9 Things AI Gets Wrong in Hiring

The One Human Fix That Changes Everything 

AI has revolutionized the hiring process. It screens faster, shortlists quicker, and pulls insights from massive datasets in seconds. But when companies lean too heavily on AI, they risk automating the very thing they say they value most: human potential. 

Here are 9 ways AI misses the mark in hiring, and the one fix that consistently leads to better, more human results. 

1. It Filters Out the Best People for the Wrong Reasons 

AI-powered systems often rely on keyword matching and rigid logic. A Harvard Business School study found that over 10 million “hidden workers” in the U.S. are overlooked because their resumes don’t fit algorithmic criteria. 

Qualified candidates are removed simply for not using the “right” industry terms, despite having the exact experience a role requires. A project leader without the keyword “project management” can easily get filtered out. 

Technology designed to make hiring more efficient often makes it less inclusive and less accurate. 

2. It Assumes Past Equals Potential 

AI is built on historical data. The problem is that hiring based only on the past limits your ability to grow into the future. 

Tools often over-prioritize job titles and experience patterns, favoring traditional career paths. But innovation often comes from those who don’t fit the mold. 

A 2023 Deloitte report highlighted that 81 percent of executives believe future success will depend on workers’ ability to learn and adapt, not their prior job titles. 

3. It Cannot Assess Character 

AI can identify hard skills, but it cannot gauge humility, grit, or integrity. 

When a client says, “We need someone who leads without ego,” they are asking for character traits, not line items. That is why one of the most telling phrases in hiring remains true: 

“You hire people for what they can do. You fire them for who they are.” 

A McKinsey study found that emotional intelligence and soft skills account for up to 90 percent of what sets high performers apart. These are qualities a resume scan will never see. 

4. It Multiplies Bias Instead of Eliminating It 

Bias in AI is not neutral. It reflects the biases in its training data. 

In 2018, Amazon scrapped a recruitment tool after discovering it consistently downgraded resumes with the word“women’s” and favored male-dominated terms. 

A World Economic Forum report warned that unless AI tools are regularly audited, they can perpetuate gender, racial, and age discrimination at scale. 

Bias does not disappear with automation. It just hides better. 

5. It Misinterprets Gaps and Growth 

Career breaks are red flags to many AI systems. Yet for humans, those gaps often represent growth, reflection, and recalibration. 

People take time off for caregiving, grief, illness, education, or transition. When you only look at timeline continuity, you miss the character behind the story. 

A LinkedIn study revealed that 62 percent of employees have taken a break at some point, and almost 70 percent say that a break helped them gain new perspectives or skills. 

6. It Rewards System Gamers Over Genuine Growers 

AI screening has created a cottage industry of optimization tools. Job seekers now use resume bots, auto-apply software, and keyword tools to pass screening filters. 

This rewards candidates who know how to manipulate the system, not necessarily those who will thrive in the role. 

A SHRM report found that nearly one in five candidates exaggerates qualifications or uses AI-generated resume boosters to bypass hiring filters. 

The best candidate may not be the one who knows how to get past your machine. 

7. It Automates Away Empathy 

Automated emails, ghosting, and chatbots have become the norm. Candidates report feeling like they are being processed, not considered. 

The 2024 Greenhouse Candidate Experience Report found that 60 percent of applicants would not recommend a company after a bad hiring experience, even if they wanted the job. 

Lack of human touch damages the employer’s brand, trust, and long-term reputation. People remember how you made them feel, especially when they are at their most vulnerable.  

8. It Cannot Understand Your Culture 

Culture is not a buzzword. It is how decisions get made, how people communicate, and how success is defined. 

AI cannot understand your leadership style, team dynamics, or unspoken norms. It cannot predict how someone will engage with your values. 

According to a Glassdoor survey, 77 percent of job seekers consider a company’s culture before applying. Culture-fit and culture-add are qualitative, not mechanical. 

9. It Misses the Spark 

There are moments in hiring that change everything. A story told with passion. A thoughtful pause before an insightful answer. 

These are the cues of connection, purpose, and potential. AI does not see those moments. 

And yet, they are often the reason we hire someone. Because something in them just felt right. 

So, What’s the Fix? 

High Tech + High Touch 

At Titus Talent Strategies, we believe in partnering with technology, not being ruled by it. 

We use smart tools to inform and support. But we lead with people. 

That means we evaluate character and competency, potential and personality; in short, we look for traits that predict success in the role. We listen between the lines, ask deeper questions, and help clients uncover what their job descriptions often miss (while ensuring we remain EEOC compliant). 

When people stay at the center, hiring becomes transformative. 

The One Fix That Changes Everything? 

Human connection. 

Use AI to sort. But never let it decide for you. Ask the questions no software can. Be curious about the person behind the profile. 

Because the future of hiring will belong to companies that know how to spot potential, not just patterns. 

Let’s connect and design a hiring process that sees people, not just resumes.