Clearly, today’s best artificial intelligence software is driving change: hardly a day goes by without artificial intelligence (AI) software introducing new and improved capabilities. As features appear and use cases expand, organizations turn to AI applications to gain competitive advantage.
AI software capabilities typically fall into several core areas: machine learning (ML), deep learning, predictive analytics, machine vision, robotic process automation (RPA), smart assistants and chatbots.
With the current focus on digital transformation, systems are changing everything from business forecasting and supply chain automation to marketing/sales and customer support. They’re ushering in smarter business and IT frameworks that can act and react to events in more agile and flexible ways. They can also make work safer for employees during the current pandemic.
It’s a field worth focusing on. According to an August 2020 report from online research site Statistica, the global artificial intelligence (AI) software market is projected to grow 54% year-to-year from 2019 to 2025, reaching a forecast size of $22.6 billion.
The same report notes that while many are concerned about the possible negative impact of AI—including potential layoffs and disruption in the workplace—the net effect of the technology will likely be positive for economic growth. Statistica estimates that AI software will contribute to a 14.5% boost in GDP in North America and 26.1% in China by 2025.
Of course, sorting through options and vendors can be daunting. What’s more, software offerings are advancing and changing rapidly. As a result, business and IT leaders should focus on solutions that not only unlock process improvements and cost savings, but also fuel innovation and disruption.
Here are 20 leading software providers in the AI software space, including major cloud providers that support a variety of AI functions and features, along with more specialized providers that address AI in different ways.
Best Artificial Intelligence Software
Clearly, AI software is a mixed bunch; given the various focus, we’ve divided the list into three core areas:
These cloud vendors offer products and solutions that span multiple AI categories. In some cases, they provide a one-stop shop for AI software.
The vendor’s cloud-based AI offerings span a number of areas, including machine learning, machine translation, image search, predictive analytics and a recently added intelligent speech interaction engine. The latter combines multiple AI technologies to deliver a more natural human-computer interaction experience in seven languages, including English, Japanese, Cantonese, Mandarin and French. The platform includes a robust SDK and API framework.
Amazon Web Services
AWS, the undisputed leader in cloud computing, offers an array of ML, DL and analytics solutions for organizations across various industries. The list includes AWS Deep Learning AMIs, Amazon QuickSight and Amazon SageMaker, which builds, trains and deploys machine learning models at scale. AWS also offers tools for speech and text, such as Lex (for Alexa); Polly, a text to speech tool; and Rekognition, which handles image/video recognition and classification.
The cloud provider places a heavy focus on AI through a variety of products and tools. It provides an AI development platform, facial recognition and other types of machine vision and image review, speech technologies, optical character recognition (OCR) and text capabilities, language processing. The vendor also delivers a variety of other AI capabilities for auto-scaling, object storage, intelligent edge management and handling cloud container engines throughout their lifecycle.
Not surprisingly, AI is at a primary focus for Google. The company offers numerous AI and machine learning products, including Vertex AI, a unified machine learning platform for building, deploying and scaling AI models. In addition, there are conversational AI tools that handle speech-to-text (and vice versa), virtual agents, natural language processing, document automation and machine vision tools. Google supports TensorFlow, a sophisticated end-to-end machine learning software platform.
Big Blue is among the leaders in AI with its portfolio of highly scalable Watson AI solutions. This includes products specifically designed for building AI models and machine learning, customer service/chatbots, business automation, natural language processing and other areas. The vendor has solutions that are designed to meet the needs of specific industries and groups, including healthcare, financial operations, risk and compliance, advertising, supply chain, security and IT operations.
Through its Azure cloud platform, Microsoft delivers a variety of AI tools and solutions that cover ML, DL and analytics. Among its offerings: Azure Machine Learning, which helps data scientists and developers build, train and deploy ML at scale; and Azure Databricks, which uses Apache Spark to support big data analytics and AI. There’s also speech assistant Cortana and chatbot tools.
