Things Business Leaders Should Understand About AI

Things Business Leaders Should Understand About AI

Artificial Intelligence is all over the news nowadays. You will find many startups and products putting AI in their domain names or in their product descriptions (Fun fact: .ai TLD is administered by the government of Anguilla).

While you may think that Machine learning and Artificial intelligence are same, but it’s not the case. ML is a subset of AI, and it has limited capabilities as compared to AI.

Usually, you will see that when people talk about using artificial intelligence in business, they think about automation. You will also find AI being put to use to optimize costs, processes and what not. Another use case of AI is generative in nature. We will learn more about it later in this article.

You might be interacting with AI regularly in one way or another. Alexa, Siri and Okay Google are few such implementations of AI being used in daily life. More and more services are being built on top of AI as we speak.

For business leaders, however, AI is important to be understood. One may think that AI is very technical and all related to programming and mathematics. But that’s just one part of the AI. The other part, that talks about business capabilities, is equally important.

The current state of AI

AI is essentially the process of understanding existing facts, figures, and information, while helping users to make better decisions which are close to reality. As we understand it today, AI is still evolving and will continue to evolve for a long time. This is because as we generate more data and facts, the more it will have to adapt and behave like a human.

AI has already accomplished the following things-

Unsupervised Learning: Beating the limitations to segregated data and labels used by conventional AI models. High-level artificial intelligence calculations are being prepared through unstructured information without human help. 

Federated Learning: Going past customary AI from a bound-together dataset, AI models are prepared locally on information subsets.

Transformers: Repetitive brain networks perform information handling successively. It replaces Transformers, which works on parallelized language handling. 

Neural Network Compression: Run-of-the-mill profound learning models are gigantic and should be compressed. Compacting them would make the neural networks more modest, quicker, and power-efficient.

Generative artificial intelligence: Moving a step forward from recognizing data sets to creating advanced ones.

What is Generative AI?

Generative AI is the process of creating new content by making the use of existing audio files, text or images. Through generative AI, computers recognize the basic pattern in the input and create similar content. Experts describe generative AI as one of the most dominating developments in the world of AI in the past decade. 

Various techniques are used in generative AI, such as generative adversarial networks (GANS), variational autoencoders, and transformers. Based on functions and activities, generative AI uses different frameworks and tools, some of them are:

  • Image Generators- DALL-E, Sharryai, Crayon
  • Video Generators- Synthesia, Lumen5, Flexclip 
  • Voice Generators- Replica, Speechify, Murf
  • Music Generators- AIVA, Amper AI, Jukebox
  • Content Generators- Frase 10, Rytr,
  • Design Generators- Khroma, Uizard, Colormind

For business leaders, generative AI can be extremely useful but very disadvantageous too. For example, it can help you in generating full blown articles and help their marketing teams in quickly ramping up their efforts with amazing returns on investments. Developers can use services like GitHub Copilot to write repetitive code quickly.

On the other hand, there have been cases of abuse as well. For example, someone recently generated a full-fledged podcast of Joe Rogan and Steve Jobs! Now, as a leader you won’t like someone using your speech and personality data and create fake content in your name. Talking about GitHub Copilot, Matthew Butterick, a lawyer, designer, and developer, announced he is working with Joseph Saveri Law Firm to investigate the possibility of filing a copyright claim against GitHub.

How is Artificial Intelligence Used in Business?

There are many ways companies can utilize AI; however, most applications focus on growth. With the help of AI and machine learning, businesses are finding new methods to improve and achieve their goals. The benefits for companies that come from AI include:

  • Increase efficiency by implementing process automation
  • Enhancing the speed or quality of service
  • Utilizing customer insights to guide the decision-making process
  • Exploring opportunities for new products and services

Examples of Artificial Intelligence in Business

AI is utilized by businesses far more often than you think. From operations to marketing and customer support, the possibilities of AI are virtually infinite. Below are some examples of how AI is employed in the business so that you, being a business leader, can lead your business accordingly. 

  • Improving Customer Service

Are you a visitor to a site and were greeted by chatbots? Chatbots are among the most frequent instances of users directly communicating with AI. From a business point of view, chatbots can help companies simplify their customer service procedures and free employees time to address issues that require more personalized attention.  IBM’s Watson is one such implementation of AI which has been trained to improvise existing customer service operations.

Chatbots generally use a combination of natural processing of language as well as machine learning and AI to recognize customer demands. Chatbot technology can also connect customers to a live person who is the best to answer questions.

  • Providing Product Recommendations

E-Commerce businesses can use AI to suggest products that align with the interests of their customers and keep them engaged. When you monitor your customers’ behavior on your site, it is possible to present your customers with products similar to those they’ve seen before. This is an excellent strategy for businesses operating in the eCommerce industry.

Another instance of personalized recommendations can be found in streaming services. Analyzing the kinds of films and shows you visit on streaming services can encourage you to use their site for longer durations of time by providing you with similar content.

  • Segmenting Audiences

Similar to recommending products, marketing departments can use AI to analyze groups of people and design specific campaigns. In highly competitive fields, reaching the appropriate target audience is vital. To ensure that marketing campaigns are more effective, businesses use data to determine what types of customers will be exposed to which advertisements. AI is crucial in predicting what kind of response customers will give. Google regularly uses ML and AI to serve better Ads to target audiences.

  • Analyzing Customer Satisfaction

Sentiment analysis is an approach that businesses employ to assess the opinions of their clients. With the help of AI or machine learning, companies collect information about how their customers feel about their brands. This may involve using AI to analyze social media content, reviews and ratings that refer to the brand. The results of this analysis help companies discover opportunities to improve their services.

  • Identifying Fraud

AI can also be utilized to aid companies in detecting and countering fraud threats. In the field of finance, there are tools which detect suspicious transactions by the use of machine-learning algorithms. For example, Telesign relies on over 2000 attributes, 5 billion unique phone numbers and over 13 years of historical data patterns to identify and mitigate fraud.

The only catch is data. One needs a LOT of data to train and make AI algorithms sharp and more accurate.

  • Optimizing Supply Chain Operations

If your business is having trouble delivering its products in the time promised, AI may be able to assist. AI-powered solutions can aid businesses by predicting the cost of shipping and materials and forecasting the speed at which the products can be moved through the supply chain.

These types of AI tools assist supply chain professionals in choosing the best method of shipping their goods. In a minor way, AI can aid delivery drivers in finding more efficient routes.


As we’ve covered in this article, AI, generative AI, and Machine Learning have transformed the world and will transform businesses in the upcoming years. From sales operations to IT and marketing, incorporating AI into workplaces cuts the time spent doing repetitive tasks, increases employee productivity, and improves customer experience. It also assists in avoiding mistakes and spotting potential issues in a way that is impossible for humans.

It’s no wonder that companies are using it to boost the efficiency of a range of business functions, from logistics to hiring and obtaining employment. We are convinced that those leading the way in AI will gain economic benefits and be the leaders in the market shortly.

We, at CitrusLeaf, uses GitHub Copilot and GPT-3 to speed up NodeJS development, design and content creation while delivering the same quality as always. Honestly, we are grateful for all these tools.

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