A few years ago, the promise was simple enough. Invest in AI for patient and member contacts, and quietly do more with less. So, healthcare and pharmaceutical organizations did what the playbook told them to: they bought in, they budgeted. They deployed.
Then the results came in. And they told a very different story.
In a new research study conducted by TTEC Digital and CX Dive, “The Great CX Reset,” 150 customer experience, contact center, and IT leaders across various industries were asked a straightforward question: has AI actually reduced your costs? Not a single respondent reported measurable cost reductions from AI, whether measured against cost to serve, operating costs, or technology costs.
Nearly two-thirds said the opposite had happened: AI adoption had increased their costs. The very thing the investment case was built to deliver hasn't shown up on the balance sheet.
For healthcare and pharmaceutical leaders, the pressure is especially acute. Patients and members expect the same frictionless, personalized service they get from consumer brands — delivered through systems and data environments that were never built for it.
So, what went wrong? That question sits at the heart of the report, which digs into the gap between what CX leaders expected from AI and what they're actually seeing, and what to do about it.
The problem isn't the technology; it's the operating model
The report highlights that AI isn't failing because the technology is immature. It's failing because the organizations deploying it haven't changed fast enough to keep pace. Only 3% of healthcare and pharmaceutical respondents describe their CX operating model as highly adaptive and built for change.
CX strategies have evolved, but the structures beneath them — the teams, workflows, and governance — haven't. Healthcare and pharmaceutical organizations have effectively bolted advanced AI onto rigid, pre-AI operating models that were never designed for cross-platform coordination, scalable AI skillsets, or the governance needed to build trust in AI outcomes.
That mismatch showed up everywhere researchers looked.
The observability gap
There's a difference between what leaders think is happening in the contact center and what's actually happening. When asked whether they can confidently account for where AI is being used across the customer journey, 56% of healthcare and pharmaceutical respondents said they are very or extremely confident they can.
That sounds reassuring, until you consider what it means for the remaining 44%. Nearly half of healthcare organizations are flying at least partially blind when it comes to where AI is actually touching the patient and member journey. In an industry where a missed handoff or an inaccurate response can carry real clinical and compliance consequences, that's not a gap leaders can afford to leave open.
That gap, feeling confident but lacking real visibility, is exactly where ungoverned automation takes root. Redundant tools multiply and decisions get made in the dark. Observability isn't just a hygiene issue; it's a performance multiplier and a patient-safety safeguard.
Where AI is actually being used, and what's holding it back
When healthcare and pharmaceutical leaders do deploy AI, the greatest share (73%) are using it for voice intelligence, including transcription and summarization. It's a practical starting point: high-volume, high-value conversations that AI can capture, organize, and surface for clinicians, associates, and quality teams.
But getting more value from AI isn't just a matter of deploying more tools. When asked what's standing in the way, healthcare and pharmaceutical leaders pointed to three barriers: security and compliance concerns, data quality and readiness, and tool integration complexity. Each one is a familiar challenge in a highly regulated industry, and all are solvable with the right foundation.
Confident on the surface, stretched underneath
If there's a theme running through the findings, it's the gap between confidence and capability. Nearly all (97%) of healthcare and pharmaceutical respondents said they feel somewhat or very confident about their business' ability to improve CX with AI. Yet 0% said they don't have any skill gaps when it comes to AI-enabled initiatives. Every organization surveyed, regardless of size or maturity, has identified at least one skills shortfall.
And when it comes to governing AI responsibly, the picture is similarly mixed. Most healthcare and pharmaceutical respondents (78%) said they have a good mix of speed and caution when it comes to AI governance — a healthy instinct in a regulated environment. But 65% said they have some governance policies but that those policies are sometimes applied inconsistently. The intent is right; the execution isn't keeping up yet.
The strongest teams, the report finds, have found a workable middle path: keeping strategy, prioritization, and governance in-house, then bringing in specialized AI expertise to accelerate execution.
A data foundation that's almost ready
AI is only as good as the data feeding it. When asked how their data foundation stacks up for AI-enabled CX, 65% of healthcare leaders said it is mostly ready but with some important gaps.
That's an honest assessment, and a useful one. The gaps are the work. Fixing reporting tools, governance, and real-time access is the infrastructure that makes everything else possible.
Where healthcare and pharmaceutical leaders are pointing next
When asked where they plan to focus resources in 2027, healthcare and pharmaceutical leaders pointed to three priorities that map directly to the gaps the research uncovered:
- Modernizing the customer data foundation: fixing reporting tools, governance, and real-time access, the infrastructure that makes everything else possible.
- Using AI to improve efficiency and productivity: getting more from the tools already in place.
- Reducing service friction and cost without sacrificing quality: delivering better patient and member experiences at a sustainable cost.
It's time for a CX reset
The organizations that recognize the gap between AI investment and AI return, and that work to close it, will be the ones that finally turn their CX spend into measurable impact. The ones that don't will keep spending more for the same disappointing results.
The Great CX Reset lays out the full picture, with breakdowns by leadership role and industry — including a dedicated healthcare and pharmaceutical breakdown — a clear-eyed look at where AI initiatives are stalling, and a closer look at what the strongest teams are doing differently. Download it here.
