'Kingdom Come: Deliverance 2' translator says developers fired him to use AI

Translator Max Hejtmánek says he was fired on March 27, 2026 after being told his Czech-to-English translation role at Warhorse Studios (employed since 2022) would be made “obsolete” as the studio plans to replace translation work with AI effective next month. The action is framed as a cost-saving/efficiency measure and poses creative quality and reputational risks for the developer; it is not expected to materially affect markets or Warhorse’s financials but signals broader AI-driven labor disruption in media and entertainment.

Analysis

The immediate cost saving from swapping human translators for AI is real but small relative to upfront development budgets; the relevant second-order impact is on monetization and IP durability — a 5–10% hit to retention or review scores from poor localization can translate into a 3–8% reduction in lifetime monetization on live-service titles over 6–24 months. That math means publishers will weigh marginal labor savings against a multi-quarter drag on DLC, microtransaction and sequel franchise value rather than treat translation as a fungible line-item.

AI infrastructure vendors (inference chips, cloud GPUs, LLM fine-tuning) capture the direct revenue upside within quarters as studios ramp experimentation, while specialist localization firms and gig translators face secular compression of margins and possible rapid client attrition over 6–18 months. Expect a bifurcation: a handful of platform winners scaling inference and tooling revenue, and a fragmented set of losers forced to pivot to premium human-in-the-loop services or niche languages where models underperform.

Key catalysts that can reverse or accelerate this trend are tangible and near-term: (1) noticeable quality regressions causing review-score declines and pre-order cancellations within weeks–months; (2) organized developer/translator pushback or regulation requiring disclosure/quality audits within 6–24 months; (3) commoditization of fine-tuning tools that lower barriers for studios and make the shift stick. Positioning should therefore balance short-term AI adoption momentum against a 6–24 month horizon where consumer and regulatory feedback can materially reprice creators and service providers.

Key Decisions for Investors

• Long NVDA (NVIDIA) — Buy 6–12 month call options or a disciplined long stock position (size 1–2% portfolio). Rationale: fastest path to capture inference/GPU demand as studios migrate translation and fine‑tuning workloads on-premise/cloud. Risk/Reward: high upside if inference demand sustains; downside is valuation compression — stop-loss at 20% drawdown.
• Long MSFT (Microsoft) or GOOGL (Alphabet) — Buy 6–12 month call spreads to capture cloud + model‑deployment revenue without full delta exposure. Rationale: enterprise AI contracts and model hosting are multi-quarter revenue drivers. Risk/Reward: moderate upside with lower tail than pure-play chip exposure.
• Short RWS.L (RWS Group) or buy 9–12 month puts on publicly traded localization specialists — size small (<=1% portfolio). Rationale: direct exposure to margin compression from AI translation adoption; earnings risk over the next 2–4 quarters. Risk/Reward: asymmetric if firms can pivot to premium human-in-the-loop services or win regulatory carve-outs.
• Pair trade: Long NVDA (or MSFT) / Short RWS.L — 6–12 month horizon to isolate infrastructure upside vs services erosion. Target 2:1 reward:risk with dynamic stop-losses (20% on each leg) and re-evaluate on concrete review-score or adoption metrics.