How to Make an AI Model for Enterprise Solutions

Over the past couple of years, Artificial Intelligence (AI) has exploded in popularity and ubiquity. While the concept has been around for centuries, AI has only recently evolved from the realm of science fiction to science fact.

AI has begun to enter every aspect of our lives, with each new iteration promising a revolution in how we produce art, educate ourselves, and run our businesses. Perhaps most noticeable has been the [rise of chatbots], programs capable of retreating and synthesizing vast quantities of information in seconds to answer questions and assist human research. Programs like ChatGPT have opened the door to a whole new way of learning and doing business.

While it is easy to get swept up in the craze of AI and the many excellent opportunities it offers, it is essential to remember that, despite the many promises of this impressive new technology, AI does not represent a magic “fix-all.” Instead, AI represents an incredible new tool that, like any tool, is best employed when the user understands how it functions.

So, if you want to employ enterprise AI for your business, it’s essential to understand artificial intelligence models, how to make them, and what you can expect from them.

What is an AI Model?

Before you design an Artificial Intelligence model, it is crucial to understand exactly what AI is and is not. Modern AI is not a “thinking construct,” meaning it isn’t meant to replicate the sentience and cognitive processes that humans have.

Instead, artificial intelligence models are programs built from algorithms and trained on data sets designed to seek out patterns and make decisions without human intervention. AI models are not catch-all programs that can be employed in any setting or use case. They should be designed with specific tasks in mind and utilized to meet the particular needs of the intended projects.

AI models are only as strong as the algorithms that comprise them and the provided data. For these reasons, a custom AI model must be approached with intention. If you want to improve your business with enterprise AI, you will need an AI model.

How to Create an AI Model

When approaching the creation of your AI model, don’t get bogged down in thoughts of esoteric code and complex algorithms. When the time comes, those challenges can be handled by the proper experts and [custom AI development companies].

By following the 7 steps outlined below, you will be well on your way to producing an AI Model explicitly designed for integration with your enterprise.

1. Identifying Problems and Objectives

Your first step in planning an AI model for your enterprise should be recognizing your objectives for the program. What problems are you looking to solve, or what inefficiencies are you hoping to rectify?

By clearly identifying these things, you set a solid foundation to direct the construction of your AI Model. Enlisting the help of a custom AI development company would be a great way to begin this process if you do not possess the expertise within your enterprise.

2. Collection and Preparation of Data

Data is the lifeblood of your AI, and the quality of the data you feed your AI model will be directly proportionate to the quality of its output. Not only should your dataset be relevant to your AI model’s eventual uses, but it should also be appropriately curated.

Once you have gathered and preprocessed the data, it can be split into training, validation, and testing sets for greater efficiency in the later testing stage.

3. Committing to an Algorithm

Much like data is the lifeblood of your AI model, an algorithm is a structure. Once again, the type of algorithm you choose will be context-dependent on your needs and use cases. Depending on whether you are employing structured or unstructured data, you may want to select an algorithm tailored to one or the other.

Additionally, Machine Learning (ML) can be an essential element of AI models, so it is vital to consider the different ML types at this stage. You may also consider a deep learning algorithm.

4. Training Your AI Model

Once you have selected your algorithm and prepared your data, it is time to start training your AI model. This is when your training data set comes into play.

You will want to feed this into the AI model until it has learned to account for variations in the data. This will require gradual changes to the AI model’s internal parameters and eventually making any necessary changes to hyperparameters.

5. Assessing Your AI Model

Once the training stage has been completed, it is time to use your validation data set assets your new model’s performance. The appropriate metrics for scoring AI models depend on the model type used, but generally, you will want to look at accuracy, precision, recall, and F1 score.

6. Testing and Deployment

Now that you have assessed your AI model and made any necessary adjustments, you will enter the testing stage. You will use your testing dataset to simulate real-world situations and environments in which it is likely to operate.

By this stage, you should be confident with its accuracy, but some minor adjustments may need to be made. Once your AI model has hit all its targets, it is time to deploy.

7. Ongoing Monitoring and Evaluation

As with any software, it is essential to remember that the improvement process is never done. As your AI model operates in the real world, you should continue to monitor its progress and recognize any errors or flaws in its function.

Regular evaluations of its performance should be done, and future updates should be planned to improve the AI model continually. Remember, the more an AI model functions in the real world, the more opportunity it has to improve.

Enterprising AI

Enterprise AI can be an invaluable tool for the efficiency of your business processes and operations, but it is essential to remember that it is a tool like all software. By following the above framework for constructing your AI model, you can ensure you develop a robust tool that is effectively tailored to your precise needs. Once you have a suitable artificial intelligence model at your disposal, your business is sure to benefit.  

Bidhan Baruah

Bidhan is the Co-founder and Chief Operating Officer of Taazaa. He is well versed in outsourcing and off-shoring, and loves building and growing startup teams. A true Apple lover, he loves trying different phones and tablets whenever he gets time.