Generative AI & Machine Learning

Artificial Intelligence (AI) is more than robots or chat tools; it’s a powerful driver of business value. With the right AI strategy, organizations can automate processes, boost operational efficiency, enhance customer experiences, and gain a measurable competitive advantage.

OEE dashboard that uses Generative AI to optimize for instance output

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Increase operational efficiency

AI can automate long and repetitive tasks. This not only helps save time and money, but it also increases employee productivity and job satisfaction. AI relieves employees from repetitive tasks and provides customers with answers faster.

Improve customer experience

Through AI, businesses can provide customers with faster support, for example, using chatbots. AI can also analyze customer behavior and predict consumer needs in real time. This allows businesses to alter their tools and services.

Enhance security & fraud detection

Based on data, AI can identify risks and understand them through Machine Learning. It can then help you choose safe passwords and even verify credit card-holders by detecting unusual devices and transactions, helping to prevent credit card fraud.

Enable data-driven decision-making

AI provides real-time insights, such as trends and correlations, by analyzing vast amounts of data at high speeds. This supports faster, more efficient decision-making. Additionally, AI can help identify and analyze risk factors and provide mitigation strategies.

“LCAPs also provide opportunities for organizations to stay up to date with the most recent practices – for example, platform engineering and technology innovation like AI-assisted application development and, specifically, the recent trend of generative AI.”

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Gartner Research 2023

How can you implement AI into your business?

There are many subtypes of Generative AI that have proven to be useful in various use cases. Here are some examples of sub-types and their uses.

Generative AI & Machine Learning

Machine Learning

Allows AI to be trained based on data, which allows it to learn to identify patterns or groupings, make predictions & classifications, or achieve other goals by interacting with its environment. This can be useful in almost any sector.

  • Supervised Learning: Training a model on labeled data. This can be used for predictions and classifications.
  • Unsupervised Learning: Uses unlabeled data to identify patterns or groupings.
  • Reinforcement Learning: Learns by interacting with its environment to achieve a goal.
Generative AI & natural language processing

Natural Language Processing

Builds on AI’s capabilities to analyze text data for insights, automate conversational agents, and translate text between languages. This can, for example, be very useful in the customer service sector.

  • Text Analytics: Analyzing text data for insights. Used in sentiment analysis, customer feedback analysis, etc.
  • Chatbots: Automated conversational agents. Improve customer service and reduce response time.
  • Machine Translation: Translating text between languages. Useful for international business communications.
generative AI & computer vision

Computer Vision

Trains AI to identify objects, features, or people both in images and videos, as well as for facial recognition. This can, for example, be very useful in the security, inventory management, and content moderation sectors.

  • Image Recognition: Identifying objects, features, or people in images. Useful in quality inspection, inventory management, and security.
  • Facial Recognition: Identifying or verifying individuals. Enhances security and personalized customer experiences.
  • Video Analysis: Analyzing video content for specific events. Used in surveillance, sports analysis, and content moderation.
AI-driven analytics & Generative AI

AI-Driven Analytics

Based on the analyzed data, AI can forecast future trends and recommend actions based on these trends. This can, for example, be very useful in the supply chain operations, logistics, and sales sectors.

  • Predictive Analytics: Forecasting future trends based on historical data. Applied in sales forecasting, risk management, and supply chain optimization.
  • Prescriptive Analytics: Recommending actions based on predictions. Enhances decision-making in logistics, marketing strategies, and operations.

Build Smarter Applications with our Generative AI Masterclass

Already exploring AI but want your team to build smarter apps with GenAI? Our Generative AI Masterclass gets them hands-on fast.

In just two days, they’ll learn how to apply prompt engineering, function calling, retrieval-augmented generation, advanced metadata filtering, and build specialized AI agents, plus everything needed to integrate generative AI into real Mendix projects immediately.

Thinking about a workshop or training session? We’ll help you get started

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