Choosing an AI agency is the process of selecting an external partner to design, build, and implement artificial intelligence solutions for your business — from chatbots and automations to full AI strategies. For SMBs, picking the right agency is the difference between an AI project that delivers returns and one that quietly gets shelved after six months.
The problem: in 2026, there are more than 400 agencies in the Netherlands alone positioning themselves as "AI agencies" or "AI partners." From solo operators to mature technology firms, from specialists to generalists who were building WordPress sites exclusively last year. This guide gives you seven clear evaluation criteria, an overview of red flags, and a comparison of pricing models so you can make an informed decision.
Why Does the Right Choice Matter So Much?
The difference between a good and a mediocre AI agency translates directly into money. Analysis by Gartner (2025) found that businesses that carefully select their AI partner see returns 2.3 times faster on average than those that choose on price alone. For projects under EUR 50,000 — the range where most SMB projects fall — that gap is even wider.
A wrong choice costs you more than the project budget. It also costs:
- 3 to 6 months of lost time
- Internal buy-in — a failed project makes it harder to secure budget for the next attempt
- Competitive position — while you recover, your competitor implements successfully
Our article on common AI mistakes at SMBs describes how choosing the wrong partner is often the root cause of failed projects. The right partner prevents those mistakes structurally.
The 7 Criteria for Evaluating an AI Agency
1. Demonstrable portfolio with measurable results
Every serious agency has case studies. But not all case studies are equal. Notice the difference between "we built a chatbot for company X" and "we built a chatbot that handles 67% of customer queries and saves the support team 12 hours per week."
What to look for:
- Concrete numbers: hours saved, revenue increased, errors reduced
- Comparable industry or company size to your organisation
- References you can call — not just logos on a website
An agency that cannot show measurable results probably has not achieved them.
2. Technical depth versus marketing
Many agencies sell AI as a concept but in practice build simple connections between existing tools. That is not necessarily bad — sometimes a workflow automation is exactly what you need — but you should know what you are buying.
Questions to ask:
- Which AI models do you use (GPT-4, Claude, open-source models, proprietary models)?
- Do you build custom or configure existing platforms?
- How do you handle data quality and privacy?
- Do you have experience with the EU AI Act and GDPR compliance?
An agency that only uses no-code tools but positions itself as an "AI developer" is not inherently untrustworthy, but transparency about it is essential.
3. Sector experience and understanding of your industry
AI for a logistics company is fundamentally different from AI for an accounting firm. An agency with sector experience understands your processes, knows the common software stack, and has realistic expectations about what does and does not work.
How to verify:
- Ask about projects in your industry or adjacent sectors
- Notice whether they use industry-specific terms without you having to explain them
- Check if they understand which regulations apply in your sector
Our overview of AI applications by industry shows how dramatically the approach differs per sector.
4. Transparent pricing model
This is where most selection processes go wrong. You receive three quotes: EUR 8,000, EUR 22,000, and EUR 55,000 — and you have no idea whether the most expensive is the best or the cheapest is the smartest choice. The table below compares the four common pricing models.
| Pricing model | How it works | Advantages | Disadvantages | Suited for |
|---|---|---|---|---|
| Fixed price | Pre-agreed amount for a defined scope | Predictable budget, clear deliverables | Change requests get expensive, scope must be tightly defined | Well-defined projects (chatbot, specific automation) |
| Time & materials (T&M) | Hourly rate (EUR 100–200) x hours spent | Flexible, you pay for what you use | Unpredictable final bill, requires good project management | Exploratory projects, complex integrations |
| Retainer | Fixed monthly fee (EUR 1,500–5,000) for ongoing support | Continuous availability, predictable costs | You pay even when you don't need the agency | Long-running programmes, ongoing maintenance and optimisation |
| Value-based | Price tied to achieved results (e.g., % of cost savings) | Interests are aligned, agency shares the risk | Difficult to measure, can become expensive at scale | Projects with measurable KPIs (hours reduced, revenue increased) |
More on the actual costs of AI projects can be found in our AI costs overview for SMBs.
5. Post-launch support and maintenance
Every AI system requires maintenance. Models degrade, user patterns change, and new regulations demand adjustments. An agency that only builds and vanishes after delivery leaves you with a system that slowly gets worse.
Ask specifically:
- What is your SLA after delivery?
- How much does ongoing maintenance cost per month?
- How quickly do you respond to outages?
- Do you proactively monitor the AI system's performance?
Expect a maintenance fee of EUR 200 to EUR 1,500 per month depending on the complexity of the system.
6. Team composition and availability
Who will actually work on your project? At some agencies, you do the intake with the director and the work is executed by a junior with two months of experience.
