March 05, 2026
The AI Dilemma: What Top CX Professionals Really Think About Automation vs. Human Touch
If there is one topic that united CX professionals in 2025 and promises to define 2026, it is the rise of artificial intelligence. The conversation has moved on from breathless predictions. Now, the leaders featured in CXM Stars 2026 are living with AI in production. What they are discovering is more nuanced, more human, and frankly more interesting than the hype suggests.
Across their submissions, a consistent tension emerges: the efficiency gains from automation are real and measurable, but so is the risk of deploying it improperly. The question is no longer whether to use AI, but how to do it in a way that deepens trust rather than eroding it. Six voices, each working inside an end-user organisation, illuminate both sides of that question.
Building AI Responsibly in a Regulated Utility
Asude Soyaslan sits at the intersection of two forces that are pulling in opposite directions: the pressure to deploy AI at pace and the obligation, in a regulated energy utility, to comply with frameworks that were not designed with AI in mind. In 2025, she integrated WhatsApp and chatbot capabilities into Enerjisa’s digital ecosystem and co-developed a chatbot with internal IT teams that was presented at a Microsoft AI event. But she is clear-eyed about what comes next.
“The biggest CX challenge heading into 2026 is enabling advanced AI-driven experiences while operating within increasingly complex regulatory, data privacy, and security frameworks. In highly regulated sectors such as utilities, the use of cloud-based AI solutions presents both an opportunity and a challenge. Defining acceptable architectures, governance models, and compliance standards — especially in collaboration with regulatory bodies — will be critical to unlocking AI’s full potential.”
Her point about regulatory bodies is important and often absent from mainstream AI-in-CX discourse. Rules around data residency, algorithmic transparency, and consumer protection were written for a different era. Organisations that want to deploy AI at scale in regulated industries are, in effect, working without a complete rulebook, and the cost of getting it wrong falls on customers.
Orchestrating Trust at Scale
Alma Olela operates in a market where AI adoption is accelerating rapidly, but where infrastructure, cultural context, and consumer expectations look very different from the environments in which most AI tools were developed. Her 2025 work focused on transitioning Jubilee Insurance from static NPS measurement to a real-time, relationship intelligence model, embedding live customer signals into operational and executive decision-making.
Her biggest challenge statement cuts to the heart of what the entire industry is grappling with.
“The biggest Customer Experience challenge facing the industry in 2026 is not technology adoption — it is orchestrating trust, humanity, and accountability at scale in an increasingly automated world. Across Kenya and Africa, organisations are rapidly embracing AI, automation, and digital channels to improve efficiency and access. While this acceleration is necessary, it introduces a critical risk: CX becomes faster, but not necessarily better; more digital, but less human; more data-rich, yet less trusted.”
The phrase ‘orchestrating trust’ is worth pausing on. Trust is not a feature that can be switched on once AI is deployed. It is built, often slowly, through consistency and accountability, and it can be destroyed quickly when automation fails a customer who needed a human. Olela says that the CX leader’s role in 2026 is less about implementation and more about governance.
Scaling AI Without Losing the Human Standard
At one of the United States’ largest pharmacy and health services companies, Melissa Archambault is working on a problem of enormous scale: how do you embed a culture of empathy and human connection when the organisation employs hundreds of thousands of people and AI is increasingly mediating customer interactions?
In 2025, her work centred on building CX culture at enterprise scale, such as leadership capability, service recovery frameworks, and systems that make it easier for frontline colleagues to do the right thing for customers. It is, deliberately, the human complement to the organisation’s technology investment.
“Our greatest challenge is learning to embrace advanced AI without losing the human connection that defines meaningful experiences. This tension — between unprecedented technological capability and the irreplaceable value of empathy — is shaping every aspect of modern CX leadership. AI in 2026 is no longer experimental. It is embedded. But embedding AI into a customer journey is not the same as designing a customer experience. The design problem is the hard part.”
Archambault’s distinction between embedding AI and designing an experience is one that many organisations are learning the hard way. The technology can be integrated in days. Building the judgment, at every layer of the organisation, to deploy it in ways that serve customers rather than frustrating them, is a much longer project.
When AI Moves Faster Than CX Maturity
Bolaji Olusola Sowoolu delivered one of the most concrete CX turnarounds in 2025, taking CSAT from 72% to 89% and lifting the company’s Trustpilot rating to 4.8 through journey redesign, proactive service models, and targeted coaching. The transformation was built on operational discipline.
Which makes his 2026 challenge statement particularly credible.
“The biggest CX challenge in 2026 is scaling AI and automation without eroding trust, quality, or human accountability. The industry proved AI can drive efficiency and insight. In 2026, the challenge is no longer whether to use AI, but how to operationalise it responsibly and sustainably. Many organisations are deploying AI across channels without first fixing broken journeys, poor data quality, and unclear ownership of outcomes. You cannot automate your way out of a broken process.”
The last observation is perhaps the most practically useful insight in this entire collection. AI amplifies what already exists. Where the underlying journey is sound, it can dramatically improve speed and personalisation. Where it is broken, it will break faster, at higher volume, with less opportunity for a human to intervene and recover the situation.
