Opening: The 2026 Spring Hiring Season — A Silent Reshuffling
The 2026 spring hiring season is already halfway through. If you've been sending out resumes, you've probably noticed the stark divide — some people land 3 offers in a week, while others send 200 applications into the void.
Let's start with the numbers:
| Metric | 2025 Spring | 2026 Spring | Change |
|---|---|---|---|
| PM job applications | ~3.8M submissions | ~4.2M submissions | ↑ 10.5% |
| Ops job applications | ~5.1M submissions | ~4.8M submissions | ↓ 5.9% |
| Average PM competition ratio | 1:68 | 1:85 | More competitive |
| AI PM competition ratio | 1:42 | 1:55 | Demand up, but supply faster |
| Fresh grad average offer rate | 8.2% | 6.7% | ↓ 1.5 percentage points |
| Average salary increase for PM job-hoppers | 18% | 22% | ↑ 4 percentage points |
Data sources: Aggregated from Maimai, Lagou, and Boss Zhipin 2026 Q1 industry reports.
One-line summary: Positions haven't decreased, but the bar for "good positions" has risen significantly. AI is redefining what makes a "good PM" and a "good ops professional."
1. The Real Impact of AI on PM and Ops Roles
What Work Is Being Replaced?
This isn't fear-mongering. In 2026, the following tasks have been dramatically compressed by AI tools:
- PRD writing: GPT-4o + internal knowledge bases cut a standard PRD from 3 days to 2 hours
- Competitive analysis reports: AI crawlers + auto-analysis have taken over junior analyst work
- Weekly/monthly data reports: BI tools + AI auto-generation mean ops no longer manually pull data
- Basic copywriting: AIGC tools batch-generate social media copy, product descriptions, and push notifications
- User feedback processing: NLP tools auto-classify, extract keywords, and generate summaries
- Prototype drafts: AI generates low-fidelity prototypes directly from requirement descriptions
What Skills Are Worth More Now?
AI replaces "hands," not "brains." These capabilities command a clear premium in 2026:
- AI product design ability: PMs who can design prompts, define AI interaction flows, and evaluate model performance earn 30%+ salary premiums
- Business judgment: Deciding "what to build" and "what not to build" — this is CEO-level thinking
- Cross-team leadership: Coordinating engineering, design, algorithms, and business teams — AI can't do this
- Deep user insight: Not reading dashboards, but truly understanding what users haven't articulated
- Domain expertise: Deep knowledge in healthcare, finance, education, and other verticals that AI can't quickly learn
A Harsh Reality
In 2026 spring hiring at major tech companies, headcount for pure execution-type PM and ops roles dropped ~25% YoY. Meanwhile, strategy and AI-focused roles grew by 40%+. The market isn't shrinking — it's bifurcating.
2. The 5 Hottest Directions in 2026
1. AI Product Manager
Heat Index: ⭐⭐⭐⭐⭐
Large model deployment has entered deep waters, and every company needs people who can turn AI capabilities into products. AI PMs are no longer "PMs who know a bit of tech" — they need to genuinely understand model capability boundaries and design AI-native interactions.
Core requirements: Understanding Transformer architecture principles, prompt writing, evaluation system design, and 0-to-1 AI product experience.
2. Growth Product Manager
Heat Index: ⭐⭐⭐⭐⭐
With economic uncertainty, companies are increasingly cautious about "buying growth" and hungry for Product-Led Growth (PLG). Growth PMs need to understand product, data, and monetization simultaneously.
Core requirements: A/B testing frameworks, funnel analysis, LTV modeling, and growth experiment design.
3. Global/Cross-Border Operations
Heat Index: ⭐⭐⭐⭐
TikTok, Temu, SHEIN, miHoYo… China's internet growth is overseas. Global ops isn't just "translation + localization" — it requires understanding user behavior and business environments across different markets.
Core requirements: English/additional language skills, cross-cultural communication, overseas social media operations, and localization strategy.
4. Data Operations
Heat Index: ⭐⭐⭐⭐
Data-driven has evolved from a buzzword to a baseline skill. In 2026, ops professionals who can't write SQL struggle to get offers at major companies. Data ops has been upgraded from "the person who pulls data" to "the person who drives business decisions with data."
Core requirements: SQL/Python, BI tools, experiment design, and business acumen.
5. AIGC Operations
Heat Index: ⭐⭐⭐⭐
This is a brand-new direction emerging in 2026. As companies launch AI features, they need dedicated people to manage AI-generated content quality, maintain prompt templates, and optimize AI output.
Core requirements: Prompt Engineering, content quality evaluation, AI toolchain proficiency, and user feedback loops.
