Customer expectations have outpaced many of the support tools companies still rely on. Demo videos, scripted chatbots, and one-size-fits-all onboarding flows once felt modern, yet today they often frustrate more than they delight. During our recent LinkedIn Live, “AI Meets Customer Experience,” guest advisor Helen Dwight and our Cofounder & CEO Irosha de Silva unpacked why the gap is widening and how a new generation of “agentic” AI can close it. 

Below is a summary of the discussion for those who missed the session.

Traditional Support Tools: Helpful Yesterday, Painful Today

• Demo videos lack interactivity. A video plays the same way for every viewer, so it rarely answers each person’s specific question. Frequent product updates make these videos expensive to maintain, and many users simply tune out after a minute or two.
• Scripted chatbots struggle with nuance. Rule-based bots do a decent job on FAQs, but the moment a customer phrases a question unexpectedly or needs empathy, the experience breaks. Users end up pounding “agent” on the keyboard or leaving altogether.
• Self-guided tours can feel rigid. Every user must follow the same click-through. Advanced users get bored while novices still get lost. Screen-share sessions solve this only if you have limitless human bandwidth – few companies do.

The common thread is that these tools don’t adapt in real time, so they rarely match the diversity of customer usage.

The AI Dilemma: Customers Pump the Brakes, Leaders Hit the Gas

A 2024 Gartner study (Gartner Survey Finds 64% of Customers Would Prefer That Companies Didn’t Use AI For Customer Service, July 9, 2024) paints a striking picture:

• 64% of customers would prefer that companies didn’t use AI for customer service

• 53% of customers would consider switching to a competitor if they found out a company was going to use AI for customer service

• Many customers fear that GenAI will simply become another obstacle between them and an agent
  

At the same time, 60 percent of service leaders say they are under pressure to deploy more AI to reduce cost and scale faster.

This tug-of-war leaves enterprises asking: How much AI is enough – and how do we use it without alienating the people we serve?

To strike that balance, leaders need a clear playbook – one that treats AI as an enabler rather than a barrier. The goal is to keep the speed and scale advantages of automation while preserving the empathy and control customers expect. The principles below offer a practical starting point.

Principles for AI That Customers Welcome

1. Make the human path easy
   AI should route a customer to a person the moment confidence drops, passing full context so the caller never starts over.

2. Prioritize accuracy and transparency
   Narrow the AI’s scope at the outset, let it admit uncertainty, and always offer a human fallback.

3. Design for empathy
   Tone, pacing, and visual guidance matter. If the interaction feels friendly and situationally aware, users judge it as “human enough.”

4. Fit the business, not vice versa
   Integration should layer onto existing workflows, not require a CRM overhaul (but this is a great opportunity to reassess current processes) . Low total cost of ownership and clear ROI are non-negotiable.

A New Approach: Marketrix and Spatial Understanding

At Marketrix we started with a single, provocative question: What if software could support itself? Our platform builds a rich spatial model of every screen in your application, learning the buttons, menus, and permission states just as a seasoned power-user would. Once that map is in place, the AI can help customers in three escalating ways – so people get exactly the depth of assistance they need, when they need it and how they need it. 

• Tell Me – A concise, context-aware tip pops up in-app, giving users the quick answer or definition they’re after.

• Show Me – The AI visually highlights each element to click and narrates the workflow step-by-step, rerouting like a GPS if the user drifts off course.

• Do It For Me – With the customer’s consent, the AI takes the wheel and completes repetitive or multi-step tasks automatically, then shows a clear summary of what it changed.
  

If confidence drops at any point, the system hands off to a human agent with full context, so the conversation never resets and precious time is saved.

Early pilots report a 20–30 percent reduction in “how do I?” tickets and a marked uptick in feature adoption – all without forcing a rip-and-replace of existing systems. For customers, it feels like working alongside a patient colleague; for enterprises, it frees human agents to focus on complex or revenue-driving work while preserving the empathy that keeps users loyal.

Key Takeaways for Enterprise CX Leaders

• Plan first, deploy second. Map where AI slots into existing journeys before writing a single line of code.

• Blend empathy with automation. Technology should accelerate help, not hide the humans.

• Always include a human escape hatch. Trust rises when people know a real agent is one click away.

• Evaluate solutions against a full checklist. Easy integration, low upkeep, clear ROI – and most importantly, a customer experience that feels personal.

If you missed our full conversation, watch the replay here: https://www.youtube.com/watch?v=V5jlNQR8YzI and let us know your toughest CX challenge. Together we can build support experiences that are smart, scalable, and still unmistakably human.

Published by Marketrix – Intelligent interactions through simulated spatial understanding.