Should You Hire an AI Developer or an AI Company? The Honest Answer

When businesses think about hiring an AI developer, they think about salary. But salary is only 40 to 60 percent of the total cost. Here is what the full picture looks like.

And these numbers assume you find the right person on the first try. The AI talent market is intensely competitive. The average time to hire a senior AI engineer in Europe is 3 to 6 months. During that time, your project is stalled. If you make a bad hire, the cost of replacing them (recruitment fees, lost productivity, severance) adds another 30,000 to 60,000 euros.

There is also the single point of failure problem. One developer means one perspective, one skill set, and zero redundancy. If they leave, go on vacation, or get sick, your AI capability goes to zero. An AI company brings a team with diverse skills and built in redundancy.

Working with an AI company looks different financially. Instead of a large fixed cost (salary) with variable output, you get a variable cost tied directly to deliverables.

The key advantages are immediate availability (no 3 to 6 month recruitment process), team depth (you get multiple specialists, not one generalist), built in project management, and the ability to scale up or down based on actual needs. You do not pay for an engineer during months when there is no AI work to do.

The disadvantage is that you are sharing the team's attention with other clients. A dedicated employee focuses 100 percent on your business. A partner allocates time based on your engagement level. For most businesses, this tradeoff is heavily in favor of the partner model because AI work is typically project based, not a constant stream.

Despite the cost analysis above, there are clear situations where hiring is the right choice.

AI is your core product. If your business builds and sells AI powered software, you need in house AI talent. Period. Your competitive advantage depends on proprietary AI capabilities that you cannot outsource. A healthtech startup building an AI diagnostic tool needs AI engineers on the team. A logistics company using AI to optimize routes does not.

You have continuous, full time AI work. If your AI roadmap has enough work to keep a senior engineer busy 40 hours a week for the next 2 or more years, hiring becomes cost competitive with outsourcing. But be honest about this. Most businesses overestimate their ongoing AI needs. The initial build is intense, but once automations are deployed, maintenance requires far less time.

You have strict security or compliance requirements. Some industries (defense, certain financial services, healthcare in specific jurisdictions) have regulations that require all development to be done by employees or within specific geographic boundaries. If this applies to you, hiring may be mandatory.

You want to build long term institutional AI knowledge. An internal team accumulates deep understanding of your data, processes, and domain over time. This knowledge compounds and becomes a strategic asset. If you are planning a multi year AI journey with increasing sophistication, building an internal team eventually makes sense, but you can start with a partner and transition gradually.

For the majority of businesses, partnering with an AI company is the better choice. Here is when it is clearly the right path.

You need results fast. Hiring takes months. A good AI partner can have an engineer working on your project within days. AlbTech's model is built around this: plug in tomorrow, ship by Friday. When a client comes to us with an urgent automation need, we can often assign a team within 48 hours because we have a network of over 500 engineers with diverse specializations.

You need diverse AI skills. AI is not one discipline. Computer vision, natural language processing, data engineering, MLOps, and conversational AI are all different specialties. One hire gives you one specialty. An AI company gives you access to all of them. When your chatbot project finishes and you need a document processing system next, you get a different specialist without a new hire.

AI is a tool for your business, not the business itself. If you are a pharmaceutical distributor, a restaurant chain, a construction company, or an insurance agency, AI is something you use to operate better. It is not what you sell. In this case, you want the AI capability without the overhead of building and managing an AI team.

You want to test before committing. Partnering lets you validate whether AI delivers value for your business before making a significant hiring investment. Run two or three automation projects with a partner. Measure the results. If the value is clear and the work is ongoing, then consider hiring. You will also have a much better idea of what skills to look for because you will have seen what good AI work looks like.

There is a third option that many businesses overlook: team augmentation. Instead of choosing between hiring or outsourcing, you embed external AI engineers into your existing team. They work alongside your people, use your tools, attend your meetings, and operate as de facto team members, but they are managed and employed by the AI company.

AlbTech's team augmentation model draws from a network of over 500 engineers across Albania, the Balkans, and Eastern Europe. When a client needs a specific skill, whether it is a Python ML engineer, a conversational AI specialist, a data engineer, or a full stack developer with AI experience, we match the right person from our network and embed them in the client's team.

The economics are compelling. A senior AI engineer through team augmentation costs 4,000 to 8,000 euros per month, fully loaded. That is 48,000 to 96,000 euros per year versus 142,000 to 238,000 euros for a direct hire at the same level. You get the same quality of work, the same dedication, and the same availability, at 40 to 60 percent of the cost.

The operational advantages are equally strong. Need to scale up for a big project? We add engineers in days, not months. Project finished and workload is lower? Scale back without layoffs or severance. Need a different skill set for the next phase? We swap in the right specialist. This flexibility is impossible with traditional hiring.

"Plug in tomorrow, ship by Friday" is not a marketing slogan at AlbTech. It is how we operate, and there is a specific process behind it.

When a client needs an AI engineer or a team, here is what happens. Day one: we review the requirements and match engineers from our network based on skills, experience, and domain knowledge. Day two: the engineer has access to the client's systems, has been briefed on the project, and begins work. By the end of the first week, they have produced a tangible deliverable, whether that is a working prototype, a technical design document, or the first iteration of an automation.

This speed is possible because of how we structure our network. Every engineer in AlbTech's network has been pre vetted through technical assessments, project simulations, and reference checks. They are already trained on our deployment methodologies and quality standards. When they join a client project, they do not need weeks of onboarding. They need a project brief and system access.

We have deployed engineers for construction companies in Milan, fintech startups in Zurich, e commerce platforms in New York, and pharmaceutical distributors in Tirana. The time zone alignment with European clients (CET and CET plus minus one hour) means real time collaboration during business hours. For US clients on the East Coast, there is a 6 hour overlap, which is enough for daily standups and real time collaboration on critical issues.

Tell us what you need. Whether it is a single automation, a full AI team, or one specialist to augment your existing team, we will give you an honest recommendation on the best approach for your situation. If hiring internally is the right answer, we will tell you that and even help you write the job description.