Piloting AI in business: a 5-step roadmap
From spontaneous adoption to deliberate strategy
According to an OpenAI study published in September 2025, 92% of Fortune 500 companies have employees using ChatGPT or Microsoft Copilot. But there's a huge gap between individual experimentation and structured corporate strategy. To turn generative AI into a sustainable competitive advantage, organizations need to move beyond opportunism and build a robust governance framework.
The challenge for SMEs and institutions: Most medium-sized organizations do not have the internal resources to structure a comprehensive AI strategy - recruitment of a Chief AI Officer, ongoing training, technological and regulatory watch, management of complex projects. The pace of change in AI (new models every 3-6 months, regulations under construction) makes in-house management costly and risky.
The Darest Informatic approach: rather than bringing these skills in-house full-time, many organizations choose to rely on an outsourced AI strategic partner - a dedicated team of experts who become your "Mr. AI" or "Mrs. AI". This model offers several advantages:
- Continuously updated expertise: technology watch, ongoing training, multi-sector feedback
- Budgetary flexibility: you pay for what you actually need, without the fixed costs of an in-house team.
- Objectivity: external viewpoint, independent of internal political games
- Efficiency: rapid deployment based on proven methodologies
- Guaranteed compliance: native integration of RGPD, AI Act, Swiss LPD requirements.
Here's a proven five-step methodology - applicable to the financial, SME and institutional sectors - that Darest Informatic deploys with its customers.
Establish clear governance
Objective:
Define who decides, who steers, who controls.
Concrete actions :
- Appoint an AI manager (Chief AI Officer or equivalent) with an executive mandate and dedicated budget. For SMEs, Darest can provide this role on an outsourced basis: your full-time AI manager.
- Create a cross-functional AI governance committee (IT, legal, compliance, business, HR) to evaluate use cases and risks. Darest facilitates and leads these committees, providing technical and regulatory expertise.
- Draw up a charter for the use of AI: what is authorized, prohibited and subject to validation. Publish this charter internally and make it accessible to all employees. Darest provides charter templates adapted to your sector and regulatory context (finance, SMEs, public institutions).
- Map risks: data security, algorithmic biases, legal liability, regulatory compliance (RGPD, AI Act, LPD). Darest carries out AI risk audits and produces compliant impact analyses (AIAD/EIPD).
Financial sector example:
A Swiss bank has set up an "AI Steering Committee" comprising the CISO, the DPO (Data Protection Officer), the Operations Director and a compliance lawyer. This committee validates each new use case and assesses emerging risks on a quarterly basis. Darest acts as technical expert, presenting technologies, analyzing risks and recommending secure architectures.
Train teams (all levels)
Objective:
Develop the organization's AI literacy.
Concrete actions :
- Basic training for all (2h): what is an LLM, how does ChatGPT/Copilot work, what are its limits (hallucinations, bias), good security practices (never enter sensitive data). Darest deploys interactive training tailored to your business vocabulary.
- Advanced training for power users (1 day): writing effective prompts, using plugins, automating tasks, business use cases. Darest accompanies your teams on your real tools (ChatGPT Enterprise or Microsoft Copilot), with exercises on your data.
- Legal and ethical training for decision-makers (half-day): RGPD, AI Act, legal liability, incident management. Darest co-hosts with your in-house lawyers or legal partners.
- Set up a feedback system: create a dedicated Slack/Teams channel where employees share their use cases, successes and failures. Darest runs an AI community of practice, facilitating exchanges between users.
Financial sector example:
An asset manager trains his analysts to use ChatGPT Enterprise or Microsoft Copilot to automate the synthesis of financial reports, with safeguards: any analysis produced by AI must be validated by a human before distribution to the client. Darest designed the training, wrote the standard prompts and established the validation protocol.
Identify measurable use cases
Objective:
Focus on high-impact, easy-to-control applications.
Concrete actions :
- Mapping time-consuming processes: where do your teams spend their time? (writing, synthesis, translation, code, reporting, customer support). Darest conducts process mapping workshops with your business teams.
- Select 3 to 5 pilot use cases with clear criteria:
- Measurable business impact (time savings, cost reductions, quality improvements)
- Technical feasibility (can ChatGPT/Copilot really do this?)
- Acceptable risk (no ultra-sensitive data, human validation possible) Darest co-constructs a prioritization matrix with you and validates technical feasibility.
- Define KPIs: time saved per task, cost avoided, user satisfaction, error rate. Darest draws up dashboards and measurement protocols.
Examples from the financial sector :
- Audit & Compliance: automate the synthesis of regulatory documents (10h → 2h per file). Darest has deployed this use case with 3 customers in the sector.
- Wealth management: generation of first drafts of customized customer reports (3h → 30 min per report). Darest configures Copilot to access customer data in SharePoint and generates reports in line with your editorial guidelines.
