The most commonly used AI tools by successful companies

Historically, systems had always been deterministic: machines executed commands under human direction. The true disruptive change is that now machines can also reason. AI has become a 'new employee' capable of understanding business processes, learning from them, reasoning, and then executing. However, we are still in the early stages; AI still requires a considerable amount of resources, computing power, and data to operate effectively and be fully trained, which poses the main challenge.

 

Nevertheless, many companies have already realized that incorporating AI into their processes is key to current and future success, both for back office and front office processes, and, most importantly, for interaction with their customers. That's why today we're listing some of the most commonly adopted AI tools among companies. Among the most prominent ones, we find:

• Chat environments: ChatGPT leads the sector, followed by Claude and Google Gemini. They provide intuitive user interfaces for simple chat interactions.

• Image generation: Tools like Leonardo, Midjourney, Dall-e, and Canva are revolutionizing the creation of visual content.

• Customized chatbots: These AI bots are trained with specific company data to address questions or issues that arise among users. They can, for example, function as a call center employee and provide responses to customers.
  
  

• Interaction tools: Microsoft Copilot, for example, can automatically send emails at scheduled times, extract insights, or take notes and meeting summaries. Additionally, they assist in generating documents such as presentations, spreadsheets, etc.

Why is it key to use AI to achieve success?  

Let's consider a practical example. Currently, many dashboards and reports are created for executives or middle management to track key performance indicators. Sometimes these panels become so complex, convoluted, and outdated that they do not facilitate management decisions but rather complicate them even further.

Current technology would allow, for instance, to provide AI through a conversational chat interface to a director. This way, the user could ask questions about sales progress, request identification of issues, of what type, and thus, based on the response, take real-time actions. Goodbye to the increasingly unintelligible complex dashboards.

And what do we do with the transfer of confidential data to AI tools?

Skepticism about handling confidential data in AI is a legitimate concern, akin to the doubts that arose in the early days of cloud computing. While privacy issues exist, current payment models ensure that data is not misused.

However, it's always possible to opt for having your own open-source deep learning language model (LLM), like Meta's LLAMA 3, in your infrastructure, ensuring complete privacy as all processing is done internally.

Real success case

From Serban Group, we recently assisted a major logistics company in Mexico, applying artificial intelligence for goods classification with advanced models like GPT-4 Turbo and cloud solutions to optimize the classification process and handle a higher volume of transactions. This collaboration resulted in improved accuracy and a 50% increase in processing capacity during peak demand, demonstrating the effectiveness of artificial intelligence in enhancing operational efficiency and regulatory compliance.

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SGX Services is our specialized service in everything related to Artificial Intelligence, Process Automation, and RPA. Contact us, we almost certainly have the solution.

With these tools and strategies, AI not only simplifies complex processes but also promotes a digital transformation that is essential for staying competitive in today's market.