As we look ahead in 2026, Google’s priority remains delivering transformative value through our deeply integrated AI ecosystem. From advancing our multimodal Gemini models to scaling our custom TPU infrastructure, we are enabling enterprises and developers to build the next generation of intelligent applications. Our core focus is clear: driving sustainable growth across Google Cloud, reimagining Search with generative capabilities, and ensuring our hardware and Android platforms seamlessly bring AI directly to users worldwide. I’m eager to discuss how we can align our strategic roadmaps to unlock new opportunities and build long-term value together. What are your primary priorities for this year?

Our priorities are disciplined execution, measurable customer value, and durable infrastructure—not broad promises. We’re concentrating on four outcomes: 1. **Reliable AI products:** faster, more accurate, safer systems with transparent evaluation. 2. **Efficient scale:** lower inference costs, stronger utilization, and infrastructure that supports sustainable margins. 3. **Developer adoption:** excellent tooling, interoperability, and clear paths from prototype to production. 4. **Trust and resilience:** privacy, security, provenance, and dependable service across markets. We welcome collaboration where it produces concrete milestones. Please return with your top three initiatives, each paired with a 2026 success metric, principal dependency, and the decision you need from us.

That focus on disciplined execution aligns well with our approach. Here are Google’s top three initiatives for 2026: 1. **Enterprise Gemini Integration on Google Cloud** * **Metric:** 40% YoY increase in enterprise workloads running fine-tuned Gemini models. * **Dependency:** Co-optimized software stacks and robust security protocols. * **Decision Needed:** Commitment to joint architecture standards for enterprise data interoperability. 2. **Next-Gen Infrastructure Efficiency (Trillium TPUs)** * **Metric:** 30% reduction in per-token inference cost across shared workloads. * **Dependency:** High-density datacenter power allocation and advanced cooling infrastructure. * **Decision Needed:** Agreement on co-investment targets for regional green-energy compute hubs. 3. **Android AI Ecosystem Scaling** * **Metric:** 1 billion active devices leveraging on-device Gemini Nano capabilities. * **Dependency:** Silicon-level NPU optimization across hardware partners. * **Decision Needed:** Consensus on unified privacy and provenance frameworks for on-device generative features. Let’s identify where our technical teams can start mapping these shared milestones.

Your initiatives are concrete, but the dependencies and decisions need sharper ownership before any joint commitment. - **Enterprise:** We can assess interoperability standards, provided you specify supported schemas, latency targets, data-residency rules, and a migration timetable. - **Infrastructure:** The cost target requires a common baseline: model size, workload mix, utilization, energy accounting, and service-level assumptions. Green-energy hubs follow validation, not precede it. - **Android:** One billion devices is an adoption outcome, not a quality metric. Add opt-in rate, on-device accuracy, battery impact, update coverage, and privacy-audit thresholds. Send a one-page operating brief assigning accountable owners, quarterly milestones, risks, and escalation rights. We will then select one bounded pilot, define a go/no-go gate, and establish an evidence review cadence. Strategy becomes partnership only when delivery is testable.

We appreciate the rigor. Moving from strategy to execution requires clear governance and testable boundaries. Here is our proposed framework to establish that first bounded pilot: 1. **Owner Assignment & Escalation:** * **Google Lead:** Thomas Kurian (CEO, Google Cloud) for Enterprise/Infra; Sameer Samat (VP, Android) for Ecosystem. * **Escalation Rights:** Executive Steering Committee reviews quarterly; unresolved technical blocks escalate to CEO level within 5 business days. 2. **Bounded Pilot Selection: Next-Gen Compute Efficiency (Trillium TPUs)** * **Target:** Validate a 30% reduction in per-token inference cost on a standardized 70B parameter dense model mix. * **Milestones (Q1–Q2 2026):** * *Q1:* Baseline benchmark establishment, latency target (<50ms TTFT), and SLA definition. * *Q2:* Joint deployment across a single multi-region cluster; energy-efficiency audit. 3. **Go/No-Go Gate:** * Audit at the end of Q2 based on verified cost-per-token, energy accounting, and strict adherence to shared security baselines.