Left of Ask vs Right of Ask: A New Framework for AI in CX

The CX Landscape Explosion

The customer experience space has undergone a dramatic transformation. In 2005, there were about 20-30 premise-based companies in this space. Today, that number has grown to over 1,100 vendors focused on customer experience.

Adam Elkins noticed this explosion firsthand at CCW Nashville in October 2024: "It was like, wow, this is really here. It's really exploded. And that was when it really took off for me."

Unlike the previous shift to the cloud (which primarily enabled infrastructure and licensing flexibility), AI fundamentally transforms operations through its ability to interpret conversations and business data in real time.

The Framework: Left of Ask vs Right of Ask

Origin: Cybersecurity's Left of Boom

The concept originates from US military terminology and the NIST cybersecurity framework:

• The Boom: Originally referred to IED detonation; in cybersecurity, it's the attack
• Left of Boom: Pre-event activities focused on disrupting the attacker
• Right of Boom: Post-event activities focused on assessing and addressing damage

Applied to Customer Experience

In CX, the ask is the boom—the customer's question or service request is the event.

Left of Ask (Pre-Event):

• Preparing for customer questions
• Enabling self-service capabilities
• Training agents and systems
• Building knowledge bases

Right of Ask (Post-Event):

• Analyzing interaction quality
• Identifying improvement opportunities
• Coaching and training
• Evolving the CX approach based on learnings

"You can't just build a wall and walk away. You have to prepare for when the attack happens and what happens afterwards."

The Three AI Focus Areas

1. Self-Service Interactions (Green Zone)

Programmatic IVRs are being replaced by conversational AI that can:

• Listen: Capture customer input
• Interpret: Understand intent (the missing piece before AI)
• Confirm: Validate understanding
• Act: Respond appropriately

Cost Impact: Decrease from ~$8/call to ~$1.50/call or less

2. Agent Interactions (Blue Zone)

AI-based agent assist tools provide:

• Real-time listening and coaching
• Knowledge suggestions during calls
• Human-in-the-loop for high-stakes situations

Cost Impact: Decrease from ~$8/call to ~$6/call, plus upsell revenue potential

3. Post-Interaction Analytics (Orange Zone)

This is Adam's "personal favorite"—taking learnings from interactions to:

• Identify trends and patterns
• Provide coaching opportunities
• Improve the knowledge base
• Drive operational insights

Impact: Decreased staffing costs and improved operational efficiency

The Augusta Lawn Care Demo

The session featured a compelling demo of modern AI self-service—a virtual agent named "Max" handling a lawn care inquiry:

• Completely AI-generated voice with natural human cadences
• On-the-fly responses based on intent interpretation
• Handled urgency requests, collected information, and noted special requirements
• Demonstrated how far the technology has advanced from word-spotting systems

Key insight: The agent added "human cadences"—small verbal acknowledgments like "got it" and "perfect"—that make interactions feel natural without you consciously registering them.

The EAC Lesson: Why AI Succeeds Where Traditional Tools Failed

Adam shared a cautionary tale from his Interactive Intelligence days about a FAQ tool called EAC:

"The problem was there was a huge amount of work required to deploy and keep all of this updated... A month later, the customer would come back saying 'our business has changed and we need to update this.' It would just grind to a halt."

AI solves this because it can:

• Respond and change based on new data
• Learn from interactions automatically
• Identify improvement opportunities without manual monitoring
• Enable continuous improvement at scale

Continuous Improvement: The Manufacturing Mindset

Adam's father ran a metal stamping business with "continuous improvement" painted on the wall and a profit-sharing model that got everyone looking for efficiencies.

The same approach applies to AI-driven CX:

• AI tools can interpret and identify improvement areas
• Charts and graphs surface opportunities automatically
• You can build continuous improvement without throwing massive effort at monitoring

Poll Results: Where Businesses See Value

Where do you see the most value?

• Balanced mix of both left and right of ask: Clear leader
• Post-interaction analytics noted as great starting point for those unsure

Which AI area holds most potential?

• Agent assistance and productivity tools: Leading
• Self-service/IVA: Strong second
• Still exploring: Smaller percentage

Matrix Networks' AI Readiness Approach

Step 1: AI Readiness Assessment (1-1.5 hours)

• Brief document based on discovery call
• Understanding of AI readiness and opportunities
• Recommendations, risks, and security considerations

Step 2: Pathfinder Report (10-12 hours over 3 weeks)

• Comprehensive, actionable results
• Agent-based feedback
• ROI and use case analysis with operations and finance
• CSAT-focused questions
• CX operational assessment using the framework

When Are You Ready for AI?

"If you've got any sort of business challenge that you haven't been able to overcome otherwise, it's a really good time to take a fresh look at those. Even if it's something you've dealt with for years and just struggled with—don't put it on the shelf and forget about it."

AI excels at processing language and data—interpreting, understanding, and acting on information whether it's:

• Real-time conversation
• Recorded transcriptions
• Business data patterns

This session was part of the AI for CX Virtual Summit, presented by AmplifAI.