Zhao Ming Joins Afari Technology as Co-Chairman to Push Faster AI Commercialization
Chongqing Afari Technology has nominated former Honor CEO Zhao Ming to its board as co-chairman. The nomination has cleared the board's nomination committee and will go to the first extraordinary shareholders meeting of 2026. His term will align with the company's sixth board.
The move backs Afari's "AI+" strategic shift-especially its "AI+Vehicles" focus spanning intelligent driving and intelligent cockpit solutions. In short: Afari is doubling down on turning proven tech into repeatable, profitable products.
Why this matters
- Afari has strong technical assets but limited large-scale AI profitability. Zhao brings commercial sharpness to convert pilots into predictable revenue.
- Automotive AI needs speed, supply chain discipline, and OEM-grade reliability. Zhao's background suggests tighter execution on these fronts.
Who is Zhao Ming
- Former CEO of Honor; led early AI initiatives and steered the brand through market and organizational shifts.
- 25+ years in global technology management across R&D, product lines, marketing, and international roles.
- Master's degree in Mobile Communications and Electronic Systems, Shanghai Jiao Tong University.
- Quote from Sept 2025: "I am looking for something that excites me, and that is worth another ten years or more of commitment."
Afari's current position
Rebranded in 2024, Afari is led by chairman Yin Qi (co-founder of Megvii) and co-CEO Wang Jun (former president of Huawei's automotive business). The management bench blends deep tech and auto experience.
In the first three quarters of 2025, revenue reached RMB 6.946 billion, up 44.27% year-on-year. Net profit attributable to the parent was RMB 53.28 million, up 33.37%, with most profits still coming from traditional manufacturing.
What Zhao is expected to drive
- Faster productization: lock scope, reduce feature creep, and move from bespoke projects to configurable platforms for intelligent driving and cockpit.
- Go-to-market rigor: tiered pricing, reference architectures, and multi-OEM deployment playbooks.
- Unit economics: standardize hardware BOM, improve inference efficiency, and push recurring software and maintenance revenue.
- Operational cadence: quarterly commercialization OKRs tied to pipeline, conversion rate, deployment cycle time, and post-launch reliability.
Strategic priorities for the next 12 months
- Win "lighthouse" programs with leading OEMs (e.g., deepen work with Geely) and secure 2-3 multi-year platform deals.
- Ship standardized AI stacks for L2+/L3 features and a modular cockpit OS with clear upgrade paths.
- Shorten deployment lead time by 30-40% through repeatable integration kits and validation pipelines.
- Improve gross margin via model compression, silicon optimization, and SKU simplification.
- Tighten post-sale SLAs and over-the-air update reliability to lift renewal and attach rates.
Risks and counters
- Price pressure from OEMs: protect margin with tiered software licenses, data services, and bundled support.
- Feature sprawl: enforce product councils and a "no custom unless it scales" rule.
- Regulatory shifts: maintain pre-cert test suites and compliance checkpoints inside release gates.
- Supply constraints: dual-source key components and pre-book capacity for flagship programs.
What to watch next
- Shareholder vote outcome and formal onboarding timeline.
- New commercial KPIs disclosed in earnings or investor materials (win rates, deployment cycle time, software mix).
- Announcements of multi-OEM platform adoptions and recurring revenue growth.
Signals from the market
A recent nighttime drone show in Chongqing displayed the Afari logo-a public hint at confidence and momentum. Against rising competition in vehicle intelligence, visible signals matter, but execution will decide the scoreboard.
Practical actions for executives
- OEM leaders: request a standardized integration roadmap, performance guarantees, and a 24-month OTA upgrade plan before selection.
- Suppliers and partners: align on shared test data, validation criteria, and a common telemetry format to shorten integration loops.
- Afari's leadership: publish a commercialization dashboard-bookings, deployments, software ARR, and post-launch reliability-to focus the organization.
Bottom line
Afari has the tech foundation. Zhao adds the commercial engine. If the team lands platform deals, improves unit economics, and keeps deployments on schedule, AI revenue can scale beyond pilots and one-offs.
Related resources
- For leaders building in-house AI capability, see curated course tracks by role at Complete AI Training.
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