Technology is continuously evolving and businesses big and small are making use of different technologies to stand out in the competition. One such technology is artificial intelligence (AI), which can help users, including application developers and marketing/sales professionals, analyze data to make decisions and predict future outcomes.

Artificial intelligence software is capable of learning, computing, and solving complex problems with high efficiency. It consists of machine learning, neural networks, and natural language processing technologies.

Artificial intelligence software is capable of intelligent behaviour which is being adopted by different industries for a variety of applications such as smartphone assistants, ATMs that can read checks, voice and image recognition software on social networks, serving ads on websites based on users' search history, and personalized recommendations based on customer purchase history.

Here’s what we'll cover in this buyers guide:

What is artificial intelligence software?
Common features of artificial intelligence software
What type of buyer are you?
Benefits of artificial intelligence software
Key considerations
Market trends to understand

What is artificial intelligence (AI) software?

Artificial intelligence (AI) software is a computer program that imitates human behavior such as learning, reasoning, problem solving, and analysis. These systems can analyze large data sets to find correlations and patterns and use these patterns to make predictions and provide valuable insights.

Some of the applications of artificial intelligence software include speech recognition, natural language processing, expert systems (designed to solve complex problems by replicating the decision-making capabilities of a human), and augmented reality. These applications can be in the form of smartphone assistants, AI chatbots, and voice and image recognition software.

Analytics features in New Relic One Software (Source)

Common features of artificial intelligence (AI) software

Machine learning	Applies machine learning (ML) algorithms to business data (such as sales, revenue, and transactions) and builds analytical models in order to learn from data, identify patterns, and make decisions with minimal human interference.
Natural language processing	Understands, interprets, and manipulates human language such as speech and text. It can be utsed in a variety of business areas such as customer service, customer experience, sales (in the form of chatbots), and data analysis.
Predictive analytics	Uses data mining, statistics, ML, and AI to analyze data and user behavior to make usage predictions.
Speech recognition	Processes human speech into a written format. It is also known as speech-to-text.
Virtual personal assistant (VPA)	Performs tasks and services for an individual based on commands and questions. Examples of VPA include Google Assistant, Siri, and Alexa. Users can ask the assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal commands.
Chatbot	Conducts online chat conversations via text or text-to-speech, as an alternative or precursor to direct contact with a live human agent.
Multi-language	Detects text or speech in multiple languages and can convert that text or speech into another language.
Process/workflow automation	Defines process paths and applies the logic to enable automatic creation of future processes and workflows to minimize overlap, repetitive processes, and human error.

What type of buyer are you?

Before purchasing an AI solution, you should determine which buyer category you're in so you can choose the right tool. The majority of buyers fall into the following categories:

Developers: Software developers and computer programmers work on building and creating software and applications by writing code, identifying bugs, and running software tests throughout the software development lifecycle. But these tasks are prone to human error and take a lot of time, and repetitive efforts not only delay the development process, but also impact the quality of the end product. Artificial intelligence software, with the help of machine learning capabilities, can handle repetitive tasks such as testing the software, detecting and fixing bugs before a product is released, and recommending changes. Using AI software will allow developers to focus more on design and feature building, as it enables fast and accurate testing that shortens the development process, and ensures a high-quality end product. An open source AI solution that provides code libraries, data preparation, model deployment, debugging, and integration with other languages such as Python, Java,and C++ would be suitable for these needs. Open source platforms allow developers to easily build and deploy applications that are customized for organization or customer needs.
Marketing and sales professionals: These professionals are looking to acquire customers, maintain brand loyalty, and build stronger relationships with their customers. They need to understand customer emotions, collect and analyze feedback, and study trends that can impact their marketing efforts. Software with AI capabilities are capable of doing all these tasks with minimum human intervention and provide insights that otherwise would go unnoticed. It can also automate tasks to save employees time on repetitive work such as answering customer queries, recommending products, capturing leads, and providing personalized experience to customers throughout their journey. An AI tool that includes machine learning, natural language processing, speech recognition, and predictive analytics along with multi-language features would help such buyers to get actionable insights, automate tasks, and address customer problems efficiently.

