Two weeks ago, I thought I had an understanding of artificial intelligence’s (AI) role in customer experience (CX). 

Then my wife and I were involved in a serious automobile accident. 

In an instant, we found ourselves navigating a complex ecosystem of healthcare providers, insurance companies, attorneys, financial decisions, claims processes, diagnostic information and eventually the need to replace our vehicle. 

These are industries built around expertise. 

Historically, the customer entered many of these experiences at a significant information disadvantage. Your doctor understood the medical terminology. Your attorney understood the law. Your insurance company understood the policy language and claims process. Your bank understood the financing. Your automobile dealer understood the vehicle, pricing, warranties and transaction. 

You relied on each institution to help you navigate its part of the experience. 

Over the past two weeks, I discovered how artificial intelligence is changing that relationship. 

Before meeting with each of these experts, I researched terminology to understand the issues I needed to discuss. I analyzed complicated documents and identified questions I might not otherwise have known to ask during my follow-up appointments. I researched complicated insurance provisions. I took these steps to evaluate prospective professional advisors partly by the depth of their thinking and their ability to engage with the research I had already done. 

I still wasn’t the expert, but I was a more informed consumer.  

The clearest example, though, came when we had to replace our vehicle.  

When AI became part of the buying journey 

My wife and I used AI throughout almost the entire vehicle buying process. 

We used it to research vehicles based on our requirements, compare models and evaluate pricing and safety.  

Once we found a vehicle we were seriously considering, AI became a behind the scenes advisor throughout the transaction. We used it to help evaluate:  

  • Financing alternatives 
  • Lending terms 
  • Warranty products 
  • Expected maintenance costs 
  • The economics of the overall purchase 

We even used live video capabilities to help guide us through a detailed inspection of the vehicle. 

By the time we sat down to complete the transaction, something fascinating had happened. The dealer was still important. The manufacturer was still important. The bank was still important. 

But none of them controlled the experience. We did. 

It became one of the smoothest and least stressful vehicle purchases either of us had experienced because we entered every interaction informed and confident in the decisions we were making. 

In less than two weeks, AI had become a proxy across healthcare, insurance, legal services, financial services and retail. It helped me understand complicated information, prepare for important conversations, compare alternatives and make decisions with greater confidence. 

For someone who has spent much of his career thinking about customer experience, it forced me to reconsider something fundamental. 

We have been talking about AI transforming CX primarily from the enterprise perspective. 

I think we may be looking at the wrong side of the transformation. 

The 360-degree view now runs both ways 

Enterprises have invested billions trying to create a 360-degree view of the customer through connected data, built customer profiles, analyzed journeys, captured intent and more.  

The ambition has always been straightforward: know the customer well enough to create a better experience. 

But AI is now creating the inverse. 

Customers can increasingly understand your products, competitors, pricing, contracts, policies, reviews and potential negotiation points before ever speaking with you. They can upload complicated information and ask AI to explain it. They can compare competing offers, identify questions they should be asking, research whether an explanation makes sense and prepare for the next interaction before it happens. 

I have experienced this firsthand while navigating the aftermath of our accident. At one point, I found myself trying to understand the intersection between automobile insurance, health insurance and the laws governing whether and how one insurer might seek reimbursement from a future recovery. Until recently, I would have viewed that as an almost impenetrable combination of insurance contracts and legal terminology. My options would have been largely limited to asking an insurer or attorney what it meant and accepting the explanation. 

AI helped me understand the concepts, research the applicable rules, examine the language in the relevant documents and, most importantly, understand what those provisions could mean to me as the consumer. I could then prepare better questions for my conversations with the professionals responsible for advising me. 

AI was not acting as my attorney or insurer. It was giving me enough understanding to participate meaningfully in a conversation that historically would have been dominated almost entirely by institutional expertise. 

And unlike the internet search revolution that preceded it, consumers no longer have to manually assemble dozens of pieces of information and determine how they fit together. AI can synthesize that information around the customer’s individual circumstances and help them determine what to explore next. 

That is an enormous transformation in the balance of information between enterprises and their customers. 

And financial services may be providing one of our clearest early signals. 

