Google Cloud's Gemini Enterprise for CX brings brand-owned AI agents to support
Google Cloud has launched Gemini Enterprise for Customer Experience (CX), a suite for building AI shopping and customer service agents under one interface. Early adopters include Kroger, Lowe's, Woolworths and Papa Johns. For support teams, this points to fewer handoffs, more context, and agents that can act instead of just suggest.
What it is
Gemini Enterprise for CX connects the full journey-from discovery to post-purchase-and lets AI agents take action. Shopping agents can add items to a cart, apply discounts, and work with service agents who handle inquiries and account needs.
The package includes Customer Experience Agent Studio, a build-and-launch environment where you can upload chat transcripts and documents, then use a drag-and-drop interface to create workflows. These agents can take specific actions, like applying credits to a customer's account, with controls you set.
Why support leaders should care
The promise here is control. As Google's Darshan Kantak put it, "They own their data and control the customer relationships. Google is providing the engine. The brands own their signature experience." For support, that means your AI runs on your rules, your knowledge, and your systems.
It also means the shopping agent and service agent share history and context. A customer's cart, eligibility, previous tickets, and active promos can inform the next response-across chat, email, voice, and apps-without repeating questions.
Key capabilities that matter in the contact center
- Actionable agents: Issue credits, apply discounts, update orders, or start returns with policy checks and audit trails.
- Real-time guidance: Side-by-side assistance for human agents with suggested replies, knowledge snippets, and relevant policies.
- Training and QA: Personalized simulations for onboarding and upskilling, automatic conversation scoring, and trend tracking to spot recurring pain points.
- End-to-end context: Shopping and service agents share state, so conversations carry over between channels without losing details.
How you might implement it
- Start with scope: Pick 3-5 high-volume intents (order status, returns, promo issues, address changes). Keep the first tranche narrow and measurable.
- Ground the model: Import recent chat/email transcripts, updated policies, and your knowledge base. Remove stale assets.
- Design the guardrails: Define which actions are fully autonomous vs. require human approval (credits over $X, multi-item refunds, international orders).
- Connect the stack: CRM, order management, ticketing, identity, and payment systems. Map required permissions and logging.
- Test with real data: Use sandbox orders and past tickets. Run shadow mode first (agent suggestions only), then progressive autonomy.
- Measure and iterate: Track FCR, AHT, containment, CSAT, refund leakage, and action accuracy. Tune workflows weekly at the start.
Governance and risk controls
- Approval queues: Route edge-case actions to senior agents. Keep a visible audit log for every automated step.
- Policy versioning: Tie agent behavior to policy versions so you can trace outcomes to the rule set in effect.
- Data boundaries: Limit access to PII fields, enable redaction, and set retention windows appropriate for your region and industry.
- Simulation before scale: Use the Agent Studio's simulations to stress-test new promos, returns rules, and seasonal spikes before go-live.
Practical use cases to prioritize
- Order help: Status, delivery ETA, re-ship, cancel before fulfillment, address updates.
- Promos and pricing: Apply eligible discounts, fix misapplied codes, explain exclusions.
- Returns and exchanges: Eligibility checks, label creation, instant store credit within rules.
- Account and billing: Password resets, payment method updates, apply credits with thresholds.
Rollout checklist
- Define success metrics and guardrails.
- Load up-to-date knowledge and transcripts.
- Map action permissions to roles and systems.
- Pilot on one channel before expanding.
- Review weekly: errors, escalations, refunds, CSAT.
Bottom line for support teams
Gemini Enterprise for CX gives you agents that can do the work, not just suggest it-and lets your brand keep the keys. If you set clear rules, plug into the right systems, and measure outcomes from day one, you can reduce handle time, cut repeat contacts, and improve consistency without losing control.
Level up your team's AI skills
If you're planning a pilot or upskilling your agents and QA leads, explore role-based training here: AI courses by job. For a broader view of vendor ecosystems and options, see AI courses by leading companies.
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