Verify:
- How many people will work on your project and what are their roles?
- What is the experience level of the developers?
- Is there a dedicated project manager or single point of contact?
- How many projects is the agency running in parallel?
A team of 3–5 specialists running 2–3 projects in parallel typically delivers better outcomes than a team of 20 generalists juggling 15 projects.
7. Communication style and working method
This criterion is most often overlooked, yet in SMB projects it is frequently decisive. If you as a business owner are used to direct communication and the agency works with weekly status reports via a ticket system, frustration is predictable.
Pay attention to:
- How quickly do they respond to your first email or inquiry?
- Do they speak in understandable language or hide behind jargon?
- Do they offer a clear consulting process with explanations at every step?
- Are they willing to handle small matters over a phone call?
Red Flags: When to Walk Away
After hundreds of AI projects in the market, patterns emerge. These signals indicate an agency you should avoid:
Guaranteed results without qualification. "We guarantee 50% cost reduction." No serious agency guarantees outcomes without first understanding your situation. AI results depend on your data, your processes, and your team.
No discovery phase. If an agency sends you a quote after a single 30-minute phone call without analysing your processes, that quote is based on assumptions. A thorough discovery phase (intake, process inventory, feasibility check) is a sign of professionalism. Read more about proper preparation in our article on whether your business is ready for AI.
One-size-fits-all pricing. "Our chatbots always cost EUR 5,000." AI projects vary enormously in complexity. An agency that charges the same price for everyone probably delivers the same standard solution to everyone.
No own portfolio, only partnerships. Some agencies function as resellers for larger platforms (Microsoft, Salesforce, HubSpot) and present those platforms' successes as their own. Always ask: "What have you built yourselves?"
Excessive jargon without explanation. An agency that fills every sentence with "neural networks," "deep learning," and "transformer architectures" without being able to explain what that means for your business is trying to impress rather than inform.
No references available. Every agency with satisfied clients is happy to share references. If they won't, ask yourself why.
Save 12 hours per week on evaluating and selecting the right AI partner by using structured selection criteria
Questions for the First Meeting
Take this list to your introductory meeting. The answers tell you more than any brochure.
- "Can you describe a comparable project you did for a company of our size?" — Demonstrates relevant experience and gives you a reference to follow up on.
- "What does your discovery phase look like and what does it cost?" — A good agency has a structured process. Expect EUR 500 to EUR 2,500 for a thorough analysis.
- "How do you measure a project's success?" — The answer should include measurable KPIs, not vague terms like "customer satisfaction" or "innovation."
- "What happens if the project does not deliver the expected result?" — Shows how the agency handles underperformance. Is there a feedback loop? Do they adjust course?
- "Who will work on my project and can I speak with them?" — You want to know who you will actually be working with, not just the salesperson.
- "How do you handle GDPR and the EU AI Act?" — Compliance is not optional. An agency without an answer here is a risk.
- "What are the costs after delivery?" — No surprises after launch. Calculate the total investment upfront, including maintenance.
How to Compare Proposals Fairly
You have received three proposals. Here is how to make a fair comparison:
Step 1: Normalise the scope. Make sure you are comparing the same deliverables. Does proposal A include a discovery phase but proposal B does not? Then you are comparing apples to oranges.
Step 2: Calculate the total cost of ownership (TCO). Add up not just build costs but also: licences, hosting, maintenance, team training, and potential change requests. The cheapest proposal quickly becomes the most expensive if maintenance costs EUR 2,000 per month.
Step 3: Weigh quality above price. A project costing EUR 25,000 that saves 15 hours per week delivers more value than a project costing EUR 8,000 that gets abandoned after three months. Our article on AI costs for SMBs helps you set realistic budgets.
Step 4: Check references. Call at least two references per agency. Ask about the collaboration, not just the end result. How was the communication? Were deadlines met? How did the agency handle setbacks?
Start with a Clear Foundation
Choosing an AI agency does not have to be a gamble. With the seven criteria in this article, you can evaluate any agency in a structured way and compare proposals fairly. The red flags help you identify underperforming agencies early.
The most important lesson: take your time with the selection. Spending an extra week evaluating agencies saves you months of frustration and thousands of euros in failed projects. Still unsure whether outsourcing is the right choice at all? Read our comparison of outsourcing AI vs. building in-house for an objective assessment. Start with a clear project brief — that document determines the quality of the proposals you receive. Also read our complete guide to hiring AI consulting for a broader perspective on working with external AI specialists.
Want to know if there are concrete AI opportunities for your business? Start with a no-obligation conversation — not a sales pitch, but an honest analysis of your situation.
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