Artificial intelligence is becoming very popular in the world of marketing. According to Statista80% of industry experts integrate some form of AI into their online marketing activities.
However, if you’re like me and are unfamiliar with the AI that you’ve seen in science fiction stories i robot Or black Mirror — You’re probably wondering what AI is and how to use it in marketing.
Is AI really as it appears in the movies? This article will explore the definition of AI, the different types of AI, and how AI can improve marketing processes.
What is Artificial Intelligence?
What are the four types of artificial intelligence?
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What is Artificial Intelligence?
Artificial intelligence is the use of computer systems to perform tasks that would normally require human intelligence, such as visual perception, speech, translation, decision-making, and problem-solving.
So now that you know what AI is, let’s find out how it works.
How does AI work?
AI combines large sets of data with intelligent, repetitive processing algorithms to learn from patterns and features within the data being analyzed. AI continuously processes data and learns from it.
At each round of data processing, the AI system tests and measures its own performance to gain additional expertise.
AI can complete thousands, even millions, of tasks repeatedly – improving its performance in a short amount of time. However, there are many types of AI, each with its own capabilities and limitations.
What are the four types of artificial intelligence?
The four types of artificial intelligence are reactive, limited memory, theory of mind, and self-awareness.
reactive
A reactive AI can only use its intelligence to react and respond to the world around it. It cannot store memory; Therefore, it cannot rely on past experiences to inform decision-making or problem-solving in real time.
Reactive machines can only accomplish a limited amount of specific tasks. While this may seem like a drawback, it has its advantages. A reactive AI will react in the same way to the same stimuli every time – making it reliable and trustworthy.
One of the best-known examples of reactive AI is dark blue, a supercomputer built by IMB in the 1990s that won a chess match against chess champion Garry Kasparov. Deep Blue can identify the pieces on a chess board and how each piece might move based on the rules of the game.
However, the AI couldn’t try to anticipate its opponent’s next move, nor could it think of ways to better position its pieces.
limited memory
Limited memory AI stores past data and predictions and uses it to make decisions – looking at past data to predict the future. Limited memory AI occurs when a machine learning model is trained continuously to analyze and use new data.
Limited-memory AI has six steps to follow.
- Create training data.
- Build a machine learning model.
- Enable the model to make predictions.
- Whether the model has received human or environmental feedback.
- Store the feedback as data.
- Repeat all the above steps in one cycle.
Examples of limited memory AI are self-driving cars. Self-driving cars identify citizens crossing the road, traffic signals and other data to make better driving decisions and avoid future accidents.
Another example of limited memory AI is HubSpot adaptive testing tool. The Adaptive Testing feature splits the traffic equally between the first page variations.
As HubSpot learns how these variations are performing, we automatically adjust traffic, so optimal-performing variations are shown more than poor performers.
theory of mind
Theory of mind sounds like AI – is theoretical. AI has not yet advanced to this extent, so theory of mind is still in its innovation phase. This type of AI interacts with the thoughts and feelings of humans. Theory of mind would lead to a better understanding of the entities with whom they interact in order to understand their needs, beliefs, feelings, and thought processes.
For example, we now know that self-driving cars are a form of limited mind AI. If these autonomous cars could analyze and understand the mental and emotional state of their drivers in order to improve safety, they would evolve into Theory of Mind AI.
self awareness
Once theory of mind becomes a reality, the next type of AI to emerge will be self-awareness. At this point, machines will not only be aware of humans’ emotions and mental states—they will also be aware of themselves. A self-aware AI would have a human-like consciousness and understand its existence in the world and with others.
How marketers can use AI
Can perform parts of AI marketing process – like task automation, campaign personalization, and data analysis – so you can spend less on repetitive tasks and more on strategy.
For example, our HubSpot mobile app has a business card scanner uses AI To take the name, email address, and other contact information on business cards and map them to your HubSpot properties. instead of spending time Entering this data manually yourself AI automates the process For you.
Pros and Cons of AI
So, now that you know what AI is, how it works, and the four types of AI—let’s dive into the pros and cons of AI technology.
artificial intelligence professionals
fewer errors
Humans can make mistakes, miss deadlines, misspell words, and get math wrong. Sometimes we get distracted or go through burnout; This is human nature. By implementing an AI-powered automated system, you are reducing the risk of errors.
24/7 uptime
AI also does not need rest and can run 24/7. AI can run continuously and continuously as long as it is programmed. This makes AI more ideal than humans for repetitive tasks, allowing marketers and business owners to focus their efforts elsewhere.
Can quickly analyze large data sets
As I mentioned earlier, humans sometimes make mistakes – especially when processing large data sets. One solution would be to go slow to prevent errors, but time is money in marketing.
Fortunately, AI machines can process large amounts of information and data quickly, making them more efficient than humans under time constraints.
Cons of Artificial Intelligence
lack of creativity
AIs are programmed to react to stimuli based solely on past data, which means they are not well suited to create innovative solutions in the present. Data from the past can help predict future outcomes, but data alone is not always sufficient to address never-before-seen variables.
Therefore, AI would be better suited for “grunt” or mundane work. From a marketing perspective, humans can develop a creative marketing strategy, while AI can take care of the repetitive tasks of implementing the plan.
impersonal
Sometimes, human connection is the best way to build a rapport with your audience. While a self-aware AI is possible in the future, current AI machines cannot completely mimic the human experience.
From a marketing perspective, applying AI to every customer interaction can drive a wedge between you and your audience. I mean, there’s a reason so many of us can remember shouting, “Speak to a representative!” When we get tired of talking to a robot on the phone.
future of ai in marketing
According to Grand View ResearchThe global AI market is expected to reach $1,811.8 billion by 2030, up from $136.6 billion in 2022.
Artificial intelligence, theory of mind and self-aware machines seem like things from the distant future. Still, the reality is that AI is here now, and its impact across industries is likely to grow in the years to come.
While AI has pros and cons, it is important that marketers keep up with its progress and be open to using AI to streamline certain processes in order to keep up with competitors.
