How to Choose the Ideal AI Voice Solution for Your Business

Assembled explores how to evaluate AI voice agents for real-world phone support, based on what really matters.

Phone support is one of the hardest parts of customer service to scale – and one of the most expensive to get wrong.

Customers call when issues are urgent, emotional, or complex. Agents need deep context. Wait times matter. And unlike chat, there’s no room for looping scripts or brittle automation.

AI voice agents promise a way forward. But in practice, not all solutions are built for real support environments.

Some modernize IVRs without improving resolution. Others demo well but struggle with escalation, integrations, or cost predictability once deployed. And many platforms labelled “voice AI” are still optimized for chat-first automation, not live phone conversations.

How to Choose the Ideal AI Voice Solution For Your Business

Choosing an AI voice agent isn’t just a technology decision — it’s a strategic investment that will shape your support operations for years.

After working with hundreds of teams adopting voice AI, a clear pattern emerges: the most successful implementations start with aligned goals, rigorous evaluation, and a plan for long-term scalability. Here’s a practical framework to guide your decision.

Prioritize Business Goals and Needs

Start with outcomes, not features. Before evaluating vendors, clarify what success looks like for your organization. This ensures your pilot, KPIs, and vendor selection remain aligned.

Ask yourself:

• What problem are we solving? (Cost reduction? Lower wait times? CSAT improvement? After-hours coverage?)
• What does success look like in 90 days, 6 months, 12 months?
• Which KPIs will prove ROI to your leadership team?

Most teams cluster around a few core goals:

Goal	KPIs
Reduce Operational Costs	Cost Per Contact, Automation Rate
Improve Customer Satisfaction	CSAT, Sentiment, First-Call Resolution
Scale Without Adding Headcount	Solves Per Hour, Handle Time
Reduce Wait Times	Average Wait Time, Abandonment
Expand 24/7 Coverage	After-Hours Resolution, Callback Volume

The key is matching your pilot and vendor evaluation to the specific outcomes you want. For example:

• If you want higher resolution, look for platforms with strong CRM, billing, and backend integrations.
• If you want better routing, prioritize advanced NLU, sentiment detection, and pre-handoff verification.
• If you want better after-hours coverage, look for consistent performance, smart follow-up workflows, and contextual escalations.

Teams that define narrow, measurable pilot goals — like “resolve 25% of cancellation requests” — see time to value significantly faster.

1. Telephony and Contact Centre Platform

Your AI must slot naturally into tools.

If SIP connections are required, plan for 4–6 weeks of setup, testing, and validation.

2. CRM and Ticketing Systems

Look for real-time, two-way sync for:

• accurate case creation
• full customer history
• automated wrap-up notes
• consistent categorization

Poor CRM integration creates downstream reporting and QA issues, and undermines trust in automation.

3. Knowledge Bases

Your AI should be able to pull from and stay aligned with:

• Notion
• Confluence
• Guru
• Google Drive

…and it must respect permissions and version control cleanly.

4. Backend Systems

This is where meaningful automation happens. Ensure the AI can interact with:

• order and fulfillment tools (Shopify, ERP systems)
• Authentication APIs
• Billing/payment systems
• Custom internal applications

A unified performance view, ties AI activity, human activity, and WFM data together so teams can understand operational impact without juggling dashboards.

Watch out for vendors who:

• Require manual data exports
• Can’t adapt to future CRM changes
• Split reporting across multiple interfaces
• Don’t support real-time syncing

Ask every vendor: “Show me how your AI accesses our CRM data during a live call.”

The strongest partners will have a crisp, confident answer.

Pilot Programs For Testing Performance

Never buy an AI voice solution without proving its value in your environment — with your data, your edge cases, and your workflows.

There are three common pilot structures:

1. Opt-Out Trials (30–90 days)

Good when you’re already strongly leaning toward a vendor.

2. Paid Pilots

Best for validating a specific workflow before expanding.

3. Proof-of-Concept (2–12 weeks)

Tight, time-bound tests focused on validating critical capabilities.

Best Practices For Voice AI Pilots:

• Scope narrowly.
  • Good: “Resolve 25% of cancellation requests.”
  • Bad: “Resolve 25% of all cases.”
• Use preview tools first before exposing customers.
• Start with small volumes (20–100 calls) and scale only after quality is validated.
• Plan integration timelines for SIP, authentication APIs, and backend connections.
• Define success criteria up front — technical, operational, and value-based.

A successful pilot proves five things:

1. The AI works with your systems.
2. Responses are accurate and on-brand.
3. Agents can manage and refine workflows without engineering.
4. Core metrics move in the right direction.
5. The vendor is responsive, transparent, and collaborative.

Plan For Evolving Demands

Your needs today won’t match your needs in 12–36 months. A future-proof AI voice solution should be able to grow with your business across five dimensions.

1. Multi-Channel Expansion

Workflows built for chat, email, or voice should be reusable with minimal changes. This protects your investment as your channel mix shifts.

2. Geographic and Market Expansion

If you’re expanding into new regions or launching new brands, your AI should support:

• Multiple languages
• Time zone–aware handoffs
• Regional compliance
• Multi-brand routing and reporting

3. Automation Maturity

Support operations typically evolve from:

• 5–10% automation (simple FAQs)
• to ~30% (AI-assisted workflows)
• to 40–50%+ (full autonomous resolution)

Choose a platform that supports this climb without requiring full rebuilds at each stage.

4. Workforce Management Integration

As automation grows, staffing strategy must evolve. Integrating voice AI with WFM data ensures:

• Accurate forecasting
• SLA protection
• Capacity-aware handoffs
• Right-sized staffing plans

5. Flexibility Across Brands, Segments, and Products

If you operate multiple brands or business units, or if you’re a BPO, look for:

• Per-brand workflow controls
• Granular routing rules
• Detailed segment-level reporting

Ask Vendors Directly:

• “What happens when we triple our automation?”
• “If we switch CRMs, how painful is migration?”
• “Can we take our workflows and data with us if we change platforms?”

A scalable platform gives clear, confident answers, not vague reassurance or lock-in.

This blog post has been re-published by kind permission of Assembled – View the Original Article

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Assembled
Reviewed by: Megan Jones