Canada’s NOC System Wasn’t Built for Immigration. So Why Does Immigration Depend on it?

The AI strategy promises to use the Global Talent Stream to “accelerate entry and onboarding of highly-skilled AI workers.”

That raises the question: who counts as an AI worker?

Canada’s immigration system relies on the National Occupational Classification (NOC) system to determine eligibility for immigration programs. Immigration, Refugees and Citizenship Canada (IRCC) uses the NOC system to classify occupations for immigration programs, like the skilled worker classification needed to qualify for Express Entry.

Meanwhile, Employment and Social Development Canada (ESDC) uses NOC codes to determine priorities and wage requirements for Labour Market Impact Assessments (LMIAs) and work permits.

NOC codes are used across a broad range of immigration programs, managed by multiple government departments; many of the same government departments committed to implementing the new “AI for All” strategy. But – when we looked through the NOC, we found only two occupations that explicitly reference artificial intelligence:

• NOC 21211 (Data scientists): Includes the job titles Artificial intelligence (AI) analyst, Artificial intelligence (AI) consultant, and Artificial intelligence (AI) designer.
• NOC 21232 (Software developers and programmers): Includes Artificial intelligence programmer.

Beyond these two NOC codes, no other positions list AI-related job titles.

So, is the NOC system failing to keep up with the technological changes to the labour market? Short answer: yes.

But – after reviewing Statistics Canada’s recent consultation report on upcoming 2026 updates to NOC codes, it’s clear that NOC codes have some serious constraints that limit their ability to be updated quickly. Though, as we’ll unpack in this article, these constraints are in place for good reason!

The NOC system was not built for immigration. It has a different purpose that makes it challenging to respond quickly to the needs of immigration stakeholders, but that is essential to preserving the integrity of the system.

The NOC was Created for Statistics, Not Immigration

Most newcomers first encounter NOC codes while researching Express Entry, Provincial Nominee Programs, or work permits. It is easy to assume that the NOC was created specifically for immigration. But – that’s not the case.

The team behind the NOC classification system makes it very clear that:

—the NOC is designed primarily for statistical purposes. Although there can be various uses of the NOC for non-statistical purposes (e.g., for administrative, regulatory, or policy functions), the requirements of government agencies or private users that choose to use the NOC for non-statistical purposes are responsible for such use of the classification.

What does this mean for the average person navigating the immigration system?

Well, it means the NOC team isn’t asking whether a specific NOC code makes sense to an immigration program or a would-be newcomer. Their objective is to create a stable and reliable system for collecting labour market data.

Furthermore, the NOC system has other restraints that prevent it from being updated without extensive work. NOC classifications must adhere to international principles and must be based on reliable data. Updating such a system is complex and can’t be done on a whim, but the restraints also help the system maintain its integrity.

That being said, the slow-moving process for NOC updates creates tension for immigrants who have no choice but to rely on an imperfect classification system to make decisions about their eligibility.

How the NOC is Trying to Adapt

The NOC system goes through major revisions every ten years and smaller revisions every five years. Traditionally, the five-year reviews have focused on what Statistics Canada calls “virtual” changes. These are smaller changes such as updating job titles, employment requirements, or occupational descriptions.

Meanwhile, the ten-year revisions focus on both “virtual” changes and larger “real” changes, which may include the creation of new unit groups, transfers of job titles and occupations, and other bigger modifications. In 2021, the NOC code system underwent a revision which replaced former “Skill Levels” with the current “TEER” system. This was considered a major or “real” change.

In 2026, the NOC code will be undergoing a revision. This was meant to be a five-year revision, only incorporating smaller changes. However, an NOC report indicates that due to “exceptional” circumstances, this five-year revision will be larger than normal, including both “virtual” and “real” changes.

The NOC code includes 516 total unit groups, of which 165 of them will be affected by changes. Of those affected unit groups, 18 will undergo real structural changes, including the creation of new unit groups, transfers between occupations, and other modifications to the classification itself.

The remaining 147 unit groups will receive virtual updates, including revised titles, new example job titles, updated duties, and changes to employment requirements.

