How AI Is Reshaping the Job Search for Immigrants in Canada

I was recently interviewed by Canadian Immigrant magazine to share insights on how artificial intelligence is changing the hiring landscape for newcomers in Canada. It was an important conversation about how technology intersects with bias, and how that affects job seekers who are new to the country.

That interview is now published. How AI in hiring affects newcomers: career expert Sweta Regmi explains [and you can read it here.]

In this follow-up piece, I’m building on that interview with additional insights and strategies I’ve developed through my work helping immigrants land six-figure roles in Canada. If you’re navigating an unfamiliar hiring system shaped by AI and algorithmic filters, this extended perspective is for you.

AI and the Immigrant Job Search: What Newcomers Need to Know About Hiring Technology in Canada

1.          How prevalent is the use of AI in the hiring process in Canadian companies, particularly in sectors that newcomers might be entering? Are there certain industries or companies in Canada that are more likely to use AI in their hiring processes.

The use of AI in the hiring process is becoming increasingly prevalent in Canadian companies, especially in sectors that newcomers might be entering. Industries such as customer service, sales, technology, finance, contact centers, retail, healthcare, manufacturing, marketing, legal, education, supply chain, logistics, and government are all adopting AI to streamline their recruitment processes. These sectors often leverage AI tools to handle large volumes of applications, assess both hard and soft skills, and speed up the hiring timeline.

AI-driven tools like one-way video interviews, resume parsing, personality assessments, and chatbots for initial candidate interactions are now standard in many recruitment workflows. Companies in industries like technology, finance, and healthcare, where the demand for talent is high and competition for skilled workers is fierce, are particularly likely to use AI to efficiently sift through candidates and quickly identify those who meet specific job criteria.

Additionally, larger corporations, especially those with a global or national footprint, tend to invest more in AI-driven recruitment tools due to the volume of applicants they receive.

AI Bias in Hiring—How It Affects Newcomers

2.     What are some common forms of bias that AI systems can exhibit in hiring decisions, especially for newcomers to Canada?

AI systems in hiring often exhibit several forms of bias, particularly when assessing newcomers to Canada. One of the most common biases is contrast bias, where AI could compare immigrant candidates to local candidates with Canadian experience or education. This can disadvantage newcomers who may not have a degree from a Canadian institution or local work experience, even though their qualifications might be equally strong.

Another form of bias is related to verbal communication skills, particularly when language proficiency is assessed. For example, AI systems may struggle to accurately assess candidates with accents or whose first language is not English. We see this in everyday AI tools like Siri or Google Assistant, which often fail to understand people with accents, misinterpreting instructions or queries. In hiring, this can translate into AI-driven one-way video interviews misunderstanding verbal responses or incorrectly parsing information, potentially leading to candidates being judged unfairly. If the AI system relies on translating responses, it might misinterpret what the candidate is trying to convey, resulting in a mismatch between the candidate’s actual skills and the evaluation.

Cultural fit bias is another significant issue. AI systems, which often rely on historical performance data, might favor candidates who exhibit characteristics or skills similar to those of previous high performers—typically local candidates. This can lead to cultural bias, where newcomers are unfairly assessed against local cultural standards and communication styles that may not reflect their own background, causing a misalignment in how their soft skills, such as communication or teamwork, are perceived.

Local experience bias: Although it is illegal for employers to outright reject candidates for lacking Canadian experience, they can still exploit legal loopholes. Employers may ask questions that unintentionally disadvantage newcomers, such as, “Do you have experience with this tool?” or “How familiar are you with the local market?” While these questions may seem neutral, they often prioritize local knowledge, which can unfairly disadvantage candidates who haven’t had exposure to Canadian-specific tools or markets. This bias overlooks the transferable skills and qualifications that newcomers bring, potentially excluding them from consideration despite their competence in similar roles.

Additionally, AI can perpetuate data bias due to the lack of sufficient data on immigrant candidates. Since these systems are often trained on historical hiring data, they may not account for the diverse backgrounds and experiences that newcomers bring to the table. This can result in AI systems being less accurate in evaluating candidates who don’t fit the typical mold based on past hiring patterns.

 How AI Tools Unintentionally Disadvantage Newcomers and Racial Minorities

3.     How can AI tools unintentionally disadvantage certain demographic groups, such as newcomers, immigrants, or racial minorities?

AI tools, while designed to streamline hiring processes, can unintentionally disadvantage certain demographic groups, such as newcomers, immigrants, and racial minorities, due to the way they analyze and interpret data.

