AI training has become a growing source of remote work. Behind many artificial intelligence systems are human workers who evaluate responses, label data, identify errors, compare outputs and provide feedback that helps improve AI models.
This has opened opportunities for people who aren’t necessarily software developers or AI engineers.
Two names that have appeared frequently in discussions about this kind of work are DataAnnotation and Remotasks. But there is an important problem with comparing them as though both platforms operate exactly as they did several years ago.
The AI-training industry has changed.
DataAnnotation continues to be relevant for AI evaluation and reasoning-based work, while the traditional Remotasks contributor model has shifted toward Scale AI’s Outlier platform.
So, if you’re looking for AI training work in 2026, which one should you choose?
The answer depends on your skills, the type of work you want and, particularly for Nigerians, whether the specific project currently accepts workers from your location.
What Is DataAnnotation?
DataAnnotation connects contributors with projects designed to evaluate and improve artificial intelligence systems.
Instead of simply entering information into a database, you may be asked to read an AI-generated response, assess its quality, identify factual or logical problems, compare two answers or produce an improved response.
Typical work can include:
- Writing and editing
- AI response evaluation
- Fact-checking
- Reasoning tasks
- Comparing AI-generated answers
- Following detailed instructions
- Coding evaluation
- Specialist professional evaluation
Some projects require specialised knowledge, which means the platform can be relevant to people with professional backgrounds as well as general contributors.
The selection process is also important. Access to projects depends on passing the required assessment and meeting the requirements of available work.
What Was Remotasks?
Remotasks was historically known as a crowdsourcing platform for data annotation and AI training.
Its work was strongly associated with tasks such as image and video annotation, object identification, categorisation, image segmentation, 3D annotation, text labelling and quality assurance.
This made it quite different from the reasoning-heavy work commonly associated with DataAnnotation.
Someone working on a traditional Remotasks project might, for example, identify objects in an image or annotate sections of a video frame. The emphasis was often on accurately following a defined annotation process.
The Important Remotasks Update for 2026
This is where many older articles become confusing.
Remotasks was part of Scale AI’s contributor ecosystem, and Scale AI moved contributors toward Outlier. The source material notes that Scale AI announced the transition and encouraged Remotasks contributors to join the newer platform.
Therefore, if you’re searching for Remotasks jobs today, don’t rely entirely on tutorials or articles written several years ago.
For current Scale AI contributor opportunities, Outlier is the more relevant platform to investigate.
That doesn’t mean the history of Remotasks is unimportant. It simply means that someone planning their remote-work strategy in 2026 needs to distinguish between the old Remotasks model and the current platforms available to contributors.
DataAnnotation vs Remotasks: What’s the Biggest Difference?
The biggest difference has always been the nature of the work.
DataAnnotation is generally more focused on:
- Language
- Reasoning
- Writing
- AI response evaluation
- Research
- Coding
- Specialist knowledge
Traditional Remotasks work was more heavily associated with:
- Image annotation
- Video annotation
- Data labelling
- Object identification
- Categorisation
- Segmentation
- Quality assurance
That means the better option depends heavily on what you’re good at.
If you enjoy writing, analysing information, researching, solving problems or evaluating arguments, DataAnnotation may be a better fit.
If you prefer structured tasks where you follow detailed instructions to label or classify data, traditional Remotasks-style work may have been more suitable.
Which One Pays More?
This is one of the most common questions, but it’s also where you need to be careful.
DataAnnotation advertises some generalist work starting around $20 per hour, with higher rates advertised for certain specialised projects. These are advertised rates, not guaranteed earnings.
Your actual income can depend on:
- Whether you pass the assessment
- Which projects you qualify for
- How much work is available
- Your location
- Your performance
- How efficiently you complete tasks
Old Remotasks earnings figures should be treated with even more caution because its contributor model has changed.
A comparison based on outdated Remotasks hourly rates could give someone the wrong impression about what they can earn in 2026.
The practical picture is therefore:
DataAnnotation: Potentially strong earning opportunities for people with good reasoning, writing, coding or specialist skills.
Traditional Remotasks: Historically offered a range of annotation work, but the old contributor model has changed.
Outlier: The more relevant platform to investigate if you’re specifically interested in current Scale AI contributor opportunities.
Which One Is Easier to Join?
Neither should be treated as a platform where you simply create an account and immediately receive unlimited work.
DataAnnotation uses an assessment-based selection process. You have to demonstrate that you can perform the type of work required.
Traditional Remotasks was historically more accessible to beginners because contributors could complete training for specific task types before gaining access to projects.
But because the contributor ecosystem has changed, someone starting now should investigate current Outlier and Scale AI requirements rather than following an old Remotasks tutorial step by step.
Who Is DataAnnotation Best For?
DataAnnotation may suit you if you:
- Write well in English
- Enjoy analysing information
- Have strong reasoning skills
- Can follow complex instructions
- Are good at spotting mistakes
- Know how to research
- Have programming skills
- Have professional expertise
- Can work independently
The work can be mentally demanding because you’re often required to exercise judgement rather than simply complete repetitive clicks.
For someone with strong analytical ability, however, that can also be the attraction.
Who Was Remotasks Best For?
Traditional Remotasks was particularly appealing to people who wanted to enter the AI-data industry without advanced professional qualifications.
Its training system allowed contributors to learn particular task types before working on projects. Some work involved repetitive labelling and classification, so attention to detail and consistency were often more important than advanced academic knowledge.
The important part for someone starting in 2026 is that the old system should not be assumed to still operate in exactly the same way.
What About the Availability of Tasks?
This may be more important than the advertised hourly rate.
AI-training platforms are generally project-based. A platform may have plenty of work available today and significantly less a few weeks later.
