BZ (Trans): No signs of white-collar and IT job cuts yet

Below is Dolphin Research's transcript of $Kanzhun(BZ.US) 1Q26 earnings call. For our earnings take, see 'BOSS Zhipin: The once niche recruiter has fully ripened'.

I. Key takeaways

1. Q2 guidance: total revenue of RMB 2.38bn–2.42bn, +13.2%–15.1% YoY, well above Q1's +7.6%. Management expects full-year revenue growth to outpace Q1, with full-year cash receipts growing at least double digits YoY.

2. Shareholder returns: YTD buybacks exceeded US$200mn, ~3% of shares outstanding. Since 2022, cumulative buybacks are ~10% of shares; management reiterated the three-year commitment to annual shareholder returns (buybacks+dividends) of no less than 50% of prior-year Adj. net profit, to be executed on an ongoing basis.

3. Margin outlook: factoring ongoing AI investment, World Cup title sponsorship, and dilution from new biz expansion, full-year Adj. OPM is expected to tick up modestly. The core business still has meaningful operating leverage to lift margins further.

4. SBC: Q1 SBC fell 24% YoY to RMB 181mn, 9.2% of revenue (-390bps YoY). For the year, SBC is expected to be ~9% of revenue.

5. One-off investment gains: Q1 interest and investment income was RMB 781mn, +422% YoY, mainly from a RMB 640mn fair value (FV) gain related to an investee’s Jan 2026 listing. The associated tax impact was RMB 154mn, plus RMB 60mn Pillar 2 top-up tax, driving a sharp YoY increase in income tax in Q1.

II. Call details

2.1 Management remarks

1) Users and platform scale

1. Over 15mn verified users were added from the start of the year through Apr. Management believes the full-year target of adding over 14mn verified users is achievable.

2. Q1 Avg. MAU was ~60mn, with Mar MAU topping 72mn (+4.6% YoY). Apr MAU was close to Mar levels. Due to a later Chinese New Year in 2026 (Feb 17 vs. Jan 29 in 2025), this year's peak season concentrated in Mar, while both Feb and Mar were peak months in 2025, creating a base effect.

3. Paying corporate customers: LTM to Mar 31, 2026 reached 7.1mn, +10.9% YoY and +4.4% QoQ. Q1 ARPU rose 2% YoY.

2) Industry and user mix trends

1. White-collar mix kept rising: as of Apr 13, about three-quarters of new users YTD (ex-new grads) were white collar, and white-collar-related revenue exceeded 40% of total in Q1. White-collar hiring demand accelerated post-CNY.

2. Software engineer roles: active job postings rose 10.9% YoY in Jan–Apr, above a 9.1% print at US peers. AI-related role revenue on the platform more than doubled YoY, and no broad-based cuts in programmer roles have been observed.

3. Other faster-growing sectors: manufacturing, electronics, telecom, semis, transportation & logistics, urban services, and various professional services.

4. Large-enterprise hiring has clearly rebounded: firms with 1k–10k employees delivered the fastest YoY revenue growth in Q1, followed by 500–1k, contrasting with last quarter's outperformance by micro and small businesses and pointing to a more balanced mix.

3) AI strategy: two theses and four initiatives

Thesis 1: AI brings more opportunity than challenge

After three years of exploration, management believes its market leadership has strengthened. Falling token costs have enabled AI services for over 10mn users on the platform, while pretraining and application work with LLMs has accelerated the development of young internal talent, refreshing the organization and reducing entropy.

Thesis 2: Standalone AI agents cannot breach the two-sided network moat; embedded agents are a tailwind

Job matching is inherently a many-to-many human marketplace, and a 12-year accumulation of two-sided users and data forms the core moat. With AI agents embedded into this ecosystem, Q1 data show a 50% lift in conversion from initial contact to mutual intent, user retention at the highest since 2020, and double-digit percentage gains in average fulfillment effectiveness for corporate users.

Four AI initiatives:

1. AI-powered closed-loop placement services (core): We are convinced the industry's endgame is pay-on-hire, not selling traffic or clicks. In internal tests, 20% of headhunter recommendations are AI-driven, and 'human+agent' productivity is 4x the industry avg. Campus hiring closed-loop services grew revenue over 50% YoY in Q1, and AI-assisted closed-loop services generated ~RMB 50mn in Q1, with the fastest cohorts up over 100% YoY; still small, but accelerating. The company will open up to partner with external specialists in closed-loop recruitment.