An applicant tracking system (ATS) may include questions like, “Do you have a driver’s license?” This can disproportionately affect newcomers who might be in the process of obtaining a license or don’t yet own a car, even when the role doesn’t require a driver’s license. The ATS may automatically filter out qualified candidates without giving them the opportunity to provide context or explain their situation.

AI-driven one-way video interviews, which assess verbal responses, non-verbal communication, and appearance, can significantly misinterpret cues from immigrant or racial minority candidates. For example, non-native English speakers often use filler words like “um” or “ah,” which AI may mistakenly associate with a lack of confidence or poor communication skills. This bias overlooks the fact that these fillers may simply reflect speech patterns, not competence. Furthermore, an accent or slight mispronunciation can be wrongly interpreted as a lack of English proficiency, disregarding the rich diversity of language backgrounds that should be valued, not penalized. When a candidate has a strong accent, the AI may struggle to process their responses accurately in text form, distorting the meaning and unfairly impacting their evaluation—especially if the system is primarily trained on native English speakers. This creates an unjust disadvantage for talented candidates who may not conform to narrow linguistic norms.

Even questions about language fluency, such as “Do you speak fluent English/French?” can disadvantage newcomers who may have strong language skills but not native fluency. A more inclusive approach would ask about comfort or proficiency in the language required for the role, rather than focusing on fluency.

 Case Study – Beating AI Bias to Land a Banking Role in 3 Weeks

4.     Could you share some specific examples or case studies of AI bias affecting the hiring of newcomers whom you’ve worked with? If so, how did it impact their job search or application outcomes?

Case Study: Navigating ATS and AI Interviews to Secure a Role at a Top Bank in 3 weeks.

Challenges:

A client came to me after multiple rejections. She took funded employment services, which lacked customization and struggled to move forward in the hiring process. When I started asking questions, a few key issues stood out:

         •        Job Title Mismatch: Her job title from back home didn’t exist in the Canadian job market, which may have confused the ATS and prevented recruiters from reaching out. Since ATS systems prioritize exact title matches, her application might have been filtered out before anyone even saw it.

         •        AI Interview Rejections: She had gone through AI-driven video interviews before but kept getting rejected. The interview was timed, meaning AI likely evaluated her structure, confidence, and delivery based on local knowledge.

Actions Taken

         1.       Resume Optimization:

         •        Researched the closest Canadian equivalent for her job title, ensuring it aligned with industry norms without fabricating anything.

         •        Matched keywords and responsibilities from job descriptions

         2.       AI Interview Coaching (CARL Framework):

         •        Challenge: Identified where her AI interview performance needed improvement.

         •        Action: Built structured responses using CARL (Challenge, Action, Result, Lessons) to ensure clarity and relevance.

         •        Result: Developed compelling, structured answers that AI could process correctly.

         •        Lessons: Improved storytelling, minimized filler words, and adjusted body languages, with the camera to align with AI scoring.

         3.       Mock AI Interviews & Refinement:

         •        Conducted multiple practice sessions to refine delivery.

         •        Worked on tone, articulation, and alignment with job description keywords to ensure AI recognized her expertise.

Results:

         •        Her resume passed the screening, leading to multiple interview invitations.

         •        She finally advanced past AI assessments after previous rejections.

         •        On her next attempt, she successfully landed a role at the bank.

Here is another example of a Canadian experience barrier and how the client landed a 6-figure leadership role despite all the odds against him. His success story was also featured in the news.

 How AI Misinterprets Resumes and International Experience

5. Are newcomers' resumes, experiences, and qualifications accurately represented by AI-powered recruitment systems, or do AI tools tend to overlook or misinterpret their credentials?

The lack of transparency in AI-powered recruitment systems makes it difficult to determine how international experience and qualifications are assessed. We don’t know how data is inputted, processed, or weighted in these systems, leading to potential biases that disadvantage newcomers.

How AI Might Misinterpret Newcomers’ Credentials

1.     Employer Location Bias:

o   If a newcomer worked at a global company like IBM India, their resume might list “IBM, India” as the location. Applicant tracking systems (ATS) may fail to recognize the global brand, mistakenly flagging the employer as an “internationally location” rather than a well-known multinational branch.

2.     Degree & Certification Misinterpretation:

o   AI-driven tools may prioritize local degrees, ranking Canadian or U.S. credentials higher than international ones, even if the content and rigor are comparable.

o   A candidate with a Master’s in Finance from a prestigious university outside of Canada might find their degree ranked lower by the system because it’s not recognized as equivalent to a Canadian degree, despite having the same caliber.