Your access can depend on:
- Your country
- Your assessment results
- Your skills
- Your quality score
- Available projects
- Client requirements
- Current demand
That is why it would be risky to quit your regular job simply because you were accepted onto an AI-training platform.
Think of these platforms as flexible remote-work opportunities, not guaranteed employment.
DataAnnotation: Advantages and Disadvantages
Advantages
- Potentially attractive hourly rates
- Flexible working
- Remote opportunities
- Analytical work
- Opportunities for specialists
- No traditional office requirement
Disadvantages
- The selection process can be competitive
- Passing an assessment doesn’t guarantee continuous work
- Project availability can change
- Some contributors report communication difficulties
- Higher-paying specialist work requires relevant expertise
Remotasks: Advantages and Disadvantages
Traditional Remotasks had several characteristics that made it attractive to beginners.
Advantages
- Beginner-friendly training
- A variety of annotation tasks
- Flexible work
- Remote working
- An opportunity to gain experience in AI data work
Disadvantages
- Pay varied between projects
- Some work was repetitive
- Task availability fluctuated
- Some projects had geographic restrictions
Again, these points describe the traditional Remotasks contributor model, not necessarily the current experience someone will have through today’s Scale AI ecosystem.
What About DataAnnotation for Nigerians?
This is particularly important if you’re reading this from Nigeria.
You should not assume that every DataAnnotation project is available to Nigerian applicants.
Eligibility can depend on the project and location, so check the current application requirements before spending time preparing for a particular opportunity.
The same principle applies to other international AI-training platforms.
For Nigerians, it makes sense to have several legitimate options rather than relying entirely on one company.
Depending on current availability and your skills, you can also investigate platforms such as Mindrift, Atlas Capture, DataLens Africa, OneForma, CrowdGen by Appen, TELUS Digital AI Community and OpenTrain AI.
So, Which One Pays More?
If we’re comparing the type of work and earning potential, DataAnnotation has an advantage for people who qualify for its higher-value projects.
The reason is that reasoning, writing, coding and specialised professional knowledge can command higher rates than basic annotation work.
But there’s an important catch.
A higher hourly rate does not automatically mean higher monthly income.
Suppose one platform offers $30 per hour but you only receive a few hours of work. Another offers less per hour but provides significantly more available tasks.
The second platform could potentially produce more income over a particular period.
That’s why you should consider task availability, eligibility, skill requirements and payment reliability, rather than choosing solely on the advertised hourly rate.
Which Should You Choose in 2026?
If you’re interested in AI evaluation, writing, reasoning, research, coding or specialist work, DataAnnotation is the more relevant option to investigate.
If you’re interested in traditional image, video and data annotation, don’t limit your search to the old Remotasks name.
Look at the current platforms operating in this part of the AI-training market.
For former Remotasks-style work connected to Scale AI, Outlier is now the more relevant platform to investigate.
For Nigerians, it also makes sense to look at Africa-focused options such as Atlas Capture and DataLens Africa where their current opportunities match your skills and location.
Don’t Build Your Entire Income Around One Platform
This may be the most useful lesson for anyone entering AI training.
Don’t treat one platform as your permanent source of income.
Instead, build a small portfolio of legitimate opportunities.
For example:
DataAnnotation: Look for higher-value AI evaluation work.
Atlas Capture: Check for data-collection and annotation projects.
DataLens Africa: Look for African-focused annotation and language opportunities.
Mindrift: Explore writing, research, coding and specialist AI-training projects.
OneForma: Investigate language, transcription, annotation and AI-data projects.
TELUS Digital: Check the AI Community opportunities currently available in your location.
CrowdGen by Appen: Look for current AI-data and evaluation projects.
This gives you more options when one platform has little or no work available.
Frequently Asked Questions
Is DataAnnotation better than Remotasks?
For someone interested in AI evaluation, reasoning, writing, coding or specialist work, DataAnnotation may be the more relevant choice. Traditional Remotasks focused more heavily on data annotation, but its contributor model has changed.
Does Remotasks still work the same way in 2026?
You should not assume so. Scale AI moved Remotasks contributors toward Outlier, making Outlier the more relevant platform to investigate for current Scale AI contributor opportunities.
Can Nigerians join DataAnnotation?
Eligibility depends on current project and location requirements. Check the current application information rather than assuming that every project accepts Nigerian workers.
Do I need coding skills?
No. Many AI-training tasks involve writing, reasoning, research, evaluation, language or data annotation. Coding becomes particularly useful for technical and programming-related projects.
Can AI training become a full-time income?
It can provide meaningful income for some people, but there is no guarantee of consistent work. Project availability can change, so it is safer to treat it as project-based remote work until you have established a reliable workload.
Is AI training worth trying in Nigeria?
Yes, it can be worth exploring, particularly if you have useful writing, research, language, technical or professional skills. But apply realistically and don’t assume that registration automatically leads to paid work.
Final Verdict
DataAnnotation and Remotasks represent two different sides of AI training work.
DataAnnotation is particularly attractive to people who can write, reason, research, code or apply professional expertise.
Traditional Remotasks was more closely associated with structured data annotation and labelling, but that old contributor model has changed significantly.
For someone starting in 2026, the better question is therefore not simply “DataAnnotation or Remotasks?”
A better question is:
What kind of AI work matches my skills, and which legitimate platforms currently have opportunities for someone in my location?
If you have strong analytical and writing skills, investigate DataAnnotation and similar AI-evaluation platforms.
If you’re interested in data labelling, explore current annotation platforms.
If you have advanced professional expertise, look for specialist AI-training projects where your existing knowledge can command higher rates.
AI training can be a genuine way to earn remotely, but it is best approached as project-based work rather than guaranteed employment. Your skills, location, quality of work and the availability of projects will ultimately determine your results.
