In this article:
Every B2B executive, CCO, and VP of Support has the same mandate from the board and CEO: Use AI to drive down costs, improve productivity, and grow revenue. But the practical reality of actually doing this requires a steadfast approach to identifying and executing against proven opportunities.
We’ve worked with some of the best mid-market B2B companies in the world, and what has clearly emerged from our conversations with leaders is a clear AI Maturity Model for the B2B Customer Experience. It creates demonstrable ROI at every level, whether you are embarking on your first AI project or are already thinking about how to agentically automate support and CS operations.
Phase 1:
Answer Automation — Efficiency and Deflection
We know that customers want to self-serve. When they have a problem or a question using your products and services, 30-70% are “How do I” questions. This is in contrast to B2C support, where the majority of customer needs revolve around transactional information, like “Where’s my order?” In the B2B environment, getting the right answer typically requires deeper product knowledge.
Enabling B2B self-service is not just sticking a legacy chatbot on your site and calling it a day. In 2026, Answer Automation means a Gen AI-native, customer-facing experience: in-product, via chatbot, and on your support site — every surface area where customers go for answers.
But a chatbot isn’t enough. To get to Phase 1 of the Maturity Model, you must also deliver a platform to the functions that deliver support and customer experience. This starts, of course, with your support team but extends to enable other functions that are critical to building and delivering the product and associated “How do I” content that powers Answer Automation.
Successfully deployed Answer Automation:
- Creates 30-50% traditional “ticket deflection.”
- Reduces ticket handle and response time by 30-50%.
- Increase tickets handled per support rep by 25-50%.
- Lifts CSAT to as high as 95%+, due to a more engaged, resolution-oriented experience for customers.
If you haven’t deployed an AI-native platform across customer-facing and internal support and CS operations, there’s still substantial value to create, just in Phase 1 of the Maturity Model.
Phase 2:
Operational Optimization — Workflow and Cost Management
Answer Automation is the entry point to drive ROI in B2B support. But it’s not enough. Your teams are still required to operate the old way, bound to using an array of SaaS tools to operate your support organization as well as those that enable customers to have a great experience.
Phase 2 is where your organization moves from answering questions to connecting systems and automating the core workflows that underpin the B2B customer experience — and further amplify support and CS impact.
At this phase, your organization begins to use AI agents to operate workflows across content and support operations, and extending into cross-functional customer operations. Your organization can use AI to drive outcomes by:
- Deploying AI Agents that automate the complex ticket processes required by legacy SaaS platforms that slow down your support team.
- Automating workflows that start with the customer, like “open a ticket if and when the customer gets frustrated.”
- Removing costly “swivel chair” tasks like looking up JIRA issues, reporting bugs, and making feature requests.
- Automatically suggesting new content to fill gaps detected in existing knowledge bases.
Reducing need for manual intervention and streamlining the end-to-end support process ultimately leads to structural, measurable impact:
- Higher first-contact resolution
- Average handle time (AHT) reduction
- Lower agent burnout while minimizing need to increase headcount
- Improved customer self-service success rates
- Predictable cost at scale as volume grows
- Decrease in time and effort needed to keep support knowledge base up-to-date
Importantly, delivering agentic automation to this extent — something that wasn’t possible before today — allows your support organization to cost-effectively scale while enabling your customers to get the most value out of the product they’re using, whether they’re engaging with AI-aided support agents or AI directly.
With the right AI technology, you can create a true system of action that scales operations and surfaces retention and expansion insights to unlock the next S-curve of business impact.
Phase 3:
Revenue & Retention Expansion — Growth and Strategy
The final phase of the support Maturity Model shifts the support function to higher-impact activities, enabling focus on the most critical and complex customer issues.
You’ve always known that support interactions can serve as an early warning system for retention risks and identify growth opportunities, but until now, support organizations haven’t had the tools to systematically do this across every customer and every interaction.
By uncovering customer signals across the entire support journey, an AI-native platform can interpret and connect them directly to the rest of the business. This eliminates the silos that have constrained B2B companies to date, ultimately enabling you to proactively address issues and capitalize on expansion opportunities.
As such, support interactions become a rich source of intelligence:
- Voice of Customer analysis surfaces sentiment trends.
- Journey intelligence identifies friction across the lifecycle.
- Customer health monitoring detects risk before churn occurs.
- Expansion and upsell signals emerge naturally from support conversations.
Instead of reacting after outcomes happen, AI enables your teams across the customer lifecycle to act earlier:
- Executives are alerted when key accounts show signs of distress.
- Account teams are notified of expansion opportunities.
- Customer experience metrics like NPS and advocacy connect directly to Net Revenue Retention.
The transformative power of AI emerges as support becomes a leading indicator, not a lagging one. Support doesn’t just solve problems anymore. Done right, it signals risk, uncovers expansion opportunities, and aligns the entire organization around a shared understanding of the customer.
This Is Where Support Changes the Business
For CCOs, the real challenge today isn’t whether to adopt AI — it’s understanding where it delivers real, measurable impact for customers. The lens of the AI Maturity Model for the B2B Customer Experience clarifies the technology’s potential: Answer Automation opens the door, but the real ROI curve starts after deflection, when AI reduces operational complexity, orchestrates work across systems, and helps teams predict and influence customer outcomes.
While traditional thinking might lead you to choose the incumbent for support AI, the reality is that this exposes you to the risk of deploying AI that fails to improve customer outcomes and leaves the CCO and support organization ultimately accountable for inconsistent, poor customer experiences.
To successfully implement the AI Maturity Model, companies need a single, unified, AI-native platform that can automate processes end-to-end. Embrace is the AI-powered B2B Customer Support and Experience Platform built for this journey because it is native AI built from the ground up — not a legacy SaaS system with AI layered on top.
Instead of stopping at ticket deflection, it acts as a unified system of action, helping support teams move from answering questions to running workflows and surfacing insights that drive retention and growth. The result is a single, continuous view of the customer that helps organizations move beyond the SaaS plateau and unlock the compounding impact of AI across the entire support lifecycle.
Request a demo
Learn firsthand how Embrace provides the foundation to scale support intelligently, improve customer experience, and turn support into a true business driver.
