Written by: Ruth V. Walker, PhD 

Published June 18, 2024

1. Lack of Personalization

AI often generates generic statements that lack the unique touch needed to stand out. According to a ResumeGo study, personalized resumes receive 30% more callbacks compared to non-personalized ones. Here's an example of a generic professional summary:

Generic Example:

Dedicated and compassionate undergraduate psychology student with a strong foundation in psychological principles and a keen interest in pursuing a career in therapy. Demonstrates excellent interpersonal and communication skills, with a genuine passion for helping individuals improve their mental health and well-being. Committed to continuous learning and professional development, with a goal of obtaining licensure as a therapist to provide evidence-based therapeutic interventions.

The generic example above tells a recruiter or hiring manager that the applicant is an undergraduate student in psychology and is interested in becoming a therapist but lacks personalization and evidence to support the claims made throughout about being dedicated, having a strong foundation in psychological principles, and having excellent interpersonal and communication skills. 

Personalized Example:

Dedicated undergraduate psychology student with over a year of experience mentoring neurodiverse college students through the Mosaic Program at UTC. Played a key role in organizing the 3rd annual Mental Health Wellness Fair as part of Psi Chi, the National Honor Society in Psychology, collaborating with 20+ community partners. My experience as a peer mentor, combined with two years of customer service experience, are evidence of my interpersonal and communication skills, as well as my dedication to supporting and advocating for mental health. Eager to bring my skillset to [COMPANY NAME] as a [ROLE] intern.

In the personalized example, I took the following steps:

1. Removed generic adjectives (e.g., "excellent," "strong").

2. Added in quantifiable metrics and evidence of the applicant's skills (e.g., two years of customer service experience, collaborating with 20+ community partners) rather than just saying they are "excellent."

3. Tailored the professional summary to note the company and role the applicant is applying for.

2. Inability to Accurately Quantify Achievements 

AI struggles to generate specific achievements or metrics without being provided with them. It's crucial to input information about your past experiences and accomplishments. For example, when asking ChatGPT to write a work experience section for a hypothetical job, you should provide quantifiable metrics:

Prompt Without Metrics:

"I worked as a barista for Starbucks. Can you help me create the bullet points for this role that include quantifiable metrics?"

AI Generated Example:

• Provided exceptional customer service to an average of 150+ customers daily.

• Achieved a customer service satisfaction score of 95%.

• Increased daily sales by 10%.

• Trained and mentored five new employees.

• Had a 98% accuracy rate for inventory and supply orders.

• Led to a 20% reduction in health and safety incidents.

These quantifiable metrics provided by ChatGPT are not likely to be accurate or verifiable. In fact, it's unlikely that a large chain restaurant is even maintaining all of these metrics at an individual employee level - which make them a potential red flag for recruiters and hiring managers. Although you could show these metrics to your manager/supervisor if you still have the job to have them help you revise the statistics to be accurate, a better approach is to provide your own metrics to start with - especially because ChatGPT is going to give similar statistics to anyone who has previously worked at Starbucks, making you look just like everyone else when you want to stand out.

AI Prompt With Metrics:

"I worked as a barista at Starbucks. I trained two coworkers. Our store averaged 500 customers a day and was recognized as Store of the Quarter. Can you help me create bullet points for this role?"

This approach ensures more accurate and ethical representation of your achievements. See my previous blog post and/or video on creating quantifiable metrics for more details on how to do this effectively.

3. Overuse of Fluff and Jargon 

AI often uses unnecessary words that add no real value. For example, phrases like "showcasing an ability to seamlessly transition" are overly complex and vague. Follow industry experts like recruiter Sam Struan on LinkedIn for practical advice. For instance, a LinkedIn headline formula could be:

[Years of experience], [Roles or responsibilities], [Organization size and scope], and [A metric related to your field]

If I go back to our Starbuck's barista example, their headline could be: "Two years in customer service, serving 250+ customers daily at an award-winning store." This is factual, personalized, and avoids using any fluff or jargon.

4. Limited Understanding of Context 

AI lacks the nuanced understanding of context that humans with expertise and experience in an industry may have. It may not accurately grasp the specific requirements or cultural nuances of different job markets and industries - particularly if you provide it with minimal input. For example, a past student was recently tailoring her resume and cover letter for a People Analyst role. Since this was a job title in an industry she has not had previous experience in, she copied the entire job description into ChatGPT. Additionally, she copied information from the company website to provide context about the industry. This helped AI provide output and suggestions that contained the appropriate context. However, there is always the possibility that it is missing the mark. I recommend always reviewing and refining AI-generated content, ideally with a proofreader knowledgeable about your field. 

5. Risk of Overselling 

AI is your biggest advocate - it loves to talk you up! This can result in output that oversells your qualifications and includes inaccurate information. This is especially true for current students and new graduates. For instance, claiming a "strong foundation in psychological principles" as an undergraduate or bachelor's degree holder is a little much. Instead, work on taking out adjectives to focus on accurate representations, "Undergraduate psychology student with a foundation in psychological principles." Providing AI with quantifiable metrics and achievements that it can incorporate and build off of can help reduce the risk of overselling. 

Conclusion

Remember, AI should complement your efforts to build your professional documents, not replace them. Use it wisely to maximize your impact when applying for jobs. 

1. Provide Specific Metrics: Always input your achievements and quantifiable metrics rather than having ChatGPT or other AI generate them for you.

2. Review and Refine: Have a knowledgeable proofreader review AI-generated content.

3. Follow Informed Recruiters: Stay updated with tips from recruiters on LinkedIn to make yourself more marketable.

If you have any questions, feel free to leave a comment! 

References and Further Reading

ResumeGo. (2019). Personalized resumes receive 30% more callbacks than non-personalized ones. ResumeGo. Retrieved from https://www.resumego.net/research/personalized-resumes/