These AI software companies offer solutions that transform data into intelligence and insights.
The company’s Experience Cloud has emerged as a leading platform for advanced analytics and AI. It is designed to deliver real-time personalization through various tools, including machine learning and AI-driven chat functionality. In addition, Adobe’s Sensei helps organizations build, manage and operationalize AI across the customer journey. The product is designed primarily for marketers and data science teams.
The analytics vendor offers a robust machine learning platform that allows domain experts and data scientists to put data to work in new and innovative ways. Automated Insight Generation finds hidden signals and key relationships in data. The firm’s Deep Feature Synthesis uses popular algorithms like xgBoost, LightGBM, and ElasticNet to detect patterns and insights through explainable machine learning models.
The vendor taps AI and ML to automate business analysis functions. It focuses on putting data to work across teams. The platform supports conversational search, natural language insights, presentation-ready decks with advanced visualizations, and sophisticated ad-hoc querying from any device. The vendor also offers solutions specifically designed for functions such as marketing, sales, finance, data science, supply chain and general analytics.
With an open-source end-to-end platform that supports AI across an enterprise, the vendor focuses on predictive analytics use cases in financial services, healthcare, manufacturing, marketing, telecom and more. This includes fraud detection, customer-churn prediction, credit risk scoring, improving clinical workflows and medical testing, predictive fleet maintenance and supply chain optimization.
With a long history in databases and data management, Oracle is among the leaders in AI driven data insights. Among its cloud-based data science, ML and AI services: advanced anomaly detection that’s designed to identify critical criteria and advanced text analysis capabilities that that can detect sentiment, key phrases and other highly specific criteria. In-database ML allows users to run SQL, R and Python learning models.
The CRM provider offers cloud-based AI capabilities within its Einstein AI solution. It delivers smart assistant tools that classify tasks and deliver next best actions, automate processes and puts smart bots to work. These agents can generate recommendations, replies and deliver relevant chat systems. They also can personalize content and information to match the specific needs of customers and others. In addition, the platform supports IoT and other edge functionality.
The long-time leader in data mining and analytics offers SAS Visual Data Mining and Machine Learning, which uses a unique automated modeling API to solve complex problems. The product can spot patterns, trends and other insights across various ML models. It includes natural language generation to product summaries and reports. The platform supports open-source algorithms and source code. It’s designed for both business analysts and data scientists.
These vendors specialize in solutions and software that help organizations unlock greater efficiencies through improved business operations, robotic process automation, supply chain automation and more.
The robotic process automation vendor is a Gartner “Leader” in the intelligent automaton ecosystem space. Through a cloud-native web-based framework, it delivers an array of sophisticated tools and capabilities, including discovery bots that fast-track automation, IQ bots that find and transform unstructured data into intelligence, and bot insight functionality that delivers real-time robotic process automation and analytics.
While the semiconductor giant is known for processors that run computers, Intel is also among the leaders in advanced AI software functionality. The firm offers AI developer tools and resources, including Intel AI Software Suite, which supports a wide array of popular frameworks and libraries in deep learning, machine learning, and TensorFlow, PyTorch, scikit-learn and other big data analytics platforms. It includes the Intel oneAPI AI Analytics Toolkit, Intel distribution of the open-source deep learning inference OpenVINO toolkit and Analytics Zoo, which scales AI models.
The vendor delivers an AI-based communications platform that taps custom bots, apps and other automation to deliver sophisticated conversational chatbots for sales and customer support functions. The platform integrates with more than 300 other applications, including Salesforce, Slack, Stripe, Google Analytics, HubSpot, Twitter and Zendesk. Intercom also has solutions available for organizations in the finance, healthcare, education and e-commerce spaces.
As a leader in advanced AI solutions, NVIDIA offers AI Enterprise, an end-to-end cloud-native platform for running and scaling AI workloads in hybrid clouds. It includes support for distributed deep learning training and various other machine learning models, edge AI inference, data analytics and other AI models. The platform accommodates a wide array of functions and capabilities with near bare-metal performance.