3.     Comparing Newcomers to Local Candidates:

o   Many AI-powered hiring tools compare applicants against a local talent pool, which can disadvantage newcomers whose experience isn’t directly mapped to the Canadian context.

o   Without context, the AI might deem a newcomer’s experience irrelevant simply because it was gained outside of Canada, even if it’s highly applicable.

The Bigger Issue: Lack of Transparency

While Ontario introduced legislation to require employers to disclose their use of AI in hiring, this still doesn’t address the core problem:

·       Candidates remain in the dark about how AI evaluates their experience, credentials, or location.

·       There’s no clear way to challenge or correct AI misinterpretations.

Additional Barrier: Reference Requirements During Application

Some job applications now demand three references, complete with contact information and addresses, right at the application stage. This creates an unnecessary obstacle for many newcomers who may not have an established local network or the privilege of providing references in this format. Typically, references are requested after a conditional offer, making this requirement feel more like a barrier than a necessity. This practice disadvantages international talent by assuming all applicants have the same access to local professional connections. It unfairly limits opportunities for skilled newcomers who are highly qualified but lack Canadian references, further perpetuating biases in the hiring process.

 

 5 Ways Newcomers Can Overcome AI Bias

6.     How Can Newcomers Tailor Their Job Applications to Overcome AI Bias in Canadian Hiring?

To mitigate AI bias, newcomers must strategically align their resumes and applications with Canadian hiring practices. Many of my newcomer clients struggle with job title mismatches, international employer biases, and ATS filtering. Here’s how they can improve their chances:

1. Conduct Labour Market Research & Align Job Titles

         •        International job titles don’t always match Canadian equivalents. Employers and AI systems might not understand unfamiliar titles, leading to automatic rejection.

         •        Example: A “Deputy Manager” in another country might be equivalent to an “Assistant Manager” or “Operations Supervisor” in Canada.

         •        Solution: Instead of completely changing the title, add context by listing it as:

“Deputy Manager (Equivalent to Assistant Manager in Canada)”

         •        This ensures AI and recruiters understand the relevance of the experience.

         •        This isn’t misleading—it’s about making your experience easier to interpret.

2. Avoid Employer Location Bias

         •        ATS systems might filter out international experience because they don’t recognize the employer or prioritize local experience.

         •        Solution:

         •        If you worked at a well-known company internationally, remove the employer’s location (e.g., instead of “IBM India,” just write “IBM”).

         •        Focus on the job role, impact, and responsibilities rather than geography.

3. Optimize for AI & ATS Filters

         •        AI scans resumes for exact keywords from job descriptions and might score.  If your resume lacks these, it may be found in Boolean search.

         •        Solution:

         •        Tailor each resume to include relevant keywords and phrases found in job postings.

         •        Match job description terminology to describe your skills and experience.

4. Practice for AI-Driven Video Interviews

         •        AI might score filler words, non-verbal communication, and accent in video interviews, leading to unfair assessments.

         •        Solution:

         •        Use free tools like LinkedIn Interview Prep to record yourself and identify excessive filler words like “um” and “uh.”

         •        Improve storytelling structure using the CARL method (Challenges, Action, Results, Lessons) to deliver concise, impactful responses.

         •        Time the interview, Maintain eye contact with the camera, as AI often assesses engagement based on gaze direction.

5. Research the Hiring Process & Employer Tools

         •        Some companies disclose the AI tools they use—knowing this helps applicants prepare accordingly.

         •        Solution:

         •        Know what the hard and soft skills for the targeted role are and integrate in answers.  

         •        If a company uses AI-driven video interviews, practice on platforms that mimic them.

7.          What strategies or tools can newcomers use to ensure their resumes or job applications are being fairly assessed by AI systems?

Strategies & Tools for Newcomers to Ensure Fair AI Resume Assessment

To improve their chances of getting past AI filters and ensuring fair assessment, newcomers must take a strategic approach to job applications. Here’s how:

1. Gain Clarity on Hard Transferable Skills & Industry Fit

         •        Identify which skills from back home are transferable to the Canadian job market.

         •        Some industries require specialized expertise, while others value generalist experience—this varies by sector.

         •        Example: If you were a Compliance Associate back home and also handled Anti-Money Laundering (AML), in Canada, these could be two separate roles.

         •        When applying for an AML role, highlight AML-specific experience instead of general compliance tasks.

         •        Avoid listing unrelated skills that may confuse AI systems or dilute your expertise.

2. Research Certification & Job Requirements Before Applying

         •        Some roles require Canadian certifications or licenses.

         •        AI systems often screen out candidates who don’t meet these requirements.

         •        Solution:

         •        Check job descriptions carefully and apply only when you meet the qualifications.

