Technology is evolving rapidly. It is crucial for companies to stay informed about the latest developments. Generative AI is by far one of the most widely discussed technological advancements in recent years. However, if you are looking for ways to leverage this trend as a company, it can be challenging to know where to start. In this blog, we discuss specific solutions that can improve your company's efficiency and make a real impact on your current work processes.

What is generative AI and how can it take your company to the next level?

Generative AI is a form of artificial intelligence that can create new content, such as text, images, videos, and even code. It presents enormous opportunities in business processes by automating tasks, improving quality, and driving innovation.

Practical applications of generative AI

There are many ways to apply generative AI can in a business environment. The simplest and most obvious solutions are AI writing tools like ChatGPT and Hyperwrite. These tools can be used for tasks such as generating AI product descriptions for e-commerce or AI job postings. Additionally, we ourselves use Claude 3, which is also highly suitable for such tasks. Check this link for additional tools that are widely used by companies.

The use cases that we frequently encounter at MSTR are explained in the visual below:

Why an AI expert is indispensable for effective AI implementation

Many of our clients, we see that they have talented developers in-house. However, developing AI solutions requires a unique approach that significantly differs from conventional development methods such as front-end development with JavaScript. AI development leans more towards data science and requires specific expertise.

Four crucial elements play a significant role in creating of your AI solution:

1. Large Language Models (LLMs): The rise of generative AI presents challenges, such as effectively communicating with Large Language Models like GPT-4 or GPT-3.5. This interaction, also known as prompt engineering, is a specialized field requires substantial practice and expertise.

2. Data quality: The quality of the data you use isi essential for the reliable results from your AI solution. The integration of both internal and public data sources with techniques like Retrieval Augmented Generation (RAG) significantly enhances the effectiveness of your AI solution.

3. Data security: In the development of AI solutions, priority number 1 is, in many cases, the security of your data. It is important to handle data shared with AI tools with care to protect business and customer information. Custom solutions on platforms like Microsoft Azure offer more control and security, especially for sector-specific applications. 

4. Modular Design: This means designing the solution so that it can be easily adapted to new and smarter models. By building modularly, you ensure that your AI solution is flexible and scalable, allowing you to benefit from the latest developments (such as new LLMs) in the rapidly changing world of AI.

Do you want to know how AI can transform your company? Contact one of our AI experts. We are here to support you in discovering and harnessing the power of AI, tailored to the specific needs of your business.