In 2025, most leadership teams thought they’d finally found the solution to their customer experience challenges. Artificial intelligence (AI) promised the scale, velocity, and personalization they needed, and it did so with a favorable impact on costs. Vendors confirmed it. Dashboards were improved. Processes were streamlined. Headcount growth was no longer a worry.
By year-end, however, something unpleasant had set in. Customer experience had not improved commensurately with the introduction of AI. In many cases, it got worse.
This wasn’t AI’s fault, however. It was the fault of leadership teams for misunderstanding what AI was capable of and not capable of doing to solve their customer experience challenges.
AI did not solve poor customer experiences. It exposed poor execution.
The appeal of AI in the customer-facing part of the business is easy to understand. It promises to provide the leverage customers experience faces organizations wanting to improve, consistency, and relief from operational burdens. For firms under pressure to scale and grow without increasing headcount, it’s irresistible.
Acceleration, however, always compounds existing weaknesses.
If processes are unclear, AI accelerates confusion.
If accountability is fragmented, AI accelerates deflection.
If incentives are misaligned, AI accelerates mistrust.
In 2025, most companies implemented AI on top of weak execution. They automated workflows in need of reform. They digitized handoffs that should not have existed in the first place. They optimized for velocity without clarifying accountability.
From within, it felt like massive progress. From outside, however, customers felt disconnected from firms.
The most damaging AI implementation in firms was motivated by a single desire: to avoid tough organizational discussions. Vendors encouraged this.
Leadership teams wanted to use AI to understand customer health without having to engage in important discussions about which accounts to focus on, which to de-prioritize, and what the company would stand behind.
It backfired.
Customers encountered smart, but empty, interfaces. Intelligent assistants that could answer questions but not solve problems. Automated journeys that used clever language to personalize experiences but delivered generic outcomes.
It felt sophisticated. It felt disconnected.
Customers soon learned to tell the difference between companies that used AI to serve them and companies that used it to hide from them.
Customer experience is not a function. It’s the cumulative impact of decisions made in sales, product, customer success, and support. AI touched all these teams in 2025 but revealed their ineffectiveness.
In sales, AI-driven insights improved targeting in teams that already struggled with this.
In customer success, AI alerted teams to problems, but only gave them limited authority to resolve them.
In support, AI absorbed incoming requests but made escalation challenges even worse than before.
Each function improved. The overall customer experience worsened.
This is the core misconception about AI-driven CX: improving the performance of individual functions does not improve the customer experience. It makes it more vulnerable to failure by obscuring where failures occur.
What customers want more than anything else during moments of friction is care. AI cannot provide care.
AI is fast. It is clever. It does not understand context, however, or exercise judgment.
In 2025, many companies removed human judgment from customer interactions in pursuit of efficiency. Escalation paths were eliminated. There were no exceptions. Agents were bound by scripts generated upstream.
What customers got was care without judgment. Processed. Not helped.
The perception set in quickly.
One of the oldest myths still in circulation is that customer experience can be fixed with enough tools, better platforms, or better data.
It’s a myth that’s dangerous.
Technology does matter but customer experience is not a technical problem. It’s an execution problem.
Execution ensures that data-driven insights translate into actions.
Execution ensures that feedback changes behavior.
Execution ensures that promises made to customers align with what can be delivered.AI can assist with execution, it cannot execute.
The companies that upgraded CX with technology in 2025 are suffering. Customers did not become more loyal. Customers did not become more engaged. Customers became more cautious and selective.
The sophistication of the experience did not make up for the fragility of the experience.
The companies that used AI in customer experience successfully achieved a level of execution maturity.
They addressed ownership before they automated workflows.
They streamlined processes before they accelerated them.
They empowered their teams before they introduced intelligence into their operations.
In these firms, AI did exactly what it was intended to do. It accelerated the time it took to gain meaningful insights. It simplified the cognitive load associated with decision-making. It allowed teams to focus on issues that really mattered.
Customers detected the change.
Not because the technology was invisible, but because it improved the customer’s experience without making the company feel more distant or less coherent.
In 2025, leaders were given a second chance. The challenges that AI presents to leaders are an opportunity.
When execution maturity is lacking, AI exposes it.
When misalignment exists, AI intensifies it.
When trust is tenuous, AI tests it.
In 2026, leadership teams cannot hide behind implementation roadmaps or vendor guarantees any longer. The question is no longer if AI has been implemented, but if the organization is equipped to benefit from its use.
Being equipped to benefit from AI is not a technical matter. Being equipped is a structural concern.
It depends on knowing who needs to know what.
It requires a disciplined approach to prioritization.
It entails understanding where speed creates more risks than opportunities.
Most importantly, it requires recognizing that customer experience is grounded in how the organization operates, not in the sophistication of its technology.
At International Executive Consulting, we are engaged by companies after they have implemented AI solutions that failed to produce the desired results for their customers.
Leadership teams are aware that something is amiss but struggle to articulate it.
What we find when we investigate these situations is not a lack of technology; we encounter a lack of execution maturity.
Our consulting work addresses this gap. We help leadership teams find their balance before or during the implementation of AI solutions. We assist them in understanding what areas require human intervention and which allow for automation. We support them in ensuring that the departments that interact with the customers are aligned.
After all, AI is not a shortcut to great customer experience.
AI is a mirror. And in 2026, only companies that want to benefit from this technology are willing to look in that mirror and address its revelations.
Author: Sandrine Moreau
At International Executive Consulting, we excel in driving business transformation and organizational change - enhancing corporate performance while optimizing efficiency.