Running a company and AI is catching your eye? I understand. Between the extravagant promises and the legitimate fears, it is not easy to find your way.
At Smart Impact, many of our clients already ask us the same question: “AI, do we get started or do we wait?”
Table of contents
The 3 concrete uses of AI in business
- Automating repetitive tasks
- Predictive analysis for informed decisions
- Improving the customer experience
What are the pitfalls to avoid?
- Rushing in without a clear strategy
- A lack of team training
- Security and privacy weaknesses
How do you make your move to AI a success?
- Start small, but start now
- Invest in continuous training
- Favour proven solutions
The 3 concrete uses of AI in business
- Automating repetitive tasks
No more time lost on administrative tasks with no added value. AI takes over data entry, email sorting and the generation of standard reports.
One of our clients in real estate gained 15 hours a week by automating lead qualification. His team now focuses on what really matters: human contact with clients.
- Predictive analysis for better-informed decisions
AI algorithms excel at analysing massive datasets. They pick up trends invisible to the naked eye and anticipate future behaviour.
In retail, for instance, AI optimises stock by predicting demand. The result? Less waste and better product availability.
- Improving the client experience
Intelligent chatbots, personalised recommendations, 24/7 customer service… AI is transforming the client relationship.
A textile SME lifted its sales by 23% through AI-based personalised recommendations. The secret? Ultra-relevant suggestions that give the impression the brand genuinely knows us.
What are the pitfalls to avoid?
- Rushing in with no clear strategy
Do not rush at the first AI solution that comes along. First define your business objectives and identify the processes to optimise.
- Teams that are not trained
AI does not replace your staff, it assists them. Invest in their upskilling to turn them into “augmented workers”.
- Security and confidentiality flaws
Data is the nerve centre. Make sure your AI solutions comply with the GDPR and protect sensitive information.
How do you make your move to AI a success?
- Start small, but start now
Go for a tightly scoped pilot project. You will limit the risks while learning quickly from your mistakes.
- Invest in continuous training
Training your teams is not optional, it is a necessity. Budget substantially for training and for support over time.
- Favour proven solutions
In 2025, there is no need to reinvent the wheel. Off-the-shelf solutions already exist for most common uses.
What budget should you plan to get started with AI?
It all depends on your objectives. Expect between CHF 5000.- and CHF 15000.- for a first pilot project, including the technical solution and team training.
How long before the first results?
On average, the first productivity gains are visible within 3 to 6 months. But allow 12 months before a meaningful ROI can be assessed.
Which skills should be developed first?
Train your teams first in data analysis and AI project management. The technical skills will come later.
Note: this article reflects my hands-on experience with our clients. Feel free to contact us to explore points specific to your sector in more depth.
To take the thinking about AI in business further, here are some quality resources that complement this article:
McKinsey – The State of AI in 2024
An in-depth study revealing that 55% of companies use AI in one way or another. The analysis details the most advanced sectors and the returns on investment observed.
🔗 The State of AI in 2024: Generative AI’s breakout year
Deloitte – Tech Trends 2025 A complete report on technology trends with a particular focus on AI. Deloitte analyses in particular the effect of generative AI on jobs and business processes.
Gartner – Top Strategic Technology Trends A reference for understanding where AI sits in the overall technology landscape. The firm sets out the most promising use cases for 2025.
🔗 Top Strategic Technology Trends for 2025
MIT Technology Review – AI Index Report A rigorous academic analysis taking stock of AI's technical advances and their adoption by business. Particularly useful for understanding what is at stake in training.
🔗 The AI Index Report – MIT Technology Review
Boston Consulting Group – AI Maturity Report
A study offering an assessment framework for measuring your AI maturity and defining a roadmap suited to your context.
🔗 Getting AI Transformation Right
Editor's note: these sources are updated regularly. I encourage you to consult the latest available versions to get the most recent data.
