Resolve demand at the lowest responsible cost.
Automate order status, account inquiries, returns and credits first. Preserve a context-rich human handoff when confidence or consequence changes.
Outcome Verified resolution
A Point of View for McKesson Agentic Customer Experience Center
From cost center to enterprise value engine.
Empowered by AI, the customer center stops being just a problem-solving tool — and starts protecting revenue, activating new sales, sharpening marketing, and catching supply chain risk early. All while making every interaction simpler for the customer.
01 / The value thesisOne conversation.
One conversation.
Four value streams.
Every contact contains operational truth: what the customer needs, where the journey breaks, what revenue is at risk and where demand is moving. AI turns that signal into governed action.
Recognize risk and opportunity in the moment.
Turn churn signals, recurring issues and product interest into a qualified, permissioned handoff to the right account owner.
Outcome Revenue protected + expanded
Convert customer intent into relevance.
Aggregate questions and friction patterns into sharper segments, education and next-best messages — without compromising trust.
Outcome Faster signal-to-campaign
Make service demand an early-warning system.
Detect shortage, backorder and substitution patterns; trigger proactive communication and inform replenishment decisions.
Outcome No waste + High CSAT
02 / Why now
Healthcare is moving to AI at high speed.
The market is moving beyond isolated assistants toward agentic customer experiences. Leaders are connecting AI investment to measurable outcomes, centralized enablement and governed delivery at scale.
80%
of common service issues could be autonomously resolved by 2029, with operating costs reduced by 30%.
Gartner forecast Life sciencesAstraZeneca
A dedicated Enterprise AI unit connects transformation across R&D, Commercial, Operations and Corporate functions.
Enterprise scale Healthcare distributionCardinal Health
An AI Center of Excellence begins with unmet customer needs and coordinates responsible solutions across the enterprise.
Centralized enablement Payer + pharmacyCVS Health
Expanded agentic support across Aetna and CVS Caremark call centers to make member and provider interactions faster and more personalized.
Scaled agentic serviceExternal benchmarks indicate direction, not a McKesson business case. Baselines and value targets should be established from internal data.
03 / Customer experience
Real customer needs and the adoption dilemma.
Having the right technology, partners and delivery capability is not enough. Success begins with understanding customers and service agents — then transforming their relationship into business value without disruption. Adoption is the strategy.
Do not add to “pajama time.”
Pharmacists, doctors and analysts are already overloaded. Another disconnected tool creates work instead of removing it. AI must fit the workflow, reduce cognitive load and return time to customers and patients.
Personal trust cannot be automated away.
Relationships between customers and service agents are built over years. AI should preserve context, strengthen the personalized touch and help people make better decisions — not replace the relationship.
The challenge is no longer whether to adopt AI. It is how to move from scattered pilots to scaled, governed business outcomes without losing customer trust.
I have seen it in the market
Three transformations. One consistent lesson: design around people, then scale the value.
GE Healthcare
$5M+ savings · Year 1Served as executive enterprise program leader for a CEO-backed internal AI platform. Navigated complex, regulated healthcare data products to unlock operational and regulatory efficiencies and establish a scalable foundation for data-service expansion.
Air Liquide Healthcare
$5.8M savings · 3 yearsManaged a 24-country customer-service transformation, cut AHT in half and materially improved regulatory compliance, quality assurance and quality control.
Mercedes
$5M+ new revenueImplemented a highly personalized customer-service model across the US and EMEA, empowering agents to support dealers, preserve high-touch relationships and convert service conversations into new revenue opportunities.
04 / The operating model
AI excellence requires an operating framework — not another pilot.
For market leaders, AI is already a must-have. But transformation requires more than selecting tools and proving isolated use cases. Healthcare needs a composable, scalable and adjustable framework that connects the technology to how the enterprise actually operates.
InnovationArchitectureOrchestrationAdoptionSecurityFinOpsContinuous adjustment
Research
Conversation, case, order, inventory, account and campaign signals
Customer + enterprise dataUnderstand
Intent, sentiment, root cause, risk, confidence and next-best action
Unified context + governed AIAct
Resolve, notify, recommend, route or escalate across channels
Voice + service workflowsLearn
Verify the result, attribute value and improve the next decision
AI Ops + business owners05 / Lessons learned
Protect the relationship. Remove the work.
Equip the named representative with customer history, risk signals and prepared follow-up — instead of putting another interface in front of the customer.
Enrich trusted calls in real time; use voice automation for overflow without breaking relationship continuity.
Put intelligence inside channels pharmacists, physicians and agents already use.
Show recommendations and plans for review before AI acts on a customer's behalf.
Mine existing calls and cases, then close a visible “you told us, we changed it” loop through the named rep.
Match rollout and communication to relationship type and readiness — reducing resistance and message fatigue.
Earn adoption before scaling autonomy.
Start with customer and agent evidence, co-design the experience, and scale only when observed behavior and outcomes show that the change is trusted.
1
Research the relationship
Observe calls, interview customers and agents, map trusted moments and quantify friction without assuming automation is the answer.
Journey evidence + adoption risks2
Co-design and prototype
Use design thinking to test agent-enabled experiences with frontline teams and customers in high-value, low-disruption journeys.
Prototype + behavioral feedback3
Evaluate and earn scale
Measure customer effort, trust, adoption and business value. Expand only the experiences that improve both the relationship and the outcome.
Adoption evidence + value caseBalanced value scorecardCustomer effortAgent adoptionTrust + CSATVerified resolutionRevenue protectedTime returned
06 / Why me
I connect AI ambition to operating reality.
My experience spans enterprise AI product ownership, regulated healthcare, contact-center transformation and the leadership required to build a new cross-functional capability.
natallia.isaevich@gmail.comGlobal service transformation
Led a 24-country program at Air Liquide Healthcare; halved AHT while strengthening quality and compliance.
CX outcome improvement
Delivered real-time guidance across calls, chat and email for AmeriLife, improving CSAT and NPS.
Experience first
Start with customers and frontline teams, not assumptions about what the technology should do.
AI-enabled evidence upfront
Make the future experience tangible early, then learn from behavior before scaling investment.
Design thinking with business discipline
Connect desirability and adoption to measurable customer, operational and commercial outcomes.
The opportunity