The enterprise applications giant supports an intelligent enterprise through prebuilt AI cloud applications that distribute a wide array of capabilities and services. For instance, SAP HANA can access, store and process AI lifecycle data from any source, while SAP’s Business Technology Platform supports AI-driven data orchestration through an open-source framework. This makes it possible to build a variety of tools including robotic process automation, chatbots and advanced machine learning programs and models.
The widely adopted open-source platform is designed to aid in the development and training of machine learning models. It includes a diverse ecosystem of tools, libraries and community resources that help developers and data scientists construct a wide variety of applications, including mobile and IoT tools. TensorFlow offers various pre-built models and datasets from Google, Kaggle and others. It has a variety of AI partners, including LabelBox, SpringML, Paperspace, Quantiphi and Stradigi.
The vendor’s Support Suite delivers a highly automated AI-based platform that fuels sales and support functions across multiple channels. It includes automated conversational AI chatbots and machine learning features that streamline and coordinate connection points and messaging across email, social media, and voice interactions. The Zendesk platform now supports more than 40 languages and delivers an assortment of products for small, medium and large enterprise.
These AI software solutions assist organizations in studying and preventing cyberattacks.
Formerly known as Symantec, NortonLifeLock is one of the most popular companies in this list. NortonLifeLock offers an array of cybersecurity tools, all driven in some part by AI. Perhaps its most popular tools are its Norton and Avira Antivirus tools. These are security tools mainly targeted towards home users and small businesses. Although these tools are very popular, NortonLifeLock’s consumer-first approach might not make it the best option for enterprise businesses looking to scale.
CrowdStrike is a leader in the AI cybersecurity space. The Sunnyvale-based company leverages the power of AI to protect against zero-day attacks and prevent future breaches from occurring. Their primary drawing point is their native cloud support, which significantly reduces operational costs for businesses.
A leader in the cybersecurity industry, Darktrace employs self-learning AI that pulls from real-time data. To put this in context, this steers away from the traditional model of drawing from historical attack data, and better ensures protection against zero-day attacks. Darktrace’s AI approach also integrates in whichever system businesses wish to protect, whether that be email or cloud systems.
LogRhythm is another platform that offers a direct alternative to FireEye’s security operations SaaS platform. LogRhytm’s NextGen platform is built with a similar philosophy to Query.AI, in that it seeks to make data and cybersecurity comprehensible for businesses that might not be experts in that field. Still, its solutions are anything but simple. LogRhythm provides tools for cloud security monitoring, cyber crime, endpoint threat detection, security analytics, and more.
Blue Hexagon is AI driven cybersecurity built primarily around cloud protection. This is especially true for AWS, GCP, and Azure-based businesses. The three main industries Blue Hexagon is equipped for are financial services, healthcare, and retail. Although their cloud-native AI-security can be implemented for a variety of use cases and industries.
Cylance, acquired by BlackBerry Cybersecurity in 2019, was one of the first machine learning based cybersecurity firms on the market. All of its products, whether it be its endpoint security system, home-based antivirus, or even its consulting services, integrate AI technology.
Query.AI is a newer player in the cybersecurity firm space that’s set on reducing costs and making security more understandable for businesses that might not be experts in the space. Similar to Darktrace, operational costs are cut significantly due to its lack of a central repository. Furthermore, Query.Ai guides clients through data so they develop an understanding of what the technology is exactly offering.
An older, yet still major, player in the cybersecurity industry, Fortinet was founded in 2000 and has continued to adapt to the advancements made with AI and cybersecurity. Fortinet integrates AI, machine learning, and automation in its endpoint security, breach protection, and security operations centers assistance.
