Have you ever wondered how does AI work and how it’ll change the working way of future generations? Before we delve into how it works, let’s first discuss what AI is. AI technology mimics human intelligence, allowing machines and computers to learn from experience via algorithmic training and iterative processing.

 

What makes AI technology beneficial?

AI offers multiple critical benefits that make it an excellent tool for virtually any modern business or organization, including:

Analysis

AI can analyze the data faster than humans, allowing it to identify patterns rapidly. Moreover, it can analyze larger datasets, allowing it to find patterns humans would miss.

 

Automation

Humans thrive on creativity, and repetitive tasks are mundane and mind-numbing for them. AI can effectively automate a repetitive task that humans do manually without having to take breaks or feeling any fatigue like a human would.

 

Enhancement

Through capabilities like optimized customer service, conversation bots, and better product recommendations, AI makes services/products smarter while enhancing customer experiences.

 

Accuracy

AI can provide more accuracy than humans. It can harvest and analyze data to make better decisions for tasks like recognizing malignant growths on x-rays, picking financial investments, etc.

 

Return on investment

Since AI can analyze complex, multi-variate relationships more effectively than humans, it increases the value of data. Ultimately, it’s a crucial tool for any organization that depends on data and operates at scale.

Now that we understand why AI is important for businesses and our daily lives let’s discuss how it works.

 

How does AI work?

 

Data collection

Data is the crown jewel of AI since AI accuracy increases along with the volume of data. Whether you’re using external data to complement your internal data or as the primary source to address a common issue, there’re 3 ways to aggregate it.

  • Prepackaged data – It may seem like a quick way to gather data, but sometimes it takes more effort than you planned. With prepackaged data, organizations often need to write code, create APIs for integration, and make other customizations.
  • Public crowdsourcing – Multiple organizations use public crowdsourcing services like Amazon Mechanical Turk to distribute the data collection and preparation work. Tasks include data normalization, image recognition, algorithm training, etc.
  • Private crowds – Organizations that need confidentiality agreements to work on their data and faster turnaround turn to private crowds of data specialists. Private crowds offer better accuracy with the data collection, labeling preparation, identification, and training tasks.

 

Analyzing the data

AI helps marketers accelerate their decision-making by analyzing large data to identify consumer behavior, trends, and other relevant information. Marketers can quickly adapt their strategies to meet customer needs better. By utilizing AI, marketers spend less time stumbling over technological obstacles and more time developing strategic and creative campaigns.

Moreover, AI can analyze two types of data:

  • Quantitative data – Data that can be measured and used for statistical analysis. AI uses data mining to find trends and patterns from quantitative data.
  • Qualitative data – Data that can’t be measured and is used for descriptive purposes. Typical qualitative data research includes interviews, surveys, and focus groups.

 

By analyzing the data from different sources, AI-powered systems provide data-driven insights about what’s working and what’s not. For marketers, it can provide predictions about product development, customer preferences, and marketing channels. Furthermore, it can also forecast product/service demand based on seasonal trends, available stocks, past purchasing behavior, etc.

To analyze the data, there’re different tools available to sort the data and visualize it for insights. The best tools used by data analysts quickly create interactive visualizations, support complex computations, have no speed or memory constraints, and seamlessly integrate with existing applications.

 

 

Implementing the AI-driven insights

AI-driven insights can be utilized in multiple industries, including:

    • AI in marketing

AI in marketing helps with predictive analysis and streamlines marketing efforts. For instance, AI programs can provide information about potential leads based on detailed demographics. Moreover, AI insights can help with product personalization. For example, Under Armour has used IBM’s Watson to combine third-party data with customer data to develop a personalized health and fitness tracking app, “Record.”

    • AI in manufacturing

In the manufacturing industry, AI provides innovative production-level designs using a generative design process. The designer input the company’s historical and existing product catalog, goals, and parameters like materials, costs, spatial, etc. The software then creates different permutations to choose from and improves its future performance by learning from each iteration.

