Frequently asked questions
Do you have to be a big company to have an AI strategy ?
Where do I start if I am not comfortable with technology ?
How much does it cost to set up an AI strategy ?
Is my data safe with AI tools ?
AI is everywhere in the discourse, but in fact, the majority of entrepreneurs have no plans, here is why this paradox is happening, what it is really costing you, and how to lay the foundations of a concrete strategy without jargon, without consultants, in less than 30 minutes.
In a study conducted by Bpifrance Le Lab among more than 1,200 managers, 58% of SME and ETI business leaders consider artificial intelligence to be a survival issue In the medium term for their business, this same percentage admits that they have no formalized AI strategy.
We know it's important but we don't know where to start.
And meanwhile, 32% of French SMEs already use AI on a daily basis, more than double that of 2024, the gap is widening and each month of waiting has a real cost, even if we do not yet see it on the balance sheet. Don't be a part of these numbers.
You have to be honest about what this adoption figure covers, the vast majority of companies that “use AI” limit themselves to ChatGPT to write a few emails or to Copilot to save time on a presentation, occasional uses, carried out by a single person, carried out by a single person, carried out by a single person, without a measurable objective, without integration into business processes.
The result is clear: an MIT Sloan Management Review Study Reveals That 95% of business AI projects fail to produce a measurable impact on financial results. Not because the technologies are bad, but because businesses are launching without a definite course.
“Testing AI” is not a strategy but reducing quotation processing time by 30% or automating 80% of unpaid reminders, yes.
Hundreds of tools available, new models launched every month, contradictory comparisons everywhere. This abundance is paralyzing and operational urgency, customers, invoices and cash flow are always taking over.
72% of managers of VSEs and SMEs who are interested in AI say they do not find use cases adapted to their business, most of the content on AI is written for large companies with dedicated IT teams and budgets in millions of euros but nothing like the reality of an entrepreneur who manages everything or almost alone.
Investing in a solution that will not be adopted, exposing confidential data, choosing an obsolete tool in six months, these fears are legitimate and, without a clear framework, they are enough to postpone the decision indefinitely.
It is the most underrated obstacle. You can't build an effective AI strategy if your data is scattered between your Shopify store, your Stripe account, your bank, your email reminders, and your quotes in another software. AI needs clean, centralized, usable data, without this database, even the best tool can't do anything concrete.
Waiting is not a neutral position, it is a decision with measurable consequences.
What you are losing and the concrete impact :
Productivity : 1 to 2 hours per employee per day on repetitive tasks
Cash flow : Unpaid invoices that are getting longer due to the lack of automated reminders
Competitiveness : your competitors who adopt AI are reducing their costs every month
Missed ROI : A well-sized AI project generates a median ROI greater than 150% in less than 7 months
Don't try to solve everything at once, ask yourself one question: what is the task that is costing me the most time and that I hate doing?
For most entrepreneurs, the most common answers are:
Pick just one of these pains and that will be your entry point.
Take a quick inventory:
This is where most entrepreneurs realize their real problem and it is not AI that is actually but the centralization of data.
A strategy without indicators is not a strategy, formulate your objective in concrete terms.
To avoid: “I want to use AI to better manage my business”
Advisor: “I want to reduce the time spent reminding my unpaid customers by 50% within 60 days”
To avoid: “I want to automate my billing”
Advisor: “I want 80% of my recurring invoices to be generated and sent automatically within 30 days”
Resist the temptation to test five at the same time, the golden rule: a single use case, measured rigorously for 30 days, before expanding. Choose solutions that integrate with your existing tools, require no technical skills and offer a visible return on investment quickly.
Lookout : Many managers choose an AI tool before they have even centralized their data, it's putting the cart before the horse and centralization is the, not an option.
Beyond the theoretical strategy, the feedback from the field is converging; the entrepreneurs who have structured their adoption of AI are not talking about a technological revolution. They Talk About Serenity Regained : less time on repetitive tasks, fewer oversights in customer follow-up, financial visibility that allows decisions to be made better and faster.
It is not AI that has transformed their business, it is the fact that they finally have a clear view of their data and processes that work without them having to think about it, but according to an analysis of more than 230 companies, 74% of those that have adopted AI in a structured way see an increase in the productivity of their teams, without reducing headcount.
The key: do not wait until you have “understood everything” to start, the selection of a first use case, its integration and its first results take time and the companies that start today will be the ones that will experience this transition most calmly.
