In an industrial landscape constantly striving for competitiveness, artificial intelligence (AI) is proving to be a major catalyst for transformation.

At Yxir, we are convinced that AI plays an essential role in helping companies adapt to the constraints of their industrial sector, enabling them to innovate, adapt and optimise their processes in an environment in perpetual search of performance.

It is for this reason that we decided to conduct an in-depth study, to explore companies' strategies for integrating innovation within their organisation and the way in which AI is being used to accelerate their digital transformation.

The study, conducted between October 2023 and January 2024, involved in-depth interviews with 17 companies in the industrial sector.

Integrating innovation into corporate strategy

Companies are adopting various approaches to integrate innovation into their strategy, recognising its crucial importance for remaining competitive and driving long-term growth.

Here is a brief overview:

The integration of artificial intelligence

AI is seen as a means rather than an end in itself, and many companies are looking to exploit its potential to improve their processes and products.

For example, some companies are investing in start-ups specialising in AI and integrating their solutions into their own range. Around 6 out of 10 start-ups in their portfolio position themselves in the field of AI.

AI can also be used to improve companies' internal processes. For example, to automate repetitive tasks and free up time for employees to focus on higher value-added tasks.

AI is also used to analyse large amounts of data and provide valuable insights for strategic decision-making.

Creation of dedicated innovation departments

Many companies are creating specific departments responsible for promoting and developing innovation within the organisation.

These departments are often composed of innovation experts, researchers and developers responsible for exploring new ideas, developing prototypes and coordinating the implementation of innovative projects across the company.

Collaboration with start-ups

Companies are increasingly looking to collaborate with start-ups to benefit from their expertise and innovative ideas.

These collaborations can take various forms, including strategic partnerships, investments or even acquisitions.

This is how companies can gain access to new technologies, innovative business models and fresh perspectives that stimulate innovation within the organisation.

Encouragement of creativity and intrapreneurship

Some companies actively encourage their employees to be creative and propose innovative ideas.

They set up intrapreneurship programmes that allow employees to develop their own projects and implement them within the company.

This approach fosters internal innovation, strengthens employee engagement and stimulates a culture of innovation within the organisation.

Technological intelligence and market monitoring

Companies carry out constant technological intelligence to identify new trends and emerging innovations in their sector of activity.

They also monitor market developments, changes in consumer behaviour and emerging opportunities, allowing them to adapt quickly to market changes and stay in line with customer needs and expectations.

Investment in research and development (R&D)

Companies dedicate significant resources to research and development of new technologies, new products and new services.

They invest in research laboratories, engineering teams and innovation centres to explore new ideas, develop prototypes and test new concepts.

These investments in R&D enable companies to remain at the forefront of innovation and to offer differentiated solutions to their customers.

Analysis of AI adoption in industry: challenges, opportunities and needs

To further explore the adoption of AI in companies, let's examine some aspects of this study. Here are the main findings that highlight points to consider and needs for successful integration of these tools:

Data preparation

The participants interviewed unanimously recognise the need for prior work on their data before being able to train a generative machine learning model (LLM).

However, they often face challenges in terms of data quality and availability.

Re-training AI models

While many companies see the potential of generative AI tools, they are cautious about the process of re-training models.

Questions persist about the size and quality of the data required, as well as the alignment between the start-up's technology and the manufacturer's business knowledge.

Need for support

Companies express interest in generative AI tools but recognise the need for support to use them effectively. They are looking for partners capable of guiding them through the implementation and use of these technologies.

Common use cases

The most common use cases of AI in the industrial sector concern predictive analysis (maintenance, sales forecasting, etc.) and energy performance diagnosis and optimisation.

Obstacles and opportunities

Companies mention several obstacles to the adoption of AI, particularly the financial and time investment required to re-train an LLM, as well as the difficulty of processing natural language and text analysis. However, they also see opportunities in developing specific solutions, notably in the areas of energy performance and maintenance.

AI & Industry: what we believe at Yxir

We believe that AI is not only a revolutionary technology, but also a powerful lever of growth and competitiveness for companies.

Based on this conviction, we continuously strive to anticipate emerging market trends, understand our customers' changing needs and develop an innovative AI solution that responds to these challenges.

At Yxir, we are committed to continuous research to improve our AI solution. We experiment with different tools and approaches to obtain the best possible answers to the complex challenges faced by our clients.

Furthermore, we are always listening to our users and understanding their needs. That is why we regularly conduct user tests and interviews to ensure that our solution is well suited to market requirements.

We support our clients at every stage of their implementation journey. From design to execution, we work in collaboration with our clients to ensure the success of our AI solution in their specific environment.