3. Salary Trends by Direction
The following data is based on median salaries in tier-1 cities (Beijing, Shanghai, Guangzhou, Shenzhen, Hangzhou), in 10K RMB/year.
| Direction | Fresh Grad (0-1yr) | Junior (1-3yr) | Mid-level (3-5yr) | Senior (5yr+) | YoY Change |
|---|---|---|---|---|---|
| AI PM | 25-35 | 35-55 | 55-80 | 80-130 | ↑ 15-20% |
| Growth PM | 20-28 | 30-45 | 45-70 | 70-110 | ↑ 10-15% |
| Global Ops | 18-25 | 25-40 | 40-60 | 60-100 | ↑ 12-18% |
| Data Ops | 18-25 | 25-38 | 38-55 | 55-85 | ↑ 8-12% |
| AIGC Ops | 20-28 | 28-42 | 42-60 | 60-90 | ↑ 15-20% (new) |
| Traditional E-com PM | 18-24 | 24-35 | 35-50 | 50-75 | → Flat |
| Social Media Ops | 12-18 | 18-28 | 28-40 | 40-60 | ↓ 3-5% |
| Content/User Ops | 12-16 | 16-25 | 25-38 | 38-55 | → Flat or slight decline |
Key finding: AI-related salary growth is 3-5x that of traditional directions. With the same 3 years of experience, an AI PM earns 60-80% more than a traditional ops professional.
4. Hiring Changes: Big Tech vs Mid-Size vs Startups
Big Tech (ByteDance, Alibaba, Tencent, Baidu, Meituan, etc.)
- Total headcount has recovered to 70-80% of 2021 levels, but with massive structural shifts
- AI-related roles account for 50%+ of new headcount
- Candidate requirements have clearly risen: experience alone isn't enough — AI tool proficiency is expected
- Campus recruiting values internship quality over quantity — "filler" internships are essentially useless
- Experienced hiring favors "T-shaped talent": deep expertise in one area + AI capabilities
Mid-Size Companies (Global companies, vertical leaders)
- Global-focused mid-size companies (Temu, SHEIN, miHoYo overseas) represent the biggest growth market in 2026
- AI startups (Moonshot AI, MiniMax, Zhipu, etc.) offer compensation packages that sometimes exceed big tech
- Mid-size companies value "getting things done" — shorter interview processes, faster decisions
- Ideal for candidates who want rapid growth and are willing to take on more responsibility
Startups (Series A-B)
- AI-track startups are still hiring aggressively, but survival rates need attention
- Base salary may be lower, but equity/options offer upside potential
- Best for high risk-tolerance individuals who want 0-to-1 experience
- Focus on companies backed by reputable VCs
5. Different Strategies: Campus Recruiting vs Experienced Hiring
Campus Recruiting Survival Guide
Core principle: Prepare early, build deep, apply wide.
- Internships are the most important door-opener: 90%+ of big tech PM campus offers go to candidates with relevant internship experience
- Choosing the right first internship matters more than choosing the right first job: AI-direction internship experience is hard currency in 2026
- Don't only target big tech: Mid-size companies have higher intern-to-full-time conversion rates and offer more hands-on project experience
- Portfolio > resume descriptions: A complete product analysis report or a real growth experiment is worth more than 10 resume bullet points
- Early-bird batches are the biggest advantage: July-August early batches are 30-40% less competitive than regular batches — don't miss them
Experienced Hiring Breakthrough Strategy
Core principle: Find your positioning, build your moat, be proactive.
- Define your "one-sentence label": Are you "the PM who grew a 10M DAU product" or "the PM with 3 years of 0-to-1 AI product experience"?
- Best window for career pivots: The AI PM talent gap is still large in 2026 — it's not too late to switch
- Referrals > mass applications: 70%+ of quality experienced-hire offers come through referral channels
- Personal brand is a long-term asset: Consistently publish professional content on Zhihu, WeChat Official Accounts, or Jike — recruiters will find you
- Don't undersell yourself in negotiations: 30% salary increases for AI-direction job changes are the norm — don't be scared by "tough market" narratives
6. Must-Have Skills for 2026
1. Prompt Engineering
"Knowing how to use ChatGPT" isn't enough. In 2026, PMs and ops professionals need to:
- Write structured prompts that control AI output quality
- Understand techniques like few-shot and chain-of-thought prompting
- Design and iteratively optimize prompt templates
- Know the capability boundaries of different models (GPT-4o vs Claude vs domestic LLMs)
2. AI Tool Stack
These tools have become standard equipment for PMs and ops in 2026:
- AI Writing: Claude, GPT-4o, Kimi (for long-context scenarios)
- AI Design: Midjourney, DALL-E 3, Jimeng
- AI Data Analysis: ChatGPT Code Interpreter, Tongyi Qianwen data analysis
- AI Prototyping: v0.dev, Galileo AI
- AI Coding: Cursor, GitHub Copilot (yes, PMs need these too)
3. Data Analysis Fundamentals
- SQL: Non-negotiable. PMs who can't write SQL in 2026 essentially can't get big tech offers
- Basic Python: You don't need to write algorithms, but you should be able to do data cleaning and visualization
- BI Tools: Be proficient in at least one of Tableau, Metabase, Shence, etc.