- Credit risk: automated analysis of financial documents (balance sheets, tax returns) to pre-qualify a file. Darest integrates ChatGPT Enterprise via API into your existing CRM.
Counter-example (to be avoided):
Use ChatGPT to make credit decisions without human validation → prohibited by the AI Act (automated decision in sensitive area). Darest ensures that all use cases comply with regulatory requirements.
Manage with rigorous KPIs
Objective:
Measure real impact, adjust on an ongoing basis.
Concrete actions :
- Set up an AI dashboard :
- Adoption: % of employees using ChatGPT/Copilot, frequency of use.
- Performance: time saved per use case, costs avoided, errors detected.
- Compliance: number of security incidents, successful audits.
- Satisfaction: quarterly user survey. Darest configures Power BI dashboards connected to your tools (Microsoft 365, ChatGPT Enterprise) to track these metrics in real time.
- Organize quarterly reviews with the Governance Committee: What's working? What needs to be stopped? What new use cases should be tested? Darest leads these reviews and presents sector benchmarks.
- Compare with industry benchmarks: where do your competitors stand? (92% of the Fortune 500 use ChatGPT or Copilot, but at what level of maturity?) Darest shares anonymized feedback from comparable customers.
Example from the financial sector:
A Swiss SME specializing in asset management measures: 35% time saving on report writing, 20% reduction in translation costs (multilingual customers), 0 security incidents (thanks to ChatGPT Enterprise or Microsoft Copilot and training). Darest set up the measurement system and supports continuous improvement.
Go into production securely
Objective:
Industrialize validated use cases, with maximum security and compliance.
Concrete actions :
- Adopt ChatGPT Enterprise or Microsoft Copilot: contractual guarantees, encryption, SOC 2, no use of data for training, native integration with your enterprise systems. Darest helps you choose the solution (ChatGPT vs. Copilot) best suited to your technical stack, and manages contract negotiations.
- Integrate AI into existing workflows: connect ChatGPT via API or Copilot via Microsoft Graph to your business tools (CRM, ERP, reporting tools). Darest develops connectors and automations (Power Automate, Azure Logic Apps, ChatGPT API).
- Document all processes: traceability (who used AI, when, for what), auditability (compliance with internal policies and regulations). Darest sets up logging and compliance systems.
- Set up an incident management system: what to do if ChatGPT/Copilot generates a critical error (escalation process, customer communication, correction). Darest writes procedures and trains your support teams.
- Carry out regular audits: RGPD/LPD compliance, compliance with OpenAI/Microsoft usage policies, output quality. Darest performs semi-annual audits and produces compliance reports.
Financial sector example:
A bank integrates ChatGPT Enterprise or Microsoft Copilot into its CRM via API: advisors can generate customer summaries with a single click, but each summary is logged (traceability), reviewed by a human (validation), and excluded from OpenAI/Microsoft training (confidentiality). Darest developed the connector, configured the governance rules and trained the advisors.
Operational checklist: 7 checkpoints
Before deploying an AI use case in production, check :
- Governance: Has the use case been validated by the AI committee?
- Compliance: Impact analysis (AIAD/EIPD) carried out? RGPD/LPD complied with?
- Security: Sensitive data excluded? Enterprise or Copilot version used?
- Human validation: Does a human validate every output before critical use?
- Training: Have users been trained in the limits of AI?
- KPIs: Performance measurement in place? Tangible results expected?
- Incident management : Escalation process defined for critical errors?
Darest Informatic supports you in all these areas, from initial audit to training and ongoing management, right through to production start-up. We become your outsourced AI team, on demand, without the costs of an in-house structure.
Operational checklist: 7 checkpoints
Before deploying an AI use case in production, check :
- Governance: Has the use case been validated by the AI committee?
- Compliance: Impact analysis (AIAD/EIPD) carried out? RGPD/LPD complied with?
- Security: Sensitive data excluded? Enterprise or Copilot version used?
- Human validation: Does a human validate every output before critical use?
- Training: Have users been trained in the limits of AI?
- KPIs: Performance measurement in place? Tangible results expected?
- Incident management : Escalation process defined for critical errors?
Darest Informatic supports you in all these areas, from initial audit to training and ongoing management, right through to production start-up. We become your outsourced AI team, on demand, without the costs of an in-house structure.
AI as a sustainable competitive advantage
The spontaneous adoption of ChatGPT or Copilot by your employees is a positive signal: the organization is agile, curious and innovative. But to transform this dynamic into a competitive advantage, you need structure. Governance, training, measurable use cases, rigorous KPIs, secure implementation: these five steps form a proven framework.
The organizations that succeed will not be those that use AI the most, but those that pilot it the best - with rigor, method and the support of experts who know both the technology, the regulations and the operational realities of your sector.
Would you like to structure your AI strategy without recruiting a dedicated team? Let's discuss your situation: a Darest expert will call you back within 24 hours.