When deploying a new system in an industrial SME, the question is no longer “Do we need AI?” but “What type of AI, for which role, with what local data?”. The tech trends of 2024 are not just a list of keywords. They translate into concrete choices regarding infrastructure, digital sovereignty, and tooling, with direct consequences on budgets and internal skills.
Autonomous AI agents: what it changes on the ground for businesses
The major shift of 2024 does not concern chatbots. It focuses on AI agents capable of performing multiple tasks without supervision. We are talking about systems that retrieve data, cross-reference it, trigger an action, and then report the result.
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In practice, this results in an agent that monitors a stock of spare parts, detects a critical threshold, places an order with a supplier, and updates the dashboard. All of this happens without an operator intervening between each step.
The friction point remains reliability. These agents are connected to language models that can hallucinate a product reference or misinterpret a threshold. Integration into existing business systems (ERP, CRM) requires an adaptation effort that many underestimate. Feedback on this point varies depending on the digital maturity of the company.
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To keep track of these developments throughout the year, there is a regular flow of technical analyses on lebloginfo.fr, which covers both tools and field experience feedback.
Deep tech and industrial AI: beyond consumer generative AI
Trend lists for 2024 talk a lot about generative AI applied to text or images. One segment that absorbs an increasing share of investments is deep tech with high R&D intensity.
Specifically, we are talking about molecule discovery assisted by generative models, optimization of industrial processes through simulation, and new materials designed by machine learning. These are not gadgets. They are building blocks that modify the value chain in sectors like chemistry, pharmaceuticals, or energy.
What distinguishes deep tech from “classic” AI
- Development cycles are long, often several years before a marketable product, compared to a few months for a SaaS application based on a language model
- The data needs are specific: experimental data, results from physical simulations, proprietary datasets that generalist models do not possess
- Funding increasingly comes from specialized cleantech and deep tech funds, with a sustainability axis that investors demand from the initial proposal
For an industrial company looking to innovate, the question is not whether to choose between deep tech and generative AI. It is about which models to feed with its own business data to gain a concrete advantage.
Digital sovereignty and semiconductors: the geopolitical constraint affecting tech choices
We cannot talk about technological trends for 2024 without addressing the geopolitical dimension. Industrial policies around semiconductors have accelerated in Europe, the United States, and China. Each bloc wants to secure its chip production capacity and computing infrastructure.
For a French company, this translates into very operational questions:
- Where are our data hosted? A European sovereign cloud often costs more than an American hyperscaler, but regulatory compliance is becoming a non-negotiable selection criterion for certain sectors
- Which hardware suppliers to prioritize when delivery times for components depend on trade tensions between major powers?
- How to anticipate export restrictions on certain technologies (high-performance chips, design tools) that could block a project midway?
Digital sovereignty is no longer an abstract political concept. It dictates concrete budgetary trade-offs regarding the choice of tools, hosts, and technology partners.
Cybersecurity tools and cyber resilience: protecting systems before modernizing them
We regularly see companies investing in new digital tools without having consolidated their security foundation. In 2024, cyber resilience is no longer a topic reserved for the IT departments of large groups.
SMEs and mid-sized enterprises are targeted by increasingly automated attacks. Ransomware exploits vulnerabilities in aging systems, sometimes hastily connected during poorly framed digital transformation projects.
Three areas to check before any modernization project
The first is network segmentation. An industrial system connected to the same network as email is an open door. The second concerns access management: each user account must correspond to a defined scope of rights, not to a default administrator access. The third concerns backups. A daily backup that has never been tested for restoration is worthless.
These checks do not require a massive budget. They require method and time, two resources that under-resourced technical teams do not always have.
The year 2024 will mark a turning point in how companies approach technology. Less fascination with spectacular announcements, more attention to real constraints of integration, security, and sovereignty. The organizations that will stand out are those that start from their ground problems, not from a checklist of trends.