State of Interviewing 2025: How AI Quietly Rewired Tech Interviews

Something changed about interviews in 2025.

The questions sound the same — but the expectations are completely different.

After analyzing over 300,000 interviews and tech job postings, Interview Query found that AI-driven restructuring has reshaped hiring across the industry.

For a quick visual walkthrough of how interviews are evolving, watch the video below:

What you’ll see: recruiters adapting to AI-cheating, candidates needing to reason with models instead of just coding, and how in-person rounds are making a comeback. Now let’s break it down.

1. Layoffs Became an Efficiency Strategy — Not a Collapse

2025 saw 62,000 tech layoffs, including 9,000 at Microsoft, yet hiring didn’t slow down — it evolved.

Companies like Amazon and Apple hired more employees than they laid off. Total tech job openings stabilized around 230,000, up 22% from the 2024 low point.

The reason? Layoffs became a tool for AI-driven restructuring, not survival. Tech firms are optimizing for efficiency and focusing on high-performance, AI-fluent talent.

Key takeaway: Fewer roles, but higher expectations — especially for candidates who can use AI to boost productivity.

2. AI Became the Core of Every Tech Role

By 2025, AI stopped being a niche specialization and became the baseline for every tech role.

From developers to data engineers, professionals are now expected to build with AI — not just code around it.

AI-native roles like AI Engineer, ML Engineer, and Analytics Engineer surged by 240% in early 2025, while traditional software roles declined slightly but remained essential.

The job market didn’t grow — it shifted toward AI builders.

3. Cheating Scandals Broke Trust — And Ghosting Followed

The rise of AI-assisted cheating in 2024 — including hidden prompts, remote “helpers,” and even AI-synced eye-tracking — shattered recruiter trust.

Recruiters, overwhelmed by AI-powered screening tools, responded by ghosting candidates instead of clarifying suspicions.

One candidate shared on Reddit:

“They thought I was cheating and were rude multiple times. I felt insulted — and then got ghosted anyway.”

Platforms like Greenhouse reported that AI automation actually doubled recruiter workloads, worsening candidate experiences instead of improving them.

1. In-Person Interviews Are Back

To counter AI cheating, in-person interviews made a comeback.

In-person rounds rose from 24% in 2022 to 38% in 2025, especially for design and behavioral interviews.

• Google reintroduced onsite interviews to reduce cheating.
• Meta experimented with AI-assisted interviews that evaluate responses dynamically.

As Computerworld noted, “Companies want to see your real thinking process — not ChatGPT’s whisper in your ear.”

2. Fundamentals Got Harder — Not Easier

Despite the rise of AI, Python, SQL, and system design remain the most in-demand skills.

But now, they’re tested within AI-integrated scenarios.

Instead of: “Sort this array.”

You might hear: “How would you design an algorithm that uses an LLM to rank and sort user feedback by sentiment?”

AI and LLM-related interview questions have tripled since 2023. The focus has shifted from Can you code? to Can you reason with the AI that codes with you?

3. Take-Homes Became Real-World Simulations

Take-home assessments didn’t disappear — they evolved into real-world projects.

Microsoft’s 2025 Work Trend Index lists AI fluency as a top hiring priority, reflecting the shift from algorithmic puzzles to practical, problem-solving tasks.

Amanda Richardson, CEO of CoderPad, calls it: “The death of algorithmic take-homes — replaced by project-based ones.”

Candidates are now asked to extend small apps, analyze real datasets, or simulate product scenarios involving AI — not grind through abstract coding puzzles.

2025 interviews don’t test what you know — they test how you think with AI.

Modern candidates operate on two layers:

1. Ground Level: Core technical fluency — Python, SQL, debugging, architecture.
2. Model Level: Reasoning with AI — prompt design, evaluation, and ethical decision-making.

Here’s how interview expectations evolved across major roles:

Role	AI/LLM Mentions (2021 → 2025)	Interview Focus	Prep Focus	Showcase In Interviews	What Recruiters Look For
ML Engineers	8% → 29.5%	Model tuning + infra fluency	Fine-tuning, RAG pipelines, latency optimization	Debug hallucinations, manage drift	Reliability > novelty
Data Engineers	3% → 9.7%	Pipeline resilience + AI readiness	Stream processing, feature stores	Real-time data flows	Make data learnable
Data Scientists	4% → 18.4%	Experimentation + interpretability	A/B tests, bias detection, prompt metrics	Diagnose misleading models	Analytical + ethical clarity
Backend Engineers	6.7% → 13%	Integration + scaling	APIs, caching, inference pipelines	Deploy scalable AI workloads	Throughput + stability
Analysts & BI	3.8% → 15.8%	Storytelling with AI insights	SQL, visualization, model metrics	Translate outputs to business strategy	Context > code

2025 marked a turning point.

Interviews no longer test what you know — they test how you reason, communicate, and adapt in a world where AI already knows everything.

Because in the age of ChatGPT, knowledge is free — judgment isn’t.

By 2026, interviews will merge human clarity with AI precision.

And the most successful candidates won’t compete against AI — they’ll collaborate with it.

If you’re preparing for interviews in 2026, you’ll need more than practice problems — you’ll need a framework for thinking with AI.

Interview Query helps you:

• Explore 9,000+ companies and real interview questions.
• Take AI-powered mock interviews that adapt to your level.
• Learn how to analyze and explain your reasoning like top candidates do.

We don’t just teach you to answer questions — we teach you to think like the engineers companies hire now.