Implement AI in business.
5-step method, use cases by department, ROI measurement: everything an SME or mid-market leader needs to know to succeed with their AI project.
TL;DR
Complete guide to implementing AI in business. 5-step method: Diagnostic, POC, Integration, Training, Optimization. Use cases by department (Finance, HR, Marketing, Operations, Customer Service, IT). Average ROI 3.5x, 40% reduction in operational costs, results in 8-12 weeks. Free AI diagnostic by Keerok, agency based in Lille, France.
AI in every department
Every department in your business can benefit from artificial intelligence. Here are the most profitable use cases by department.
Accounting automation & reporting
Automatic invoice processing, intelligent bank reconciliation, financial report generation, and anomaly detection.
Saving: -60% time on accounting close
Intelligent recruitment & onboarding
Automatic resume screening, candidate-job matching, HR chatbot for employees, onboarding automation.
Saving: -70% pre-screening time
Personalization & content generation
Advanced segmentation, campaign personalization, SEO content generation, customer sentiment analysis.
Saving: +45% conversion rate
Business process optimization
Demand forecasting, supply chain optimization, predictive maintenance, workflow automation.
Saving: -35% operational costs
AI-augmented support
Intelligent chatbot, automatic ticket routing, sentiment analysis, suggested responses for agents, AI knowledge base.
Saving: -50% resolution time
Development & infrastructure
Development assistance, automated code review, intelligent monitoring, proactive incident detection.
Saving: +40% dev productivity
Our method in 5 steps
A progressive and pragmatic approach to minimize risks and maximize results for your AI project.
Diagnostic
Audit of your business processes, mapping of available data, and identification of AI use cases with the highest ROI. Assessment of your digital maturity.
Proof of Concept
Rapid development of a functional prototype on the priority use case. Validation in real conditions with a controlled scope and limited budget.
Integration
Production deployment with connection to your existing tools (CRM, ERP, emails, databases). Setting up data flows and automated processes.
Training
Upskilling your teams on deployed AI tools. Practical workshops, documentation, and change management support to ensure adoption.
Optimization
Continuous KPI tracking, real ROI measurement, and model adjustments. Identifying new use cases to deploy to amplify results.
The ROI of AI in numbers
average ROI observed on supported AI projects
average reduction in operational costs
weeks to first measurable results
of projects achieve their performance targets
| Benefit | Short term (0-6 months) | Long term (6-24 months) |
|---|---|---|
| Productivity | Automation of repetitive tasks | Reallocating teams to value creation |
| Quality | Reduction of human errors | Continuous improvement through learning |
| Decision | Quick access to relevant data | Predictive analysis and trend anticipation |
| Competitiveness | Differentiation through innovation | Sustainable and scalable competitive advantage |
The obstacles and our solutions
Every obstacle to AI implementation has a concrete solution. Here is how we address them.
Resistance to change
Teams fear being replaced by AI or reject new tools.
Our solution
Change management from the start: involving teams in choosing use cases, progressive training, demonstrating concrete gains. AI assists, it does not replace.
Data quality
Scattered, unstructured, incomplete, or siloed data.
Our solution
Initial data audit with remediation plan. Many modern AI solutions (LLMs, RAG) work with unstructured data. We start with what you have.
Budget constraints
Limited budget, difficulty justifying the investment, fear of overruns.
Our solution
Progressive POC approach: small initial investment with measurable ROI in 3 months. Help with BPI France applications and regional subsidies (up to 50% funding).
Technical complexity
Lack of internal AI skills, complex technology choices, integration with existing systems.
Our solution
Keerok handles all technical aspects. Open and documented architectures to avoid lock-in. Training your teams for progressive autonomy.
Why Keerok
Dual Automation + AI expertise
We combine process automation and artificial intelligence for complete solutions. No need for two providers.
Pragmatic approach, not theoretical
No endless PowerPoint slides. We code, deploy, and measure. Every project starts with a concrete POC delivering results in just a few weeks.
Complete A-to-Z support
From initial diagnostic to continuous optimization, including development, integration, and training. A single point of contact for the entire project.
projects delivered
years of experience
They Trusted Us
Frequently asked questions
What budget should you plan for implementing AI in your business?
The budget depends on complexity: an initial pilot project costs between 5,000 and 20,000 euros. A full deployment with integration into existing processes ranges from 20,000 to 80,000 euros. Funding options exist: BPI France, Hauts-de-France regional subsidies, and the Innovation Tax Credit (CII) can finance up to 50% of the project.
Which department should you start AI implementation with?
The most profitable departments to start with are customer service (chatbots, response automation), finance (invoice processing, automated reporting), and operations (process optimization). The choice depends on your available data and business priorities. A free diagnostic helps identify the best starting point.
What data do you need to implement AI?
Contrary to popular belief, you don't need big data. Many AI solutions (chatbots, document automation, agents) work with your existing data: emails, documents, CRM databases, Excel files. What matters is data quality and accessibility, not quantity.
How long does it take to see ROI on an AI project?
A well-scoped AI project generates its first results in 8 to 12 weeks. Full ROI is measured between 6 and 12 months depending on complexity. Document automation and chatbot projects show the fastest returns (3 to 6 months).
Do you need to hire a data scientist to implement AI?
No, not necessarily. Modern solutions (GPT-4, Claude, no-code AI tools) allow you to deploy AI applications without an internal data science team. A partner like Keerok handles the technical side and trains your teams to use the tools. Internal hiring only becomes relevant once you reach a certain volume of AI projects.
What is the difference between AI and traditional automation?
Traditional automation follows predefined rules (if X then Y). AI can understand text, analyze images, make decisions in ambiguous situations, and improve over time. The ideal approach is often to combine both: automation for repetitive and predictable tasks, AI for tasks requiring judgment.
What are the risks of an AI project in business?
The main risks are: lack of team buy-in (solved through training and change management), data quality (solved through a preliminary audit), budget overruns (solved through a progressive POC approach), and technology lock-in (solved through open and documented architectures).
Are there financial grants available for AI in business?
Yes, several programs: BPI France's AI Diagnostic (up to 50% funding), regional subsidies (Hauts-de-France, Ile-de-France), the Innovation Tax Credit (CII, 20%), and European programs (Horizon Europe). Keerok helps you with funding applications.
What KPIs should you track for an AI project?
KPIs vary by use case: time saved per process, reduced error rate, cost per transaction, customer satisfaction rate, number of automated tasks, overall ROI. The key is to define metrics before deployment and measure them regularly.
How to convince management to invest in AI?
Three levers: 1) Quantify the cost of inaction (lost hours, errors, missed opportunities), 2) Propose a low-risk pilot project with measurable ROI in 3 months, 3) Show concrete examples of similar SMEs that succeeded. The free Keerok diagnostic provides these elements in a structured report.
Free 30-minute AI diagnostic
An expert analyzes your processes and identifies the most profitable AI use cases for your business.
- No commitment, 100% free
- Opportunities report delivered in 48h
- Tailored for SMEs and mid-market companies across France