         •        If a certification is required, obtain it first or mention ongoing certification training to increase visibility.

3. Understand ‘Knock-Out’ Questions in ATS Systems

         •        Many ATS (Applicant Tracking Systems) use “knock-out” questions to automatically reject applicants for not meeting the requirement. Take this free resume course.

         •        Example:

         •        A job requiring a CPA designation may ask upfront if you have a CPA. Answering “No” could lead to an automatic rejection.

         •        Solution: Only apply when you meet critical qualifications or clarify ongoing certification efforts in the resume.

4. Prepare for AI-Driven Personality & Skill Assessments

         •        Many employers now use AI personality tests and gamified assessments as part of hiring.

         •        Solution:

         •        Use free online personality assessment tools (e.g., 16Personalities, Big Five, or Predictive Index) to understand how you may be evaluated.

         •        Practice answering behavioral questions, as these are often mirrored in AI testing.

5. Request Accommodations if Needed

         •        Employers must provide reasonable accommodations for interviews, tests or assessments.

         •        Solution:

         •        If you require accommodations (e.g., additional time, alternative testing formats), ask for them in advance.

8.          What advice would you give newcomers to Canada to better navigate the complexities of AI-driven hiring processes in today’s job market?

To successfully navigate the complexities of AI-driven hiring processes in today’s Canadian job market, newcomers must take a proactive and informed approach.

One of the most important steps for newcomers is to stay informed about the latest labour trends and understand the mandatory requirements for the roles you’re applying for. Before submitting any application, it’s crucial to ensure that your resume aligns with industry-specific jargon, job responsibilities, and the expectations of employers. This helps minimize AI biases and ensures your application meets the standards of Canadian hiring practices.

Additionally, I recommend partnering with certified professionals who are deeply familiar with the local job market. Together, we can master Canadian-style resumes, understand the tools used by employers (like AI-driven applicant tracking systems), and prepare for interviews in ways that enhance your visibility and appeal.

What to Know About Accent Bias at Work

(especially for newcomers in customer-facing roles)

• You may encounter customers who are “shopping around for accents” — meaning they prefer to speak to someone who sounds more familiar to them.

• This often happens in call centers or customer service roles, where a customer might say things like, “Can I speak to someone who speaks English?” or “Someone without an accent.”

• It’s important to recognize that this type of bias often comes from customers, not necessarily employers or colleagues.

• Accent bias can show up subtly, but it still affects your confidence, performance, and career growth.

• Being aware of this bias is the first step. You’re not alone, and your accent is not a weakness.

  
  

• Stay calm, not defensive. Bias isn’t your fault. Take a breath and respond professionally.

• Redirect the focus. You can say,

  “I can definitely help you with that.”

  or

  “Let me know what you need, I’m happy to assist.”

  This reinforces your capability without acknowledging the bias directly.

• Don’t apologize for your accent. Your accent is part of who you are. Fluency isn’t about sounding native, it’s about being understood and delivering results.

• Document the interaction (if it crosses a line). If a customer is abusive or makes discriminatory remarks, log the incident and inform your supervisor. Many companies have policies in place to protect staff.

Take a listen to this example from my podcast: The Hidden Bias in Accent Shopping & Customer Services

Helpful Resources:

• Watch my free webinar on resume and job search clarity

• Download Free Resources

Sweta Regmi is the Founder and CEO of Teachndo, a former hiring manager at award-winning companies, and a Certified Career & Résumé Strategist. She’s also the host of the Diaspora’s Career Challenges podcast.

An immigrant herself, Sweta empowers professionals from diverse backgrounds to break barriers and land six-figure careers.

In 2024, Sweta was recognized with the Outstanding Career Leader award—the highest honor from Career Professionals of Canada. She is also a finalist for the Top 25 Canadian Immigrant Awards (2025) and ranks among the Top 10 Career Coaches in Canada. Sweta has been named one of the Top Career Advisors to Follow on LinkedIn and is listed among Canada’s Top Creators.

Her work has been featured on over 100 media platforms, including CBC National, CTV National, Global National, CNBC, The Wall Street Journal, Forbes, HuffPost, The Globe and Mail, LinkedIn News, and Indeed.

Sweta is also the Amazon Bestselling Author of 21 Resilient Women: Stories of Courage, Growth, and Transformation, praised by Canadian libraries, ministers, and MPs. She has received three consecutive nominations (2022–2024) for the RBC Canadian Women Entrepreneur Awards by Women of Influence.

To date, Sweta has helped over 500 career professionals worldwide secure roles at top organizations, including Amazon, Deloitte, IBM, Accenture, Canadian banks, and the Government of Canada.