Benefits of artificial intelligence software

More accurate data analysis: With the growing number of devices in use, the data generated from these devices is increasing day by day. Manually analyzing this huge volume of data can be cumbersome and prone to errors. AI machine learning algorithms are capable of sifting through data much faster than humans and providing actionable insights for you to make informed business decisions.
Improved customer service: AI capabilities allow you to gain real-time insights across all customer contact channels. Machine learning and natural language processing applications are being used in contact centers and customer service departments to solve customer problems by solving their basic and redundant issues without the need for human intervention. This allows your agents to focus on more complex problems, which in turn boosts customer experience.
Automation: AI platforms can automate all kinds of tasks your team would otherwise find tedious and time-intensive. The range of tasks from predictive maintenance to filling in common phrases in your email can be automated using an artificial intelligence tool. Additionally, these platforms are capable of taking care of multiple functions simultaneously, which increases the productivity and decreases the time spent on tasks such as such as shortlisting CVs, employee scheduling, and emailing.
Predictive capabilities: Artificial intelligence solutions have predictive functionality that can analyze historical data to detect corrections and patterns to predict outcomes such as customer churn, equipment maintenance, and fraud detection. Such predictive capabilities can help your organization against any serious losses or create opportunities for business value.

Key considerations:

Security: Artificial intelligence tools are capable of going through a huge volume of data (historical or confidential), performing analytics, providing actionable insights, and predicting the future. This makes security an integral part of such tools. The tool you select should have data protection and security measures in place around the data it collects, analyzes, and communicates with other devices. Also, ensure that the tool complies with industry-security standards such as General Data Protection Regulation (GDPR). This feature will help you maintain privacy, and prevent theft, data loss, and any kind of fraud.
Software type: It is important to consider whether you need a free, open source AI software, or a paid version of the software. If you are an independent app developer looking to build machine learning models, develop advanced applications, and speed up research and discovery, you can opt for a free and open source AI platform. Such tools provide pre-built algorithms and easy-to-use interfaces that will help you build and deploy customized models according to your needs.

But if you are looking to integrate AI functionalities into your business outcomes, such as perform predictive analytics on your customer data, support digitization process, and integrate AI to your existing software such as a custom built chatbot, a paid version of AI software will better suit your needs. A paid version will provide better security for your data, provide custom integrations, and give you greater computing power.
Additionally, software requires more maintenance compared to commercial versions as it constantly evolves because of user suggestions and requires a dedicated IT team for implementation and deployment. A commercial version of AI software is comparatively easy to implement as the third-party vendor takes care of it with their integration support.

Trial version: Artificial intelligence is a technology with vast areas of applications and functionalities. Before deciding on any software tool, you should take time to understand the working and setup of the tool, the business value it can provide, and its learning curve. For this, it is important to look for a software that provides trial versions to help you ensure it is the right option for your company before making a purchase.

Market trends to understand:

Here is a market trend to keep in mind when selecting an artificial intelligence platform for your business:

Convergence of artificial intelligence (AI) and Internet of things (IoT): The Internet of things combined with artificial intelligence has brought us artificial intelligence of things (AIoT). While IoT lets devices interact using the internet and provide data around it, AI makes these devices learn from their data and experience in order to drive smart actions. AIoT is capable of creating intelligent machines that can simulate smart human behaviour while also supporting decision-making with little or no human interference. This includes voice assistants (such as Alexa, and Siri), fleet management, drone monitoring and delivery, and healthcare wearables. Gartner estimates that by 2022, more than 80% of IoT projects will have an AI component which will help companies to gain capabilities they earlier could not achieve by applying AI to specific business problems.

Note: The application selected in this article is an example to show a feature in context and is not intended as an endorsement or recommendation. It has been obtained from sources believed to be reliable at the time of publication.

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