2. AI foundational research, focused on small models: continued investment given lower internal costs, tighter business accountability and vertical specialization, rising industry interest, superior efficiency vs. large models in search and recommendation, and currently prohibitive costs of large models.

3. Heavy investment at the application layer: treat AI as a tool to discover and solve problems, with success measured by service to both sides of the marketplace. Teams that use AI to identify and fix issues will be incentivized.

4. AI-driven revenue growth as a natural outcome: AI raises platform efficiency, improving fulfillment, which boosts satisfaction and word of mouth, sustaining revenue growth. Management explicitly prefers '15% per year for the next five years' over '50% this year' for a steadier, lower-risk, more sustainable path.

4) Hong Kong and overseas

1. Hong Kong DAU is ~60k, equal to 1 in 50 of the city's ~3mn workers using the platform daily, and employers can efficiently reach a large pool of active candidates.

2. Overseas strategy: Hong Kong is the key testbed to validate the two-sided model outside the mainland while building a core team for going abroad. Revenue is not the near-term priority; the focus is steady investment to become the most trusted recruiting platform for employers and job seekers in Hong Kong.

2.2 Q&A

Q: Ex-CNY timing, how did the post-peak season and Q2 trend? Which sectors improved most?

A: Mar and Apr are good reflections of underlying demand post-peak. Avg. MAU was ~60mn in Q1, but Mar exceeded 72mn and Apr was close to Mar, with a healthy supply-demand balance and new job postings up 10% YoY, a strong signal that the market remains fast and robust after the peak season.

For 1H and the full year, we expect cash receipts to grow at least double digits YoY, and revenue growth in Q2 and for the year to be above Q1.

Q: Is AI dampening job demand on the platform? If white-collar roles face bigger impact than blue-collar, will you accelerate blue-collar? Any update and feedback on AI-driven closed-loop services?

A: We take AI's impact on jobs seriously and continue to invest in research to reach rigorous, scientific conclusions, which we will share once ready. For now, software engineer roles have not declined; instead, active postings rose 10.9% YoY in Jan–Apr. I need roughly two more quarters to provide a clearer answer.

On AI-driven closed-loop services, this was our fastest-growing set of experiments in Q1, with some cohorts over 100% YoY and others around 50%, though still small in absolute terms at ~RMB 50mn in Q1. We view this as a core strategic track and will keep investing.

Q: Peers said AI meaningfully lifted average revenue per job. How will Kanzhun raise monetization per posting with AI, and can AI help lower-match peers leapfrog?

A: We see three angles. First, create more value for clients before considering price increases; second, China has over 40mn enterprises, more than half of which have never used online recruiting, so the market is still early in the shift from extensive to refined operations and expanding the payer base is a higher priority than raising prices; third, the industry is structurally moving from selling exposure to selling placements, a long journey that we have been pursuing so we can ultimately say 'we placed your hire; pay accordingly.'

We now have 7.1mn paying corporate customers and ~RMB 8bn in annual revenue, implying low avg. spend per customer and ample pricing headroom. But my priority is to grow the payer base, say from 7.1mn to 19.1mn, and then layer on pricing for even greater upside; if my thinking changes, I will update everyone. As for whether weaker-matching peers can catch up or surpass us via AI, based on the past three years I am not particularly worried.

Q: Full-year margin outlook and AI-related S&M/R&D trends? Shareholder return updates? Progress in Hong Kong and overseas?

A: Adj. OPM will not surge to 50%. Considering competition for AI talent with sharply higher pay in key roles, expanding compute leasing and depreciation, World Cup title sponsorship, and dilution from new businesses, our outlook is unchanged from the start of the year: a modest increase in Adj. OPM.

On shareholder returns, we have repurchased over US$200mn YTD, more than 3% of shares outstanding, at a quarterly pace already ahead of our initial plan. Two reasons: the current valuation is attractive, making buybacks an efficient use of capital, and we are confident in the company and want to share that confidence with our employees and investors; we will continue to honor our return commitment.

Regarding Hong Kong, progress has been solid. DAU is ~60k, meaning 1 in 50 workers in Hong Kong uses our platform daily, and employers can efficiently reach many active job seekers; our instant two-sided communication model works well locally. We have two objectives: validate the two-sided platform outside the mainland and build a core team for future expansion overseas; revenue is not the immediate goal, and we remain in a phase of rational investment. My goal is for BOSS Zhipin to become the most trusted recruiting platform in Hong Kong, and we will keep investing toward that goal.

Risk disclosure and statements:Dolphin Research Disclaimer and General Disclosures