    • AI in business

AI algorithms integrated into analytics and CRM platforms can uncover insights to serve customers better. For instance, websites incorporate chatbots to provide immediate customer service. Click here to learn more about the role of AI in chatbot success. Besides that, job position automation has now become a talking point among IT analysts.

 

AI has proven to be crucial to businesses for everything from automating redundant tasks to improving customer experiences. According to Technavio, the global AI-as-a-service (AIaaS) industry is predicted to expand by $14.7B between 2021 and 2025. In today’s era, where data is rapidly accumulating, companies implementing AI to make informed decisions have gained a competitive edge.

Now that we’ve discussed how does AI work let’s delve into why it’s essential to integrate third-party AI software or partner up with third-party service providers.

 

Top reasons to integrate third-party AI tools or hire AI specialists’ company

Marketers and businesses must utilize AI-as-a-service or AIaaS to experiment with multiple objectives with lower risk and upfront investment. The top reasons for using third-party AI technology include the following:

 

1. You don’t need to have up-to-date engineering skills

If you don’t have an AI programmer, AIaaS can be used to add a layer of no-code infrastructure. At any point during the setup process, companies that deliver AIaaS mainly don’t require any technical knowledge or coding.

 

2. Transparency

Third-party companies do not just give you AI access while decreasing non-value-added labor; it also offers transparency. Of course, you can create an AI system from scratch, but it will require too much computational power. The cost of creating a system will be significantly high. However, third-party AI systems allow you to pay on a usage basis. Some systems even give more control over AI automation.

 

3. Scalability

With third-party AI software or company, you can begin with smaller projects. It helps you determine whether it would be a suitable fit for you. Additionally, it helps you comprehend your unique needs. As you gain expertise with your data, you can fine-tune your service and scale it up or down as project complexity increases. Moreover, businesses with limited data infrastructures have adopted third-party AI solutions for their data management needs since they can easily be integrated with the cloud.

 

What are the top AI technologies that help marketers in scaling a business?

 

Advanced machine learning

Machine learning enables predictive algorithms to improve in accuracy over time. It’s used to find the most relevant audiences and determine creative elements that’ll resonate with these audiences.

 

Neural networks

Neural networks are at the core of advanced AI. They enable marketers to identify complex patterns in customer purchasing behavior. Neural networks are also used for bid optimization, helping marketers find the right balance between ROI and costs.

 

Natural language processing

NLP gives computers the ability to analyze speech and text. This capability enables marketers to extract valuable insights (like customer personalities and moods) from social media platforms and other sources. It also allows the integration of automated communication tools like chatbots.

Computer vision

It enables pattern recognition and image processing to accelerate and optimize the creation of better creatives.

 

Let’s look at a few case studies of AI in marketing to help you understand how big brands utilize AI.

L.L.Bean used AI marketing to improve conversions for new products.

L.L.Bean intended to increase awareness for its high-end athleisure line of clothing. By collaborating with IBM Watson Advertising Accelerator, they reached the appropriate audience with the proper creative ad units. With the help of this campaign, they were able to increase orders by 48% while lowering costs by 76% for each site visit and 68% for each order.

 

The American Marketing Association used AI marketing to write personalized emails.

The AMA wanted to serve its subscribers with the most relevant content. Therefore, they pulled in rasa.io. It’s an AI system that uses machine learning and natural language processing to generate personalized newsletters and offers newsletter automation. By utilizing an AI system, AMA significantly improved reader engagement.

 

The final verdict

AI technology redefines how business operations are carried out in different fields, such as marketing. Organizations are exploring new ways to reap significant benefits from this technology. Because of AI’s strong data analysis capability, businesses can now reduce the hardware costs to manage large amounts of data. Moreover, it reduces human efforts and works to manage everything manually. For content creation, AI is a really handy tool that increase productivity drastically. One human input is sufficient with AI, and AI systems do the rest of the work.

Besides that, storytelling, empathy, and compassion are all human qualities that technology cannot yet emulate. AI is ultimately unconstrained by human limits. If Moore’s Law holds steady for some time, there’s no telling what AI will accomplish in the near future. In the meantime, we understand how does AI work and why it’s high time for businesses and marketers to implement AI to obtain sustainable growth.