Technology & Customer Experience
Enterprise Conversational AI Implementation
Took a fragmented self-service experience and replaced it with a single enterprise virtual assistant deployed across web, chat, and voice, governed by a phased scale-up roadmap.
Client
A multi-channel customer service organization
Duration
12 months
Services Used
Technology Strategy & Roadmap, Program & Project Leadership
The Challenge
- Self-service tools had been deployed independently across business units, with no shared platform, data model, or governance.
- Containment rates were low, pushing avoidable volume to live agents and inflating cost to serve.
- Leadership wanted an enterprise virtual assistant but had no agreed use-case priorities or delivery plan.
The Approach
Mapped against the relevant dimensions of the ACTION™ framework.
Audited self-service usage, containment rates, and the patchwork of point solutions already deployed across business units to establish a single, shared baseline.
Facilitated executive workshops to define a single AI vision and prioritize use cases across business units competing for the same budget.
Led vendor evaluation and architecture review for a Microsoft-ecosystem virtual assistant platform, establishing the operating model and integration into existing CRM and knowledge systems.
Established program governance across five workstreams and three vendors, with a phased rollout from pilot to enterprise scale.
Built a change and training plan for frontline agents and channel owners across business units, so consolidation read as a shared platform win rather than one team's tool replacing another's.
Tracked containment and agent-transfer rates by channel after each release, using the data to decide which use case launched next rather than following a fixed roadmap.
The Solution
- Selected and implemented a single conversational AI platform integrated with CRM, knowledge base, and telephony.
- Sequenced deployment by channel and use case, starting with the highest-volume, lowest-complexity intents.
- Put in place program governance, vendor management, and executive reporting spanning the full delivery lifecycle.
The Results
Higher containment rate
A significant share of previously agent-handled interactions resolved by the virtual assistant without a transfer.
Lower cost to serve
Reduced live-agent transfer volume for routine requests across web, chat, and voice channels.
Faster time to scale
Subsequent use cases launched markedly faster once the platform, governance, and playbook were established.
Consolidating onto a single platform and governance model, rather than continuing to add point solutions, was the unlock that let the program scale past pilot.
Facing a similar challenge?
Let's talk through what's specific to your organization and what a realistic path forward looks like.