How AI Works: The Basics You Need to Know (2023)

artificial intelligence technologycome a long way from the days ofIBM Deep Blue, a computer designed to play chess against humans. Today, AI software can improve existing workflows, predict customer behavior, and much more.

AI is rapidly shaping the marketing landscape. Your team needs to adjust its technology stack to keep up with the competition.

Let's look at what AI is and how you can use this technology to save time, improve the quality of your leads, and ultimately get better sales.

AI can mimic human judgment and make decisions in real time. In other words, artificial intelligence is programmed to think, act and react like a real, living human being.

AI should not be confused with automation. While automation and AI use real-time data to perform a function, the mechanics and output are very different.

For example, automation requires manual data entry to perform a specific task. An algorithm is used to repeat this task regardless of what the data says or whether there is an error.

AI, on the other hand, is machine learning. That is, it requires a data entry. As the data is processed, the AI ​​can identify behavioral patterns and errors, then adjust its functions and algorithms as needed.

AI is growing in popularity and can be used across multiple industries. Let's take a look at the benefits of using it.

While AI isn't exactly foolproof, it's getting pretty close. There are many benefits to using AI in your workflows and processes. Here are just a few examples of its benefits.

How AI Works: The Basics You Need to Know (1)

1. Reduces human error.

Let's be honest. Sometimes people make mistakes. After all, we are only human. The problem with a mistake is that we can usually learn from it, process what we learn, and try not to make the same mistake again.

Artificial intelligence works the same way. Although AI acts and functions like a human being, it can significantly reduce human error by helping us understand all possible outcomes and choose the most suitable one.

AI uses real-time data to predict alternative outcomes. Data and predictions help us better understand our options, the outcomes and the impact of those outcomes.

This is especially useful in business. Decision makers can consider all possibilities before proceeding.

2. Helps in data research and analysis.

Another advantage of AI is the use of technology for research and data analysis. AI technologies are smart and can collect the necessary information and make predictions in minutes.

What would normally take a person months of research can now be done in much less time.

The data collected by the AI ​​and the analyzes performed are invaluable. With the information collected by AI, your data analysts can make smarter, more informed decisions in less time.

Leverage data collected by AI along with the work of your data analysts.

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3. Can make impartial and wise decisions.

With the right data, AI removes bias from decision making. For the best unbiased results with AI technologies, you need to enter thethe most accurate information and records.

When AI is given the best data, it can accurately predict outcomes, solve problems, and properly perform its functions without human preference for any particular desired outcome.

However, if the data you feed your AI programs is flawed, you will likely get a biased result.

Be sure to verify the accuracy of your data to maximize this AI benefit.

4. Performs repetitive tasks.

While automation and AI are not the same technologies, AI can act as an augmented version of automation, meaning it can be used to perform repetitive tasks and suggest alternative outcomes.

By using AI to perform repetitive tasks, your employees have more time to take care of other, more complex matters, such as B. closing a sale or checking in with current customers on your listkeep customers.

AI can be used to perform a variety of tasksrecurring tasks. AI can take on tasks in the HR department such as B. Employee onboarding.

AI can also be integrateda chatbot on your website. While a chatbot might not offer a human touch when interacting with prospects, using AI to automate interactions between your business and your customers can initiate processes and guide your customers through your pipeline.

For example, AI can help a potential customer initiate a new inquiry and gather important customer information and behavioral data. This data can then be entered into your CRM for later review.

How does AI work?

AI technology is complex and extremely useful for businesses. HubSpot has integrated AI directly into its software to extend existing workflows.

HubSpot's AI Can Do ItReveal team performancemonitoring sales calls and providing insights to the team. You can also optimize the contentCreate transcripts of recordings and calls.

If AI is a complex but necessary technology, how does it work?

Simply put, AI works by combining large datasets with intuitive processing algorithms. AI can manipulate these algorithms by learning behavioral patterns within the dataset.

