Tirer parti du modèle BOT pour renforcer les capacités d'un centre d'excellence en IA
AI is significantly influencing markets and steadily reshaping many industries, making it essential for companies to put in extra effort to remain competitive. With large investments from tech giants and institutions, it is becoming crucial for organisations to establish an AI centre of excellence (CoE), which can facilitate the full potential of AI and increase a firm’s efficiency and innovation.
C'est pourquoi cet article aborde les défis que vous pouvez rencontrer lors de la mise en place d'une unité d'IA dédiée. Nous examinons également comment notre modèle BOT peut simplifier ce processus, en apportant une expertise dès le premier jour et en vous aidant à constituer, exploiter et transférer une équipe d'IA qualifiée et mature au sein de votre organisation.
L'IA dans le paysage commercial
AI is now a permanent part of business. Many industry leaders see it as a vital investment that should be started as soon as possible. As they want to stay competitive and up to date with the market, they must be ready to allocate more financial resources to AI initiatives. Especially since big tech organisations and global institutions are already spending extensively. Only this year, the four largest tech corporations (Microsoft, Alphabet, Amazon, and Meta) plan to increase their combined expenditure to 320 milliards de dollars et se concentrent sur la construction de centres de données et le développement d'infrastructures d'IA qui accéléreront leurs capacités de recherche sur les LLM. Un autre financement majeur dans le développement de l'IA est également prévu par le Union européenne, qui consacre 200 milliards d'euros à cette cause.

Given how much the field can grow with such large investments, for many companies keeping up with the market and competition may require a dedicated AI team or an entire development centre. Importantly, awareness amongst enterprises of the importance of investing in AI is high. In a enquête Deloitte d'il y a deux ans, 94 % des dirigeants d'entreprise ont admis que l'IA est essentielle à leur stratégie de réussite.
De plus, le rapport le plus récent shows that 78% of companies plan to increase their overall AI spending in the next fiscal year. However, this does not come as a surprise, as 74% of respondents say their most advanced Gen AI initiative is already meeting or exceeding their ROI expectations.

Investir dans un centre d'excellence IA dédié
Knowing how important AI is to the markets and how it can impact your firm, establishing a dedicated AI CoE becomes even more pressing. As the popularity of CoE use cases for deploying cloud infrastructure, BI solutions and new accounting or logistic tools proves, this approach can bring many benefits. From cultivating an environment for testing new ideas and processes to setting and implementing standards throughout the company – CoE helps embrace changes and create a culture that encourages team members of all disciplines and seniority to share ideas and push innovation even further.
In the case of AI, a specialised unit enables the efficient coordination and management of all AI development efforts within an organisation. It covers its adoption and optimisation, and fosters collaboration between AI experts and professionals with business and domain knowledge. Centralising such activities in a company ensures that AI projects are not isolated experiments but integrated, scalable solutions that deliver real business value.
The AI team consists of technology experts responsible for advising, preparing strategies, and guiding and overseeing AI projects in the firm. This means that such a unit identifies potential AI use cases, develops the necessary models and systems, enables the building and development of technology infrastructure, and works closely with both internal leaders and external vendors.

Défis et considérations pour la mise en place d'un CoE en IA
While establishing a dedicated AI unit offers significant benefits and can be seen as a strategic move that drives company innovation and competitiveness, it also can present a few challenges. From assessing AI readiness to financial considerations and talent acquisition – proceeding with the AI centre adoption process requires careful planning. Some key factors worth considering are:
Niveau de maturité AI dans l'organisation
Avant de lancer un centre d'excellence en IA, vous devez évaluer la maturité actuelle de votre entreprise en matière d'IA. Dispose-t-elle d'une expertise interne, d'une infrastructure et d'une gouvernance des données en place ? Si ce n'est pas le cas, vous devrez peut-être commencer par des projets pilotes et des partenariats externes.
