In a rapidly changing economic landscape, companies are constantly looking to unlock new sources of value. If you’re considering an exit, raising capital or simply consolidating your position, it’s crucial to recognise the intrinsic value of your artificial intelligence processes.
But that’s not all: the rigorous documentation of these processes could be your company’s most undervalued strategic asset.
AI transcends the status of a simple tool. It represents a transformational paradigm that, when integrated strategically, can metamorphose operational efficiency, drive innovation and create sustainable competitive advantage.
However, to unleash its full potential, a scientific and systematic approach is imperative.
The quantifiable value of documented AI:
Documentation is not just an administrative formality; it is the key to quantifying and articulating the value that AI brings to your business. It allows you to turn hunches into concrete evidence, strengthening your company’s credibility and attractiveness to potential investors and acquirers.
Beyond tools, a process-focused approach:
The emphasis should not be placed solely on the AI tools used (machine learning frameworks, cloud platforms, etc.), but rather on the specific processes that they enable to be optimised. A detailed description of these processes, their inputs and outputs, as well as the algorithms and models used, is essential.
Data, the lifeblood of AI:
Documentation must include precise information on the datasets used to train the AI models, the methods used to clean and transform the data, and the measures taken to guarantee the quality and relevance of the data. Data traceability is a crucial element in ensuring the reproducibility and reliability of results.
Key metrics and impact analysis:
The effectiveness of AI must be rigorously assessed using relevant key metrics (KPIs), such as :
- Cost reduction: What are the observed levels of reduction in operational expenditure as a result of automation?
- Increased revenues: What level of growth in sales and market share has been observed as a result of improved products and services?
- Improved efficiency: What impact has automation had on reducing processing times and optimising workflows? Which workflows have been affected?
- Customer satisfaction: How have you managed to increase customer loyalty thanks to an improved customer experience? To what extent?
- Model performance metrics (accuracy, recall, F1-score, AUC). An in-depth analysis of these metrics, with comparisons before and after AI implementation, will enable you to convincingly demonstrate the positive impact of AI on your business.
System Architecture and Interoperability:
Describe the architecture of your AI systems, the integration with existing systems and the APIs used. Document security and compliance considerations (RGPD, etc.). This documentation will be crucial for audits and due diligence.
The Asymmetric Advantage of SMEs and Startups:
Large companies, despite their considerable resources, are often faced with the challenges of organisational inertia and data silos. SMEs and startups, on the other hand, can leverage their agility and flexibility to rapidly adopt AI and create innovative solutions. This agility, combined with rigorous documentation, can create a significant asymmetric advantage.
Concrete example:
Imagine a lead scoring model powered by machine learning. The documentation doesn’t just state that you’re using a logistic regression algorithm.
It should include:
- The features used to train the model.
- The cross-validation methodology used to evaluate the model’s performance.
- The probability thresholds used to classify prospects.
- The impact of the model on lead conversion rates.
- The procedures for re-training the model to maintain its performance over time.
This exhaustive documentation will transform a simple tool into a strategic asset capable of generating significant value.
These are the structuring questions that I believe are important to ask:
- How does my company structure the documentation of its AI initiatives?
- What metrics are we using to assess the impact of AI?
- What are the challenges we face in implementing rigorous documentation of our AI processes?
In a world where AI is becoming an essential component of competitiveness, rigorous documentation of your AI processes is not only recommended, but imperative.
Don’t think of it as a mere administrative task, but as a strategic investment that can transform your company into an industry leader and maximise its long-term value.