It is important to understand that AI is not just an algorithm. Rather, it's a complete machine learning system that can solve problems and suggest outcomes.

Let's take a step-by-step look at how AI works.


The first step of AI is input. In this step, an engineer must collect the necessary data for the AI ​​to work correctly.

Data does not necessarily need to be entered in text; it can also be images or language. However, it is important to ensure that the algorithms can read the input data.

It is also necessary to clearly define the context of the data and the desired outcomes at this stage.

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The processing step is when the AI ​​receives the data and decides what to do with it. During processing, the AI ​​interprets the pre-programmed data and uses the learned behaviors to recognize the same or similar behavior patterns in real-time data, depending on the AI ​​technology.

data results

After the AI ​​technology processes the data, it predicts the results. This step determines whether the data and its provided predictions are a failure or a success.


If the dataset produces an error, the AI ​​technology can learn from the error and repeat the process differently. Algorithm rules may need to be adjusted or changed to fit the data set.

Results may also change during the adjustment period to reflect a more desirable or appropriate outcome.


Once the AI ​​completes its assigned task, the final step is scoring. The evaluation phase allows the technology to analyze the data and make conclusions and predictions. It can also provide useful feedback that is needed before running the algorithms again.

AI is of great use in business. However, it's important to choose the right AI technology for your business needs.

The four concepts of AI

As mentioned earlier, not every type of AI is right for your business, process, or dataset. There are actually four main AI concepts that you should consider.

1. Reactive machine

Reactive machines live up to their concept name. This type of AI can react or respond to data in real time. However, this AI is limited and cannot store information or build a memory bank.

Since it cannot store memories, AI cannot use past experiences to analyze data based on new data behaviors.

Reactive machine technologies are best used for repetitive tasks designed for simple results. Consider using reactive machines to organize new customer information or filter out spam from your inbox.

2. Limited storage

Unlike reactive machines, limited-memory technologies can store and use information to learn new tasks. A machine with limited memory needs pre-programmed data to function.

After processing this information, it can analyze data in real time to make predictions and observations.

Bounded memory technology is the most used AI technology in enterprises. In fact, this is the technology that makes self-driving cars work.

A chatbot is an example of limited storage technology. Chatbots use pre-programmed data to interact with customers and predict their needs based on their actions and requests.

3. Theory from Mind

Theory of mind technology is more advanced than limited memory. Like limited memory, theory of mind technology can store information and make observations based on the observed data in real time.

However, this technology is more advanced, which means it can respond to human emotions.

Theory of mind technology must be designed to understand that humans are complex, with individual thought patterns and past experiences that affect how they respond to specific stimuli. Because of this, theory of mind technologies are not yet fully developed.

As it stands now, AI cannot respond to humans in fully human ways.

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4. Confident

Self-Aware Technology takes Theory of Mind technology one step further. It can process information, store it, use it in decision-making processes, understand human emotions and feelings, and is also self-aware on a human level.

In other words, self-aware machines function like human consciousness and can have their own thoughts and feelings.

Self-confident technology is still a long way from being mature. However, scientists and researchers are taking small steps to understand how human emotions can be integrated into AI technology.

How to create basic AI

AI doesn't have to be overly complicated for you to benefit from it. You can use AI to perform repetitive functions that rob your employees of valuable time — time that could be spent building customer relationships or building customer relationshipsmake sale.

When using AI, consider the processes and workflows you can take off your employees' plates. In particular, think about processes that you can automate that you don't need to optimize because the AI ​​is doing its job.

Let's look at the basics of implementing AI in your workflow.

How AI Works: The Basics You Need to Know (2)

1. Define the problem.

Before you decide to integrate AI into your workflow, you should consider the processes your teams use every day, which are time-consuming and repetitive.

Does your team spend a lot of time sorting through data to find contact information for potential customers? Could they make better use of their time talking to potential customers and onboarding new customers?

Take some time to identify time-consuming workflows and make a list. From that list, choose a simple, repeatable process.

