What Is the Hiroshima AI Process for AI?

Launched by the G7 in 2023, the Hiroshima AI Process resulted in an International Code of Conduct for Organizations Developing Advanced AI Systems, built around eleven actions covering risk management across the AI lifecycle, transparency, security, content authentication, governance, and data protection.

In February 2025, the OECD translated these principles into a Reporting Framework — a voluntary, standardized tool enabling organizations to publicly report on how they implement these principles. It is neither a label nor a certification, but a transparency initiative designed to make AI practices comparable across organizations.

For ARKANE, Trustworthy AI Starts with Engineering

ARKANE designs frugal embedded AI for signal processing, antenna systems, and wireless protocols, primarily serving customers in the aerospace and defense sectors.

In these industries, trust cannot simply be declared — it has to be proven. Robustness under real-world operating conditions, risk management across the full product lifecycle, model security, and explainability are engineering requirements, aligned with standards such as DO-178C and the EASA AI Roadmap. Here, explainable AI (XAI) is used as a reliability tool rather than a retrospective justification.

For ARKANE, joining the HAIP reporting initiative means formalizing, at an international standard, a practice that is already central to how the company operates.

A Natural Extension of Our Commitments

This commitment builds naturally on ARKANE’s existing positioning:

• “AI Pioneers” award winner (France 2030 / P2IA) — recognition of ARKANE’s innovation capacity in AI applied to demanding use cases.
• Bpifrance Deep Tech label — a mark of strong technological and scientific depth.
• AI for critical infrastructure resilience — a priority identified by the tech industry in the “Cybersecurity and Critical Infrastructure Resilience” section of the TECH7 recommendations to the G7.

ARKANE also took part in the TECH7 Summit (28 May 2026), the forum bringing together the leading digital-industry associations from the G7 and the EU, which issues annual recommendations to G7 leaders.

Our Practices, in Concrete Terms

Our approach to trustworthy AI translates into concrete, day-to-day practices:

• Lifecycle risk governance: identifying, assessing, and mitigating risks from design through embedded deployment.
• Robustness and reliability: validation under representative operational conditions, consistent with our sectors’ certification requirements.
• Explainability (XAI) used as an engineering lever to strengthen hybrid AI / signal-processing pipelines.
• Frugality: optimized models (compression, quantization) designed to run under tight embedded resource constraints (Size, Weight, and Power — SWaP).
• Data security and governance: internal data-protection and security rules tailored to the sensitivity of our projects.

What Comes Next

This declaration is the first step. The next will be completing our HAIP report, to be published on the OECD platform, mapping our practices against the Code of Conduct’s eleven actions and turning our commitment made in Bercy into demonstrated proof.

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Further reading:

• Press release from the French Directorate General for Enterprises (DGE)
• OECD HAIP Reporting Framework

A strategic issue: securing PNT signals

Positioning, navigation and synchronization (PNT) signals are now essential for the operation of many critical infrastructures: transport, energy, telecommunications, autonomous systems.

However, these signals are exposed to increasing threats:

• Jamming
• Spoofing
• Desynchronization

In an increasingly tense geopolitical and cyber context, the ability to guarantee the integrity, authenticity and continuity of service of PNT signals becomes a challenge for European sovereignty.

 

 

The P2IA project: an embedded AI at the service of cyber-resilience

To meet this challenge, ARKANE is developing P2IA, an embedded artificial intelligence solution capable of:

• Detect attacks in real time
• Identify their nature
• Neutralize their effects
• Maintain service continuity

Our approach is based on frugal and explainable AI, designed to be directly integrated into embedded systems, with strong constraints on performance, latency, and energy consumption.

 

 

A differentiating technological approach

1. AI hybridization / signal processing
ARKANE combines the robustness of classical signal processing methods with the adaptive power of artificial intelligence.

This hybridization allows:

• Better resilience against unknown attacks
• A dynamic adaptability to contested environments
• Increased explainability of algorithmic decisions

 

2. Generative AI attack scenario generation
We integrate generative AI mechanisms to automatically produce complex and realistic attack scenarios.

Objective:
Continuously train, test and reinforce our defense systems against evolving and increasingly sophisticated threats.

 

3. A sovereign and certifiable firmware architecture

From phase 1 of the project, P2IA’s architecture is designed to meet European regulatory requirements:

• Compliance with the AI Act (high-risk AI systems—critical infrastructures)
• Alignment with NIS2 and REC frames
• Taking into account the recommendations of ANSSI

This “compliance by design” approach guarantees a certification path compatible with the requirements of European institutional and industrial actors.

 

A strategic recognition

The selection of ARKANE among the first winners of ‘Pioneers of AI’ is a strong recognition:

• From our vision of a sovereign AI
• Of our commitment to an explainable AI
• From our positioning on the challenges of cyber-resilience of critical infrastructures

 

We thank our institutional partners as well as all of our teams, whose expertise in signal processing, embedded AI and secure architectures makes this ambition possible!