- Experiment Design: Statistical foundations of A/B testing, sample size calculation, significance testing
7. Job Search Timeline Planning
Campus Recruiting Timeline
| Timing | Action | Priority |
|---|---|---|
| Junior Fall (Sep-Dec) | Find first internship, build foundational experience | ⭐⭐⭐⭐ |
| Junior Spring (Jan-Jun) | Target big tech summer internships, aim for return offers | ⭐⭐⭐⭐⭐ |
| Senior Summer (Jul-Aug) | Join fall early-bird batches, secure safety offers | ⭐⭐⭐⭐⭐ |
| Senior Fall (Sep-Oct) | Regular fall recruiting, apply broadly | ⭐⭐⭐⭐ |
| Senior Spring (Mar-May) | Spring supplemental recruiting, last chance | ⭐⭐⭐ |
Experienced Hiring Timeline
| Timing | Action | Notes |
|---|---|---|
| Jan-Feb | Update resume, organize project stories | Preparation period around Chinese New Year |
| Mar-Apr | Peak hiring season, interview intensively | Best job-switching window of the year |
| May-Jun | Evaluate offers, make decisions | Don't rush to accept the first offer |
| Sep-Oct | Second wave of opportunities | Good for those who didn't move in H1 |
| Year-round | Maintain network, keep learning | Referral opportunities can appear anytime |
8. Three Real Cases
Case 1: Liberal Arts Grad Pivots to AI PM, Lands ByteDance Offer in 6 Months
Background: Lin, a master's student in Chinese Literature from a top-tier university, had no technical background. During 2025 graduation, she applied to 50+ companies and only received 2 traditional ops offers.
Turning point: In the second half of 2025, she spent 3 months systematically studying AI product knowledge — completed Andrew Ng's Prompt Engineering course, built an AI writing assistant MVP using Cursor, and published 20 AI product analysis articles on Jike.
Result: During 2026 spring recruiting, she reapplied targeting "AI Product Manager" roles and received offers from ByteDance AI Lab and Moonshot AI. She joined ByteDance at a salary 60% higher than her previous ops offers.
Key actions: Learn AI fundamentals → Build a portfolio piece → Establish personal brand → Apply strategically.
Case 2: Traditional E-commerce Ops Pivots to Growth PM, Doubles Salary
Background: Jie, with 3 years of e-commerce ops experience at a mid-size company managing store operations, earning 250K RMB/year, felt he'd hit a career ceiling.
Turning point: He spent his spare time learning SQL and Python, then proactively took on a user growth experiment project internally. In 3 months, he improved new user Day-1 retention from 32% to 41%. He wrote a detailed case study about this project and published it on Zhihu.
Result: The article was spotted by an HR at Meituan, who proactively reached out for a Growth PM interview. He ultimately received an offer, with his annual salary jumping from 250K to 520K RMB.
Key actions: Fill skill gaps → Create growth cases in current role → Content output for visibility → Passively receive opportunities.
Case 3: Fresh Grad Chooses AI Startup Over Big Tech
Background: Zhou, a CS undergraduate from a 211 university, received offers from both Tencent and an AI startup (Series B, led by Sequoia). Tencent offered a backend PM role; the AI company offered an AI PM role on their core product.
Decision: He chose the AI startup. His reasoning: growth potential as a backend PM at big tech was limited, while the AI startup would let him build an AI product from 0 to 1 — experience that would be extremely scarce in the next 3-5 years.
Result: Six months after joining, the AI feature he led launched and reached 500K DAU. This experience built his industry reputation, and recruiters have already started reaching out.
Key insight: For your first job, choosing "growth velocity" over "brand prestige" may be the smarter play during the AI wave.
9. Action Checklist: 5 Things to Start Doing Right Now
Whether you're a student or a working professional, start these 5 things immediately:
1. Spend 30 minutes daily using AI tools
Not casual chatting — use AI tools to complete an actual task: write a competitive analysis, create a data visualization, generate a PRD. Make AI a work habit.
2. Learn SQL — start now
If you don't know SQL yet, this is the highest-ROI skill investment you can make. Use SQLZoo or LeetCode SQL problems — 2-3 problems per day, and you'll reach interview-ready level in a month.
3. Build your portfolio
Write 3-5 high-quality product analysis or ops case study articles and publish them on Zhihu, WeChat Official Accounts, or Jike. This is more convincing than any resume description.
4. Find your "one-sentence positioning"
Who are you? What are you good at? Which direction do you want to go? Say it in one sentence. If you can't articulate it yourself, interviewers won't remember you either.
5. Start networking and building industry connections
Join PM/ops communities, attend offline events, and proactively connect with industry veterans on Jike and Maimai. 70% of good opportunities come from referrals, not mass applications.
Final Thoughts
The 2026 job market isn't a "winter" or a "recovery" — it's a bifurcation.
AI is reshuffling the PM and ops professions. Those who embrace change, proactively learn, and dare to pivot will find more opportunities than ever before. Those still using 2020 playbooks will find it increasingly difficult.
Choosing the right direction matters more than raw effort — but the effort after choosing matters most.
Want to systematically boost your competitiveness for PM and ops roles? We've prepared comprehensive learning resources and interview question banks:
👉 — Systematic courses covering AI PM, Growth, Global Ops, Data Ops, and more
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Keywords: 2026, product manager, operations, career trends, AI impact, job market, tech careers, industry analysis, AI PM, growth PM, global operations, data operations, AIGC operations