing and bot security threats across all endpoints while reducing the need for dedicated IT teams. Additionally, it is built on non-disruptive security principles, allowing it to provide security solutions for organizations with limited security budgets and expertise.

This cybersecurity-as-a-service (CaaS) provider demonstrates how AI can support higher-level services for lower-level business market tiers.

wave of artificial intelligence innovation

As artificial intelligence technologies continue to advance and more organizations adopt them, IT leaders must determine how the solutions they choose fit their business goals . With so many vendors riding the wave of AI innovation, buyers must choose their solutions carefully.

IDC predicts that artificial intelligence platform and artificial intelligence application development and deployment will continue to be the fastest growing areas of the artificial intelligence market. This list provides a starting point for organizations to evaluate the methods and solutions that best fit their needs.

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