FireEye, similar to Fortinet, has been around for a while now. Founded in 2004, FireEye has made the transition from threat research into providing a range of cybersecurity tools rooted in AI technology. The firm’s primary product is its SaaS security operations platform: Helix Security. This is a user-friendly event and threat management platform built for a variety of business types and, of course, dependent on data and AI. The main industries FireEye is built for are financial institutions, higher education, government, and healthcare.
Deep Instinct is a startup that’s received considerable attention due to its deep learning framework. Their primary claim is that simple, machine learning-based models do not tap into the potential of AI with cybersecurity. Deep Instinct’s deep learning model trains itself as your businesses’ data set grows, and it does this with a hands-off approach. Deep Instinct claims that its service requires very little updating. This autonomy can help teams focus on their operations without the worry of cybersecurity attacks.
These AI software solutions provide virtual assistance to employees and customers, often using natural language processing (NLP) technology.
7.ai’s core value lies in improving the customer experience (CX) through its conversational AI solutions. Its primary product is the Engagement Cloud, a single SaaS platform that features AI-driven chat, messaging, and voice channels. 7.ai allows you to upload chat transcripts, which it then uses to learn and discover customer intents. This helps build the customer journey with minimal human-intervention, allowing 7.ai to guide conversations across the most appropriate and efficient channels.
Based in Toronto, Ada’s conversational AI caters to marketers and customer service departments. Like many other conversational AI companies, CX and customer insight comprise the heart of their technologies. Businesses can leverage Ada CX, which combines its Ada Engage and Ada Support features in a centralized chatbot, to build personalized customer journeys for new and existing users.
Trusted by companies such as Zoom and McAfee, Aisera offers solutions for call centers, customer service, employee experience, HR, IT, and sales. Aisera’s Virtual Assistant draws from over five billion intents and one trillion phrases from multiple industries to continually train and improve its CX. Perhaps its most unique feature is its employee experience offering. With Aisera, businesses can set up 24/7 support systems for employees to finish onboarding, as well as perform more clerical tasks like signing up for a 401(k).
Amelia’s flagship product is its self-titled virtual agent. Amelia draws on episodic memory, process memory, intent recognition, and emotional intelligence to respond to customer and user queries. Amelia is fluent in 10 languages and can learn more than 100 if necessary. Amelia is particularly trusted by enterprise businesses, with over 550 clients globally.
Based in China, Baidu is one of the first conversational AI providers in the region. Because of this, Baidu offers one of the largest semantic asset libraries from a variety of industry verticals for the Chinese language. In fact, Baidu’s conversational AI pulls from billions of images and videos through its search engine to cover industries such as finance, telco, aviation, and more.
ContactEngine offers a number of solutions for a range of businesses and use cases. This includes conversational AI for teclos, Covid-19 comms, government, and retail banking. ContactEngine’s AI can respond to customers in less than half a second, as well as pin any human agents on conversations that need human interaction.
Based in California, Inbenta is a no-code solution targeted towards e-commerce businesses in need of conversational AI. Inbenta averages a resolution rate of around 80% with bots that have no prior training. Furthermore, its offerings integrate seamlessly with e-commerce and helpdesk solutions such as Salesforce and Zendesk. Inbenta can answer based on semantic information from these integrated solutions as well.
Kore.ai, similar to Aisera, offers both customer and employee experience conversational AI. Because Kore.ai, similar to Inbenta, is a no-code solution, both business owners and developers can collaborate to build storyboards and customize virtual assistants as they please. This is especially helpful for designers who want to track and tweak the customer journey that Kore.ai is building.
Openstream provides conversational AI for four primary industries: Contact centers, insurance, financial services, and healthcare. One unique feature of Openstream’s offerings is its multisensory input of face, voice, gestures, and vision to help train its intents and entities. It can study utterances, reasons, and infer user intent through this method.
Based in Washington, SmartBotHub offers solutions for risk management, telecom, financial services, as well as retail and healthcare. Again, this solution offers no-code tools for business users who are not developers or data scientists. SmartBotHub’s team offers account managers for onboarding assistance, from iteration to deployment.