The exact details of the updates have not yet been made public, but the new changes are expected to go into effect in December, 2026. It is possible that among the 165 unit groups being updated, some of these updates may account for changes in the AI landscape over the past several years. However, this is not guaranteed.

Updating an NOC unit group is not something Statistics Canada does lightly. The report acknowledges that some proposed changes couldn’t be implemented due to a lack of data to support the changes. With the rapid rate of AI-related changes, it’s possible that there’s not enough data yet to support certain AI-related NOC updates.

What Happens When Your Job Doesn’t Fit Neatly into an NOC?

Many immigration applicants continue to face uncertainty about how to select an NOC code when their job title isn’t explicitly listed in the NOC system, or when their job duties don’t appear, or seem to apply to multiple NOC codes. This is especially true for individuals working in rapidly evolving tech roles, like those in the AI industry.

Let’s look at an example from an immigration hopeful.

Example: AI Trainers

One worker on Reddit describes their role as an “AI Trainer”:

Which NOC code in EE is for an AI Trainer Role
by
u/Routine_Security_375 in
canadaexpressentry

The Express Entry hopeful explains that their role does not involve machine learning development or traditional data entry work. Instead, they review and refine model-generated outputs across a range of subjects.

The Redditor suggests three possible NOC codes: Data Scientists (21211), Database Analysts and Data Administrators (21223), or Information Systems Specialists (21222).

However, the duties and responsibilities listed in the Reddit post suggest that the role encompasses a good deal of testing the model. Another possible NOC code could be Information Systems Testing Technicians (22222) which includes duties related to testing software.

Most notably, this Reddit post contains insufficient information to choose an NOC code with complete confidence. Before selecting an NOC code, an immigration consultant would ask:

1. What is your level of education? How does that correspond to the training requirements for your possible NOC selections?
2. List the exact duties and responsibilities you perform in your role. Which NOC code do these duties resemble most closely? Will your employment reference letters back up these claims?

With this information, it would be easier to make a defined choice, even though “AI Trainer” is not a job title in the current NOC system. Similar issues and decisions face many workers in new AI roles and those in hybrid positions combining software engineering and data science.

What Immigration Applicants Should Know

For immigration purposes, an important takeaway here is that job titles alone are not enough to determine the correct NOC code. More important than the job title are the job duties: IRCC expects applicants to select the occupation that best reflects their primary duties and responsibilities.

Supporting documents, particularly employment reference letters, must demonstrate that the applicant’s work aligns with the duties described in the chosen NOC. Reference letters should demonstrate that the worker performed (a) the actions described in the lead statement for the occupation, and (b) at least a substantial number of the main duties of the occupation including all the essential duties.

This is extremely important for workers in emerging fields where job titles may not yet appear within the classification. An applicant working as an AI Trainer or AI Prompt Engineer can still qualify under an existing NOC so long as their duties closely match their selected occupation’s description.

Workers who are uncertain which NOC best reflects their experience should seek advice from a regulated Canadian immigration consultant before applying. Selecting the wrong NOC code can have serious implications, including the rejection of an immigration application. You can book a consultation with our immigration consultant here:

A Growing Challenge for Immigration Programs

The upcoming 2026 NOC update shows that Statistics Canada is continuing to revise the system in response to changing occupations and labour market conditions. At the same time, the consultation report makes clear that the NOC is not intended to function primarily as an immigration tool.

The NOC system is a statistical tool first. Its priority will always be to adhere to strict statistical principles, regardless of the pressure the NOC team might feel from immigration stakeholders advocating for faster changes.

As artificial intelligence reshapes occupations and creates new hybrid roles, immigration candidates may increasingly find themselves relying on a classification system built to provide stability and consistency, rather than fast-moving updates. This inflexibility may also make it challenging to Canada to attract the first-movers in new, emerging fields like artificial intelligence.

For most occupations, the current NOC approach works well. But – for workers whose jobs combine elements of data science, software development, and artificial intelligence, fitting their work into a single occupational category may remain a complicated step of the Canadian immigration process.