It is worth emphasising the importance of two technologies: generative AI and decision intelligence. Early adoption of these technologies can provide a significant competitive advantage and simplify the use of AI models in business processes.
Generative AI is a subset of artificial intelligence that focuses on creating new data, whether it be text, images, video, or other formats. It uses machine learning models that are trained on large data sets to then generate new, similar data. These include:
These techniques are used to generate text, images, videos, and music. They improve data quality by pre-learning existing data, and synthesising missing data. You can use them to develop new products, they help generate ideas for products and services. One of the most famous examples of generative AI is DALL-E 2, an image generator that can create photorealistic images from a text description.
Decision Intelligence (DI) is a field of AI that focuses on helping people make more informed decisions. DI uses machine learning algorithms to analyse data, identify patterns and predict future events. It includes:
Effective integration of AI into business operations requires a well-thought-out strategy. Without a strategic approach, implementing AI can be risky. One recommended strategy involves identifying specific areas in the business where AI can deliver tangible benefits while ensuring alignment with overall business objectives. This is where we can be your technology partners to develop and implement a solution that can help you. Our approach in delivering project with significant AI component:
We evaluate current state (point A), the desired state (point B) in measurable, specific terms.
We assess how AI can benefit you and which type of AI would be most suitable to help you achieve your goals.
We examine the risks you may potentially face and how we can minimise them by working together.
We design, develop, and implement the solution, testing not only technical but business impact along the way.
It is worth noting that AI solutions aren't always capable to outperform human experts in terms of expertise and thought process. That's why we believe it is necessary to assess the potential value that AI can add. Critical decisions, especially those with significant consequences, should be vetted by human experts.
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