When reports emerged that McKinsey has begun mandating the use of its internal AI tools during select final-round interviews, it sounded like a dramatic shift. But for many recruiters and hiring experts, the move was less a surprise and more a confirmation of what has been quietly unfolding across industries.
From consulting and tech to media, design, and operations, AI is no longer treated as a specialist skill. Increasingly, it is being viewed the same way recruiters once viewed Excel, PowerPoint, or email — something you are simply expected to know.
“AI has become central to the way all consulting and service businesses are becoming heavily AI integrated,” says Ankur Agrawal, Founder and CEO of LHR, an executive search firm that works closely with top consulting candidates.
“And it’s just not possible to not have AI fluency and be able to deliver or face clients anymore,” he adds.
THE RISE OF THE ‘HIDDEN’ HIRING FILTER
One of the biggest concerns around AI-led hiring is transparency. Many candidates say they are being evaluated on AI use without being told upfront that it matters.
Agrawal acknowledges this gap. “Many firms now test AI use in interviews secretly but not all list it as a hard requirement in job descriptions,” he says.
“For me, the real issue isn’t that companies are testing for it; it’s that many candidates haven’t recognised this shift still,” he adds.
At the same time, he believes clarity would benefit everyone. “Job descriptions should explicitly state when AI proficiency will be evaluated, just as we mention strong PowerPoint skills or proficiency in CRM tools. Transparency serves both parties better,” he says.
From the recruiter side, Bishal Guha Mallick, Head of AI Operations at Internshala, says the reality is often more messy than deliberate.
“Often, we see companies write ‘Needs AI fluency,’ but when we speak to them, they simply mean the candidate should be comfortable using tools like ChatGPT or Perplexity,” he explains. “Recruiters are still adapting and figuring out specific requirements with hiring managers.”
He adds that for clearly defined technical roles, expectations are usually stated upfront. “For technical roles — like a product designer needing GenAI for image and video generation — they tell candidates upfront. So I’m not sure about a hidden filter; it’s more like a test of efficiency.”
IS AI OPTIONAL OR EFFECTIVELY MANDATORY?
Most employers insist AI is just a tool, not a replacement. Yet, candidates who hesitate to use it are increasingly being filtered out. That contradiction sits at the heart of today’s hiring debate.
“I think the framing needs to be relooked at,” says Agrawal. “AI isn’t replacing the person; it’s amplifying their output. Much like Word would do over using a typewriter.”
He is blunt about the consequences of opting out. “A candidate who is refusing to use AI is creating an output gap. That will have consequences.”
Agrawal uses a vivid analogy to explain the shift. “This is much like the difference between a woodcutter still using an axe, versus one using a power saw. Companies aren’t coercing; they’re simply choosing candidates who understand leverage over those who don’t.”
Mallick echoes that view from a hiring platform perspective. “Hesitation to use AI is often viewed as a lack of adaptability,” he says. “It becomes coercion only if the tool adds no value. But right now, AI is becoming the standard for modern productivity.”
He adds that recruiters read resistance as a mindset issue rather than a skill gap. “If a candidate refuses to use a tool that clearly makes them faster, it signals a mindset issue. Employers are looking for people willing to adapt to new ways of working.”
WHAT INTERVIEWS ARE ACTUALLY TESTING NOW
As more interviews include live AI usage — whether through case studies, take-home tasks, or simulations — concerns around fairness and tool access have grown.
Agrawal believes the distinction lies in how AI is evaluated. “Smart recruiters test thinking with AI, not tool familiarity,” he says. “I’d evaluate: Does the candidate know what question to ask? Can they validate AI output critically? Do they iterate effectively?”
He agrees that access must be standardised. “Companies should provide equal access during assessments, just as they give everyone the same case study. Testing on premium tools without access is indeed measuring privilege, not capability.”
Mallick, however, argues that AI has actually flattened the field.
“Unlike expensive software of the past, the most capable AI tools have free versions accessible to anyone with the internet,” he says, pointing to ChatGPT, Perplexity, and Google AI Studio. “The real differentiator now is not financial privilege, but curiosity and agency.”
WHO SHOULD BE UPSKILLING, AND WHEN?
Perhaps the most uncomfortable question is about responsibility. If AI literacy is now essential for employability, who should bear the burden of learning?
“Both must share responsibility, but the weight differs by seniority,” says Agrawal. “For entry-level roles, employers should invest in training; it’s talent development.”
But at senior levels, expectations are unforgiving. “For mid-to-senior positions, candidates must arrive AI-literate. A 50 LPA executive who hasn’t explored how AI impacts their function isn’t demonstrating the learning agility that role demands.”
He adds a blunt reminder: “Ultimately, it’s the candidate who has to take ownership. They have only one career, whereas an organisation will have multiple employees.”
Mallick agrees. “The basics of upskilling are always on the candidate,” he says. “It’s risky for a job seeker to wait for an employer to teach them these fundamentals because they might not even get past the resume screen.”
THE GEN Z ADVANTAGE, AND THE SENIOR STRUGGLE
A striking pattern recruiters are noticing is generational.
“There’s a strange dichotomy,” Agrawal observes. “Gen Z is exceedingly comfortable leveraging AI and is often able to out-deliver more senior people, just because they’ve been playing with AI from day one.”
In contrast, he says, experienced professionals often approach AI too mechanically. “They want to learn it like a tool and struggle, because they’re not spending enough time swimming with AI.”
SO, WHERE DOES THIS LEAVE CANDIDATES?
The message from recruiters is clear: AI skills are no longer about standing out. They are about staying in the game.
What began as an internal interview experiment at firms like McKinsey now reflects a much larger reset in how employability is defined. The question for job seekers is no longer whether AI belongs in their workflow, but how long they can afford to ignore it.