AI: Relative intelligence, yet very useful
We talk about Artificial Intelligence (AI), yet machines are still far from achieving what we understand by intelligence. Take the recent example of ChatGPT, an excellent language model that has no common sense and is usa email list therefore not intelligent. Even if AI is not intelligent, that doesn’t prevent it from being useful in a multitude of situations. Today, AI models are used in all sectors: manufacturing, finance, energy, and healthcare, for example.
Once the domain of research labs and large technology companies a few years ago, artificial intelligence is now accessible to any business . The factors that have led to such growth are multiple: decreasing storage costs, increasing computing power, and the ease of use of AI tools. That said, for companies to successfully achieve their data-driven transformation, three complementary areas must be considered:
- use cases,
- talents,
- a common language.
Identify relevant use cases for your business
To identify the most interesting use cases, companies can use a three-step approach:
Step 1 – Identification
One or two brainstorming sessions with stakeholders are a what to expect during the procedure great starting point for listing use case ideas. This involves combining a top-down approach based on needs or desires with a bottom-up approach based on the company’s available data.
Step 2 – Selection
Use cases are roughly placed on a benefit/impact matrix. The goal is to separate them into groups. Two to five use cases are then selected to strike a balance between ideas that are easy to implement immediately and promising but more complex projects.
Step 3 – Definition
The selected use cases are then detailed using a canvas. An example of a canvas is provided below (Figure 1: the Data Initiative Canvas) . The purpose of the canvas is to ask the right questions about the project. It also serves to align all stakeholders on the initiative. Note that the document will evolve over time.
For these three steps, it is necessary to find the right balance in terms of the time to be devoted to them as well as the stakeholders to be involved in order to be able to move forward in a reasonable manner.
Finding the right talent for your AI project
Developing AI use cases in business requires finding the right talent. There are several possible options, such as:
- Specializing in business experts – Indeed, hiring a data scientist is expensive for a small business. Therefore, we can train a business expert to become a data citizen.
- Hiring data scientists – If the company can afford it, this is certainly the best solution. Developing internal taiwan lists skills is an important long-term asset for companies.
- Consulting firms – Outsourcing resources is also possible. An intermediate step is to recruit a junior data scientist and seek advice from a consultant on the strategy to adopt.
Once this choice is made, there is only one important ingredient missing for the use of AI to be implemented on an enterprise scale.