In the era of digital transformation, artificial intelligence (AI) has become a strategic lever for companies looking to optimize their operations, improve decision-making, and develop new products or services. Yet, many SMEs and mid-sized companies still hesitate to take the plunge, often due to a lack of visibility on the concrete opportunities that AI could bring to their business.
This is where the AI diagnostic comes in: a structured methodology to precisely evaluate the potential of artificial intelligence for your company by identifying the most relevant and high-value use cases.
AI diagnostic is an expert guidance approach aimed at analyzing your company's processes, data, and challenges to identify opportunities for implementing artificial intelligence solutions. Typically conducted over a period of about 10 days, this diagnostic transforms abstract concepts into concrete, actionable projects.
An effective AI diagnostic generally revolves around four distinct phases, each with its specific objectives and methodologies.
Indicative duration: 1 day
The framing phase constitutes the essential starting point of your AI diagnostic. During this initial stage, the expert and the management team meet to:
This phase allows for establishing a detailed mission schedule and identifying the main data sources that will be explored in the subsequent phases.
Indicative duration: 2 to 3 days
This second phase is crucial for developing a deep understanding of the company and its data ecosystem. The main activities include:
The main deliverable of this phase is a complete assessment that provides an accurate portrait of the company's IT/Data maturity and identifies the organization's strengths and weaknesses in terms of data management.
Indicative duration: 4 to 5 days
This is the most substantial phase of the diagnostic, during which the expert will:
At the end of this phase, the company has a structured inventory of applicable use cases and a prioritization matrix allowing for a clear visualization of high-potential opportunities.
Indicative duration: 2 days
The final phase of the AI diagnostic consists of synthesizing all the analyses and formulating actionable recommendations. The main activities are:
This phase concludes with a formal presentation to the management team, presenting the diagnostic's conclusions and paving the way for concrete actions.
A well-conducted AI diagnostic offers numerous advantages for your organization:
To maximize the effectiveness of an AI diagnostic, here are some recommendations:
A complete AI diagnostic typically takes 10 days of guidance. These days are spread over several weeks and break down as follows: 1 day for the framing phase, 2 to 3 days for the assessment, 4 to 5 days for identifying and prioritizing use cases, and 2 days for recommendations and final presentation.
AI diagnostic is particularly suited to SMEs and mid-sized companies looking to explore the potential of artificial intelligence in a methodical way. This approach is suitable for companies of all sizes, but is particularly relevant for those that already have a minimum of exploitable data and are looking to optimize their processes or develop new products/services.
There is no significant difference as these terms are often used together. A good diagnostic examines both the maturity of the company's data (quality, availability, governance) and the opportunities for applying artificial intelligence. These two aspects are inseparable because AI cannot be effectively deployed without a good data strategy.
The AI diagnostic begins with a framing phase where the expert and the management team define the objectives. This is followed by an in-depth assessment that evaluates data/IT maturity and analyzes business processes. The third phase, the most substantial, identifies and prioritizes AI use cases according to their impact and feasibility. The diagnostic concludes with concrete recommendations and a detailed action plan for implementing the priority solutions.
AI diagnostic constitutes a fundamental step for any company wishing to explore the potential of artificial intelligence in a methodical and pragmatic way. Beyond identifying use cases, this approach allows for raising awareness within the organization about data and AI challenges, and for laying the groundwork for a successful digital transformation.
By following a structured methodology in four phases (framing, assessment, identification of use cases, and recommendations), companies can transform AI from an abstract concept into concrete projects generating real added value.
If you are the leader of an SME or mid-sized company and you wish to explore the potential of AI for your organization, don't hesitate to inquire about available guidance programs from artificial intelligence experts.
At Strat37, we conduct AI diagnostics to help companies fully exploit the potential of artificial intelligence. Our team of experts accompanies you at each step of the process, from evaluating your data maturity to concrete implementation of high-value use cases. Would you like to know more about our AI diagnostic services? Contact us for an initial no-obligation discussion!
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