Our added value: combining artificial intelligence and business expertise
Pierre Guérin, Head of Data Science and AI at Equans Digital FranceOur added value: combining artificial intelligence and business expertise
Pierre Guérin, Head of Data Science and AI at Equans Digital France
There are many players in the AI market. What makes Equans stand out from everybody else?
Whether in industry, buildings, cities and regions or transport, the potential of artificial intelligence is immense. There are many players in this field, some of whom are recognised leaders. Equans' experts are positioned to add value in these areas, thanks to their industry-specific expertise. To date, this has mainly involved AI applied to engineering:
- Conventional" Machine Learning: implementation of supervised or unsupervised algorithms to optimise the consumption or performance of an installation, or to predict certain situations.
- Computer Vision: detection, identification and categorisation (e.g. detecting defects in products manufactured on production lines, optimising the use of public space in cities, augmented remote surveillance, etc.). See also Equans-Digital expertise on Computer Vision
We have significant initial references for this type of project in France, Belgium, the United States, the United Kingdom and the Netherlands in particular, with convincing results.
At Equans, we have a major advantage: the fact that we have developed, often over many years, a detailed knowledge of our sectors of activity, our clients and their facilities. Often, we are already on site, alongside our client, as part of recurring service contracts. This holds particularly true for industry, where integrating AI is not within everyone's grasp and requires in-depth knowledge of facilities and processes. This is our added value: the best experts in algorithmic models cannot achieve good results without this knowledge.
Our strength also lies in the fact that, thanks to our core businesses, we have access to a phenomenal volume of data associated with the facilities we design and/or operate. This makes it much easier to process and integrate this data into the design of algorithmic solutions. By positioning ourselves further upstream, we can proactively offer our clients use cases that incorporate AI.
In practical terms, how do you integrate AI into your projects?
The core of AI is data. The more numerous and relevant they are, the better the accuracy and therefore the performance of the model. The first task is to collect, extract and quality-assign all available relevant data (whether internal to the facility or supplied by an external system). This is a long and decisive stage. The second phase, which is less complex than it might seem, involves developing the algorithmic model: choosing the model best suited to the use case and testing it. The third stage is in situ deployment and integration of the solution into the IT infrastructure. This is a complex phase, in which the Equans teams have the greatest added value. Thanks to their knowledge of the processes involved, and often even of the production facilities concerned, they are able to implement the solution across an extended value chain and at the interface with the site's other information systems. Finally comes the phase of operating the solution, sometimes combined with a service offering to ensure that the algorithmic system is monitored over time, and if necessary retrained manually or automatically.
In your opinion, should we be wary of AI?
Personally, I see AI-based solutions as powerful decision-support tools. In the end, the decision rests with the human being, who alone is capable of assessing the relevance of the algorithmic results obtained thanks to his or her business expertise. It is the combination of AI and human expertise that makes this technology so powerful.