2. Define the results.

AI should improve its already established processes. Once you've created a list of the processes and workflows that can most benefit from AI, define your desired outcomes.

For example, AI can collect and classify customer data. But before the AI ​​can sort your potential customer base, you need to tell it what to look for and how to sort the information.

Make sure you clearly define the outcomes of your AI processes. AI works best when you have an end goal in mind.

3. Organize the record.

Having a rich and organized dataset to feed AI technologies is critical. If you don't already have your data in one place, it's best to do that before implementing AI. You don't want your program to lose critical data because it was stored on another system.

Use a CRM, for exampleHubSpotsto organize your data. You need clean data that the algorithm can read. This allows the AI ​​technology to understand the dataset and recognize its patterns and behaviors.

4. Choose the right technology.

There are hundreds of AI algorithms to choose from, each performing a task with varying levels of efficiency and quality. It is important to understand that not every algorithm will fit your dataset, problem, or desired outcome.

spend time searchingbest AI technologyand choose the one that best suits your needs. After choosing an AI technology, run the data to create a model.

5. Test, simulate and solve.

Now that you have the appropriate technology and a model for what you want the data to do, run the data again to test it out. This will help you to identify any issues that need to be resolved. When you're ready to use AI, embed it in your workflows and let it do the work!

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Now you and your employees have more time for more important and valuable matters.

AI use cases for marketers

AI technologies can significantly improvethe performance of marketing teams in differentWays.

We already know that AI can be used for chatbots on your customer facing websites. But there are many other ways to incorporate AI into your marketing game. See how.

sales forecast

Sales forecasting is like looking into a crystal ball. Only this crystal ball can predict future revenue margins for your business.

Analysts need to gather the necessary data from different sources to make a proper forecast. Then they collect customer data and behavior, compare it to historical data, and project future sales.

Data analysts often use automated algorithms to help them sort through historical data and track important new information. This process can take a long time.

But the good news is that it can be significantly accelerated with the help of AI technology. AI can store data collected by chatbots, analyze which customers are most likely to make a sale, compare real-time data with historical data, and make predictions and assumptions about future sales.

AI uses predictive analytics andcan predict predictions with up to 80% accuracy.

Targeted advertising and content personalization

Targeted advertising and content personalization is Marketing 101. Any good marketer knows that getting your brand in front of the right audience is necessary to drive more sales. AI technologies take a step further with targeted advertising.

You already know your target audience, but do you know exactly what they will do after seeing your business ad? The reality is that you can have a good indicator of customer behavior, but sometimes you miss the mark. AI can help you draw better conclusions.

AI can use predictive analytics to determine customer behavior and what potential customers will do after seeing your ad. The massive amount of advertising information and customer behavior data collected by the AI ​​can also show your customers the next matching ad.

lead generation

In the past, a marketer needed to run multiple ads, collect data from potential customers, create a customer profile, build a contact list, and start reaching out to potential customers. This process would likely take days and reduce time to market.

AI dramatically reduces the time marketing and sales teams spend on lead generation. AI can collect customer data, create customer profiles, and generate a contact list of potential customers who are most likely to make a purchase.

With the time saved, sales reps can make better use of their time by contacting qualified leads, building new customer relationships, and making that all-important sale.

dynamic pricing

AI isn't just about saving time for your employees. AI can help maximize profits and margins by enabling dynamic pricing.dynamic pricingit's a marketing strategy that many companies use to adjust the prices of their products to current supply and demand.

AI technologies use dynamic pricing models to predict customer behavior, supply and demand to alert sellers when to raise or lower the price of a product or service.

Optimize your business with AI.

While AI can be a complicated technology, your business doesn't need to use it. Artificial intelligence technologies can significantly improve your workflows, saving you valuable time and making more accurate predictions.

Brainstorm with your team to list potential processes that could be automated with AI software. Then find the appropriate AI technology that works best for you and your workforce. Start improving your business with AI today.

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