Financial advice is already moving outside the institution

Researchers from MIT Sloan and Stanford recently examined how consumers are using large language models (LLMs) for financial advice.

Their research notes that industry surveys suggest more than half of adults in the United States and United Kingdom have used LLMs for personal financial guidance, potentially exceeding the share who consult a human financial advisor. 

AI does not have to become a perfect financial advisor to disrupt the financial services industry. It simply needs to make financial intelligence more accessible. 

NPR recently reported on J.D. Power research in which 40% of surveyed consumers said they had turned to AI in the previous three months to help manage their finances. More than a third of those AI users said the guidance helped them make smarter financial decisions, a result comparable to the share who found advice from their bank helpful. 

In contrast, a recent Gallup survey found much lower levels of AI use for financial guidance and substantially greater trust in human financial advisors. 

Put together, those numbers don’t contradict each other; they describe a transition in process in which consumers are experimenting aggressively with AI while still valuing the accountability of a human professional. 

That’s the real exposure for banks and advisory firms. Customers no longer need institutions to be their only source of expertise.  

And that behavior is already spreading far beyond financial services. 

The exam room isn’t the first stop anymore  

KFF reported in March 2026 that 32% of adults had used AI for physical or mental health information or advice during the previous year. Among those users, 41% said they had entered personal medical information such as test results or physician notes into an AI tool seeking explanation or guidance. 

Patients are not simply researching their symptoms anymore. They are arriving at appointments having asked AI to explain terminology, interpret information, organize questions and help them understand what they may want to discuss with their physician. 

This has been another part of my own post-accident experience. When testing results became available, I did not have to spend the days before my appointment wondering what unfamiliar terminology might mean or trying to piece together information from random search results. 

I could use AI to help translate complex results into plain language and help me build a better list of questions for my physician.  

There are legitimate risks here. AI can be wrong. Context is crucial in medicine. Privacy is essential.  

Professional expertise matters. But the behavioral change has already occurred. 

The patient who arrives in the examination room may have spent an hour interacting with an AI system before spending fifteen minutes with the healthcare system.  

How AI is raising the bar for legal expertise  

Legal services may be confronting an even more complicated version of the same phenomenon. 

My own experience reinforced this. Choosing an attorney after the accident was not simply a matter of comparing advertisements, websites or reputations. By the time I began having substantive conversations, AI had already helped me understand many of the issues I wanted to discuss. 

There are obvious limitations and risks here. Legal guidance requires jurisdictional knowledge, professional judgment and confidentiality that a general purpose LLM cannot guarantee. Recent court decisions have also raised serious questions about whether conversations with AI systems receive anything resembling attorney client privilege. 

But focusing exclusively on whether AI can replace the professional misses the larger CX transformation. 

The next frontier of CX is not just enterprise AI 

There is enormous focus right now on how enterprises can use AI. We are asking how AI can automate service, improve employee productivity, personalize interactions, enable AI agents to resolve customer issues and reduce the cost to serve. Those are important questions, and they continue to reshape customer experience. 

But there is another question that may prove equally important: What happens when the customer brings their own AI to the experience? 

They are more prepared, more comparative, more capable of challenging inconsistencies and more equipped to understand complexity. Most importantly, they are increasingly less dependent on the enterprise to orchestrate their journey. 

This creates an extraordinary opportunity for organizations willing to embrace the change. I think the winning enterprises will stop assuming that they own the customer journey. 

My experience over these past two weeks made that very real for me. Across healthcare, insurance, professional services, finance and retail, the institutions remained critically important.  

But I was no longer completely dependent on any one institution to explain the entire experience to me. 

AI gave me a layer of intelligence that traveled with me across all of them. 

Enterprises have spent twenty years trying to build a 360-degree view of the customer. AI is now giving the customer a 360-degree view of the enterprise. 

I think the next frontier of customer experience will be defined by mutual visibility – enterprises and customers who can finally see each other clearly.  

And I am not convinced most enterprises are ready. 

Closing that gap is the real work ahead for CX leaders. They need to equip frontline teams and AI agents with intelligence that matches what customers already bring to the table.  

See how Genesys helps enterprises build that kind of intelligence.