Through collaboration with a well-established software provider, you can get access to proven experts and methods of operation that facilitate the entire AI CoE development process. For example, Spyrosoft’s BOT model can enable your company to fast-track the work on AI centre creation by leveraging our knowledge, experience, and best practices. It also involves helping with assessing your AI readiness, defining a clear roadmap, and building the right technology infrastructure.
Découvrez comment les partenariats externes peuvent aider votre centre d'IA à prospérer >>
Constituer une équipe pluridisciplinaire
AI success depends on a diverse team that includes data scientists, engineers, business analysts, and domain experts. Finding, recruiting, and retaining top AI talent can be challenging due to high market demand. So, you may need to explore a mix of recruitment, partnerships, and upskilling existing employees to bridge the skills gap
With the BOT model, you gain immediate access to skilled, multidisciplinary AI specialists who bring their expertise and work closely with your internal teams. More so, the partner provides recruiting and back-office support that handles the hiring and onboarding processes, ensuring a well-trained AI team that is tailored to your needs.
Coûts d'investissement initiaux élevés
Setting up an AI centre of excellence requires significant financing for infrastructure, resources, and skilled personnel. While the long-term benefits can be substantial, companies should plan for cautious but steady investments and align all AI initiatives with the firm’s priorities. Establishing such a centre within BOT can mitigate initial risks and reduce upfront costs, as the partner is responsible for building the team and preparing the infrastructure using its own resources. This allows businesses to focus on scaling initiatives effectively while maintaining cost efficiency and getting great value from artificial intelligence.
Formation à l'IA des parties prenantes et des employés
AI adoption isn’t just a technological challenge; oftentimes, it’s also a cultural shift in the organisation. Employees, decision-makers, and stakeholders must understand AI’s potential, limitations, and ethical considerations. Therefore, a strong internal education program is often needed. It can foster an understanding of AI topics, boost competence development, improve adoption rates, and ensure alignment with business goals.
Dans le cadre de la collaboration BOT, nous pouvons vous fournir des programmes de formation en IA, des ateliers pratiques et un mentorat continu d'experts pour vous aider à développer vos connaissances en IA en interne et à promouvoir une culture axée sur l'innovation.
Prendre en compte tous ces facteurs dès le départ et tirer parti du modèle BOT peut vous aider à mieux faire face aux défis liés à la création d'un centre d'excellence, libérant ainsi tout le potentiel de l'IA tout en minimisant les risques et les coûts.
Découvrez comment le modèle BOT peut bénéficier à votre centre d'IA
En savoir plusModèle BOT pour la mise en place d'un centre d'excellence en IA
As mentioned earlier, the Build-Operate-Transfer (BOT) model can be a very effective strategy for setting up an AI CoE, especially for organisations new to AI or lacking internal expertise. The BOT model allows companies to leverage external expertise and resources in the critical early stages of planning and building a dedicated AI unit, thus ensuring that it has a solid foundation.
In line with the model premise, the technology partner is initially in charge of building and introducing the team, and then the operational aspect and scaling. Over time, as the team’s capabilities and competencies are developed and reinforced, full control and oversight of centre of excellence operations are transferred to the client organisation.
Voici un aperçu de ce que chaque phase de BOT peut couvrir en matière de mise en place d'un centre d'excellence en IA :

Phase de construction
- Formation de l'équipe initiale: Facilitating the recruitment and onboarding of experienced, multidisciplinary AI professionals and working on training and integrating promising internal candidates into a CoE team. The focus is on building a dedicated team with data scientists, engineers, project managers, business analysts, and experts with domain knowledge.
- Mise en place de l'infrastructure: Tirer parti des connaissances technologiques et des ressources du partenaire pour établir l'infrastructure technologique requise, y compris les solutions de stockage de données, les plateformes nécessaires et les outils de développement d'IA.
- Projets pilotes: Identification des domaines d'activité clés où l'IA peut générer des gains significatifs. Élaboration et déploiement de stratégies et de projets visant à démontrer la valeur de l'IA, à affiner les processus et à renforcer la compréhension et la confiance des parties prenantes.
phase d'exploitation
- Partage des connaissances: Le partenaire prend l'initiative d'exploiter les activités du centre d'IA et garantit un partage continu des connaissances et des compétences par le biais de formations pratiques, d'ateliers et de mentorat.
