Small steps today, big transformations tomorrow.
AI to improve business processes is no longer a “future” technology; it’s increasingly becoming part of businesses’ daily activities. You don’t need to revolutionize everything: just start, test, and understand. In this guide, we’ll explain how to take the first steps, stress-free and waste-free.
Estimated reading time: 6 minutes
Table of contents
Why You Should Start Using AI Today to Improve Business Processes
According to data from the Buyer Behavior Report 2025, 57% of companies will increase software spending in 2025. And do you know what’s driving this increase? Artificial intelligence.
AI for improving business processes is no longer an R&D project: budgets come from IT, marketing, customer care, and operations departments. In other words, it’s becoming an integral part of business processes.
And if you’re wondering, “Where do I start?”, the answer is simple:
with a small, high-impact project.
AI to Improve Business Processes: “LAND and Expand”
Using AI to improve business processes isn’t just about implementing it. It also means using it to make better decisions. In practice, if you don’t start using AI, you risk losing not only operational competitiveness, but also strategic competitiveness.
In the world of AI applied to business processes, the new mantra is “Land and Expand.”
Simple to understand, yet incredibly powerful to apply, this strategic model is based on a fundamental principle:
Start small, demonstrate concrete value, then scale sustainably.
Today’s buyers want:
- Flexible models (pay-as-you-go, outcome-based)
- Lightweight projects that can be implemented quickly
- Measurable ROI, not abstract features
And this applies to both large enterprises and SMEs.
In the past, many technology implementations started with large, monolithic projects that were lengthy to implement, expensive, and with uncertain or diluted ROI. Today, the game has changed: buyers, especially in the AI space, no longer want complex, expensive, and slow-to-implement solutions.
Instead they want:
Flexible pricing models
For example:
Pay-as-you-go: You pay based on actual usage, without overly rigid initial constraints
Outcome-based: The cost depends on the results achieved (e.g., number of automated tickets, time saved, sales generated)
This makes it easier to start even with limited budgets, encouraging experimentation and scalability of AI projects for business processes.
Lightweight projects that can be activated immediately
Companies are looking for ready-to-use solutions that can be implemented in days or weeks, not months. AI, especially no-code AI, perfectly meets this need, allowing companies to see initial results quickly.
Measurable ROI
No one has the time (or desire) to invest in abstract or futuristic features. Today, what truly matters is what improves processes, generates efficiency, cuts costs, or increases customer satisfaction.
The value of AI for business processes must be tangible, documented, and replicable. This is why the first pilot project is so important: it must provide concrete proof that the technology works and can scale.
Improve Business Processes in large companies and SMEs
The beauty of the Land & Expand strategy is that you don’t have to be a global giant to implement it. It also works perfectly for SMEs, which often have more limited resources but greater decision-making flexibility.
In an SME, starting with a small AI project (e.g., a virtual assistant for FAQs or internal request management) can already bring tangible benefits within a few weeks. Once the value has been tested, it will be natural to extend its use to other departments or processes.
In summary, the “Land & Expand” approach:
- Lowers the entry threshold: you can start even with limited budgets
- Reduces risks: controlled testing on specific cases
- Accelerates learning: AI is learned by using it, not by reading white papers
- Fosters internal adoption: the team sees the value and supports growth
- Increases the speed of change: from small test to systemic transformation
Where to apply it: business areas and use cases
AI can be applied virtually anywhere to improve business processes. Here are some key areas:
Customer care
- Chatbots and virtual assistants
- Review sentiment analysis
- Automated email replies
Human resources
- CV screening and candidate matching
- Predictive turnover analysis
- Automated onboarding
Marketing and sales
- Campaign personalization
- Lead scoring and conversion forecasting
- Automated content generation
Operations
- Supply chain optimization
- Process anomaly detection
- Intelligent task planning
IT & cybersecurity
- Automated threat monitoring
- Ticket management automation
- AI for predictive maintenance
How to Get Started with AI to Improve Business Processes
Here’s a 5-step mini-plan to get you off to a good start:
- Choose a well-defined process to improve
(e.g. customer support, internal request management, FAQs, orders).
- Involve a small team
Motivated, transversal, with ownership.
- Opt for a no-code AI solution
It can be activated in just a few days and can be managed even by non-technical people.
- Monitor results and feedback
Continuous monitoring to achieve the best results.ltati.
- Plan expansion
Once you get the first results, start thinking about what happens next.
In conclusion: Don’t wait for the perfect moment to improve your processes.
AI to improve business processes isn’t a project to be put on hold “until the budget is available.” It’s a strategic tool for:
- improving efficiency
- freeing up your teams’ time
- offering better experiences to customers and employees
The world is moving fast. Companies that have started using AI today are already reaping tangible benefits.
What about you? Do you want to sit back and watch or take the first step?
Faqs – AI to Improve Business Processes
AI automates repetitive tasks, improves decision quality, reduces errors and downtime, increases productivity, and delivers personalized experiences to customers and employees. It also helps companies become more agile, competitive, and data-driven.
The best way to get started is with a well-defined, high-impact process (such as customer care or internal support). It’s advisable to use no-code AI solutions, with “land and expand” approaches—small pilot projects with measurable ROI that can be scaled over time.
Absolutely yes: AI is now accessible to even SMEs thanks to no-code tools, SaaS platforms, and flexible pricing models (pay-as-you-go). You don’t need advanced technical skills to start using it effectively.
