25 Terms for Artificial Intelligence in Business Explained

Artificial intelligence has swept through the marketing and sales departments across all industries.

According to Salesforce, 84% of marketers report using AI today. Back in 2018, less than 30% said AI was a part of their marketing strategy.


Despite its growing popularity, many managers and marketers may not be aware of all the terms associated with AI.

25 Artificial Intelligence Terms You Need to Know for B2B

Bookmark this page, so you always have it handy when you need to reference a term.

1. Algorithm

While the coding behind algorithms is complex, the concept is simple. An algorithm is just a set of rules you give to a computer system so that it can complete a specific task.

Algorithms can act independently – like when Netflix recommends its original content by ranking it as “important.” They can also work in layers – like how YouTube or Spotify – use millions of other sessions to recommend the best content for you.

2. Artificial Intelligence

The idea, practice, and study that computer systems can complete tasks with similar or better quality than a human.

3. Artificial Intelligence Engine (AI Engine)

A system of interworking algorithms, neural networks, and machine learning techniques. An AI engine can consume data from first-party interaction or receive data from third-party input.

You interact with an AI engine every time you scroll through Netflix, browse Spotify recommendations, shop on Amazon, or read content in the Hushly resource center.

AI engines include different models like collaborative filtering and session similarity models to create a hyper-personalized and interactive experience for everyone.

4. Artificial Neural Network

A system of algorithms and artificial intelligence that mimics the same pathways in the human brain to learn, adapt, and carry out tasks.

5. Automation

The act of unloading tasks once completed by humans onto artificial intelligence – such as email marketing and lead scoring.

6. Backpropagation

Backpropagation is short for “backward propagation of errors” and is a type of algorithm. Backpropagation trains neural networks until the initial result (output) is as close to the desired result (output) as possible.

7. Chatbots

A text messaging system that is powered by artificial intelligence and human input. The human sends messages on one side. The artificial intelligence responds on the other side. Some chatbots are extremely advanced and include machine learning features to adapt based on new information (see point 14).

Chatbots are not to be confused with live chat, which involves two real humans communicating.

8. Classification

Using an algorithm to set up categories and place data entries within specific categories.

9. Clustering

Using an algorithm to identify patterns – often undetectable to humans – to group pieces of data into larger sets.

10. Collaborative Filtering Model

A type of supervised machine learning where an algorithm compares a current session’s behavior to previous sessions to offer personalized content recommendations.

This is like Spotify’s “people who listened to XYZ also liked ABC.”

11. Content Similarity Model

A type of unsupervised machine learning that uses natural language processing to group content assets and make recommendations based on a single session’s behavior.

12. Data Mining

Digging through massive data sets to find patterns, groupings, or recurrences. Both humans and machines can mine data. However, AI can often find patterns much faster and efficiently than humans.

13. Deep Learning

A type of machine learning where multiple neural networks study massive data sets and make conclusions – similar to how the human brain works.

14. Digital Ecosystem

Your martech stack or combination of tools you use to implement AI, CRM, email, and associated technologies.

15. Machine Learning

A type of artificial intelligence where algorithms can improve themselves based on access to new data or regular input.

16. Natural Language Processing

A subset of artificial intelligence where algorithms are trained to consume, interpret, manipulate, and analyze characteristics specific to how humans communicate with each other.

Google’s BERT update focused on improving its natural language processing, and Google called it the most important update in years.

17. Reactive Machines

Algorithms and AI tools that immediately analyze, predict, and react to situations in real-time. Reactive machines do not store data.

18. Recurrent Neural Networks

A vast neural network that uses their internal memory to make decisions. Recurrent neural networks can recognize patterns and sequences while consistently improving themselves.

19. Reinforcement Learning

Maybe you’ve heard of positive or negative reinforcement in the context of raising kids. AI can learn using reinforcement too. The algorithm interacts with its environment and receives either rewards or punishments depending on how it responds.

20. Session-Based Similarity Model

A type of deep learning that looks for patterns across each visitor’s entire session history by following the path they took. The algorithm then looks for similar patterns in future visitors to recommend relevant pieces of content.

21. Structured Data

A concrete set of data that you can easily understand, analyze, and search. These are your Excel sheets full of data.

22. Supervised Learning

This type of machine learning mimics a student and teacher relationship. The AI system is taught to produce a desired outcome using provided data sets.

23. Turing Test

The infamous test that was conceived by Alan Turing to judge how an algorithm or artificial intelligence system compares to the human mind. If the algorithm can convince a human that they’re communicating with another human, the algorithm is said to pass the Turing Test.

24. Unstructured Data

Data you can’t put a concrete set of numbers to – such as podcasts, audio files, videos, infographics, and image content.

25. Unsupervised Learning

Feeding unlabeled and unclassified information to an algorithm so it can learn and train itself without help. Where supervised learning is like a teacher-student relationship, unsupervised learning is more like a self-study environment or open-book test.

Harness the Power of AI for Your B2B Website

Hushly’s AI engine brings the same personalization as top companies like Amazon to your B2B website. Best of all, you don’t need any serious AI or coding knowledge. The plug-and-play platform and price-per-lead cost make it easy for anyone to take advantage of AI-driven personalization.