- Optimisation des processus: Introduire et développer des flux de travail standardisés, des bonnes pratiques et une documentation pour garantir la cohérence, la haute qualité et l'efficacité des projets d'IA.
- Mise à l'échelleAssumer la responsabilité d'élargir continuellement les ressources et les équipes afin de garantir la croissance continue des initiatives d'IA, y compris à travers les départements et les fonctions métier.
- Engagement des parties prenantesMaintenir une communication régulière avec les dirigeants, les décideurs et les parties prenantes afin d'aligner les initiatives d'IA sur les objectifs stratégiques et d'apporter un soutien continu.
Phase de transfert
- Transfert et passation: Once the team has gained sufficient knowledge, competence, and trust, the partner hands over full control of the AI centre of excellence to the client organisation. This includes IP, all resources, the entire infrastructure, management of ongoing projects, and governance of the team’s administrative aspects.
- Planification d'une croissance stable: Créer et transférer une stratégie à long terme pour le CoE, incluant des programmes de formation continue, des initiatives de développement des talents et des investissements dans les nouvelles technologies et les solutions d'IA afin de garantir une base solide pour le développement futur.
Collaborez avec nous pour mettre en place un centre d'excellence en IA en BOT
Setting up an AI centre of excellence using the BOT model provides a reliable, structured, and scalable approach to integrating AI into an organisation’s strategic business activities. By centralising expertise, enhancing resources, and fostering a culture of innovation, an AI CoE can significantly improve your company’s productivity and ability to outpace the competition. The BOT model offers distinct advantages, such as risk mitigation, faster deployment, and stable knowledge transfer, making it a great option for firms looking to build robust AI capabilities.
Si tout cela semble parfaitement correspondre aux besoins de votre entreprise, n'hésitez pas à nous contacter via le formulaire ci-dessous. Nos experts répondront volontiers à toutes vos questions et élaboreront le meilleur chemin versaugmentez votre potentiel en IA.
FAQ
An AI centre of excellence is a dedicated team that supports the organisation in developing, governing, and scaling AI initiatives. It brings structure, shared standards, and technical expertise to projects that might otherwise be isolated or inconsistent. This helps teams apply AI responsibly and with clearer direction.
The BOT model allows organisations to launch or strengthen an AI centre of excellence without building everything internally from day one. An external partner helps set it up, runs it for a defined period, and later transfers the ownership back when the team is ready. This reduces early-stage risk and accelerates capability building.
Many organisations struggle with talent shortages, slow onboarding, unclear governance, or fragmented AI efforts. The BOT model provides temporary structure and expertise while internal processes mature. It helps teams avoid common mistakes and reach operational stability sooner.
Non. Le modèle est conçu pour accroître l'autonomie. Au moment où l'étape de transfert arrive, les équipes internes ont acquis les connaissances, la documentation et les pratiques nécessaires pour gérer le centre d'excellence en IA en toute confiance.
Timelines vary based on project size, data readiness, and organisational maturity. The “Build” phase usually includes defining the strategy, governance, and technical environment. “Operate” focuses on delivery, upskilling, and stabilising processes. “Transfer” happens only when the organisation is prepared to maintain operations without support.
Oui. Ce modèle peut servir à développer un centre d'excellence en IA existant, à introduire de nouvelles compétences ou à normaliser des pratiques qui se sont développées de manière informelle. Il s'adapte bien aux organisations qui ont besoin d'être orientées plutôt que de tout reconstruire.
Depending on the organisation’s needs, an AI centre of excellence may involve data scientists, ML engineers, software developers, domain specialists, and governance leads. Clear processes for ethics, security, and model monitoring are also essential for sustainable growth.
Partnerships play an important role, especially in the early stages. According to Spyrosoft, organisations benefit from working with a team that has experience in operationalising AI practices and supporting the full lifecycle of an AI centre of excellence. This helps create a stable foundation before responsibilities shift fully to the internal team.
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