Find out how AI can increase lead conversion by 51% and quality by 59%.

6 Strategies to Use Artificial Intelligence in Business Marketing

hushly blog

Artificial intelligence is taking over every industry.

When people think of AI, they tend to imagine robotic devices completing human tasks like bagging groceries or grilling burgers. The reality is, however, the use of artificial intelligence in business goes much deeper than that.

At least 18% of B2Bs already use AI in their marketing strategies and that figure rises every day. Plus, AI is effective. 84% of businesses using AI expect to see a return on their investment within a year.

Despite its growing prevalence in the business world, some marketers are still reluctant to adopt AI technology into their strategies. Here are a few tools and ideas to get you started.

the use of artificial intelligence in business

6 Benefits of Using Artificial Intelligence in Business

Artificial intelligence makes marketing work easier – A LOT easier.

Long gone are the days of sifting through massive data sets, piecing together segments, creating personalized content, and struggling to deliver it at the perfect time.

AI removes marketing’s most tedious work so you have more time to work on creating incredible content, connecting with leads, and building your social strategies.

1. Creating a Personalized Experience for Everyone

B2B buyers demand personalization. 85% of buyers will write off a vendor that doesn’t personalize the very first touchpoint. That’s a lot of pressure but the use of artificial intelligence in business marketing can create a personalized experience for everyone based on behavioral data.

2. Scoring Leads

Just think of how much time your team spends scoring leads each week. Artificial intelligence can sort through massive datasets faster and better than any human can. Not only does it make lead scoring easier, it delivers better results too.

3. Keeping Websites Secure

Cybersecurity is a major concern for B2Bs. According to the FBI, 50% of cybercrime targets B2B payment systems. Artificial intelligence can protect your processing systems and protect your databases from hacks.

4. Helping Leads Self-Nurture

Buyers complete up to 90% of the buying process alone without ever reaching out to anyone at your sales team. It’s important for all businesses to build websites that allow leads to conduct effective research with minimal time and effort.

AI and machine learning cater to your leads’ demand for instant gratification so they can research at their own pace without forms getting in the way.

5. Preventing Customer Churn

80% of B2B buyers will switch suppliers within the first two years citing poor customer experiences. You can identify potential churn and stop it in its tracks with powerful AI. Plus, using AI-driven website experiences can help customers feel appreciated and valued.

6. Verifying Lead Information

Did you know most B2B marketers are basing their strategies on data up to 40% incorrect? Not good.

It’s no surprise that an estimated 80% of businesses will abandon their data-driven personalization strategies by 2025.

Artificial intelligence removes the problem of bad data at its source by verifying lead data upon entry through publicly available information sources.

How Do Companies Use Artificial Intelligence?

Now that we’ve gone over some of the benefits, let’s look at how AI is changing business marketing for the better. Here are a few practical applications.

1. Human Lead Verification

Another piece of lead data expires every day. Every year

  • 34% of your leads change job functions or titles
  • 37% change their email address
  • 30% change jobs
  • 34% of companies change names

With an AI engine on your site, you don’t have to rely on collecting static lead information. Instead, AI cross-references every lead’s business email with publicly available information on sources like LinkedIn so it’s always accurate.

This is good for your leads too because it means they don’t have to spend time filling out forms when you’re only collecting an email address.

2. Personalized Exit-Intent Popups

Let’s be honest. No one wants to fill out a form as they’re trying to leave your website.

AI can help you prevent bounces and exits with personalized content recommendations.

Instead of confronting your visitors with an intrusive form asking for data while they try to tab away, they’ll receive a popup filled with relevant and useful content.

3. Chatbots

Chatbots have come a long way in the past few years. You don’t have to feel weird about adding chatbots to your site either because visitors have come to expect them.

People spend so much time online each day and they still crave conversation. AI-driven chatbots use machine learning to simulate real conversations and fill the gap where workers can’t.

4. Adaptive Content Hubs

Adaptive content hubs remove the old blog interface in favor of a technology-driven upgrade. Instead of forcing your visitors to scroll through categories and backward through old posts, AI offers personalized recommendations for everyone.

Using the same collaborative filtering and other algorithms like Amazon, machine learning studies your visitors and improves the longer you use it!


5. Self-Nurturing Landing Pages

Remember your leads complete up to 90% of the sales process alone without ever communicating with someone at your company. Self-nurturing landing pages are vital for giving them the tools they need.

A self-nurturing landing page uses content bingeing features and AI-driven algorithms – just like Netflix – to keep users hooked.

6. Effective Account-Based Marketing Strategies

Account-based marketing has picked up plenty of steam over the past few years and we have technology to thank for that.

AI makes it easier than ever to create relevant content for specific accounts and target them at the perfect time. You no longer need a massive marketing budget to pull off an effective ABM strategy because you have the power of efficient AI.

Embrace the Use of Artificial Intelligence in Business Marketing and Watch Leads Skyrocket

Hushly AI creates a personalized experience for everyone who visits your website – whether known or anonymous. You can spend less time organizing content on your website and nurturing leads because AI takes control of everything. Plus, it’s much more effective than humans!

the use of artificial intelligence in business