David Pedelty | A First 90 Days for LCS Data & AI

Why I'd be effective, fast

What I bring to this specific role

Business outcomes, not tech for its own sake

25 years of P&L leadership. I read AI through occupancy, margin, and conversion, the same way LCS already frames its data wins.

I build agentic AI hands-on

My own infrastructure, an MCP server, and 40+ deployed projects, so I can direct the frontier, not just buy it.

I've led a technology transformation before

As COO of an EHR company (acquired by ChiroTouch), I led developers, sys admins, and support through a client-server → SaaS migration in a HIPAA-regulated environment.

I get adoption in the field

My whole operating career is making systems work for busy, non-technical people across many locations, the make-or-break for AI-native.

How I read where LCS is

You've done the hard foundational work

Which is exactly why this role is about leverage, not starting over.

You stood up a data science team and Insight Advantage a couple of years ago, with real adoption across 140+ communities and tools like Sales 360 already lifting inquiry-to-tour and tour-to-move-in conversion. You're scaling through the Vi merger, and your 2026 wellness model points AI at giving staff time back for real resident connection. The next leap, genuinely AI-native with agentic AI on the foundation you've built, needs a leader who can steady the team, protect that momentum, and tie every model to business value while driving adoption in the field. That's the role I'd step into.

The plan

The first 90 days

Three phases: earn context, set the strategy with early proof, then deliver a measured win and a repeatable engine.

Days 0–30

Listen, learn, map the landscape

Earn the trust of the data & analytics team; protect momentum on Insight Advantage
Meet leadership, IT, governance, and the field operators
Go deep on Insight Advantage and Sales 360: what drives decisions, where it stalls
Audit data model, platform stack, governance, in-flight AI, team skills
Confirm the business outcomes AI should move; learn the Vi timeline

By Day 30: a steady team, protected momentum, a shared current-state + opportunity map, and an agreed definition of "AI-native" for LCS.

Days 31–60

Strategy + first quick wins

Draft the enterprise Data & AI roadmap, tied to business value
Prioritize use cases on top of Insight Advantage: agentic workflows, real-time pricing/amenity flags, move-in acceleration, staff-time-back
Stand up responsible-AI guardrails with the governance director
Ship one or two quick wins; map the team's growth into agentic roles

By Day 60: an approved roadmap, governance in motion, quick win(s) delivered, first agentic pilot scoped.

Days 61–90

Prove, operationalize, scale-ready

Launch the first agentic pilot; measure move-ins, margin, labor, time returned to residents
Establish the intake → prioritize → deliver → measure operating rhythm
Build the field adoption plan across 140+ communities
Align IT on next-gen AI architecture; fold in the Vi communities

By Day 90: a proven pilot with measured ROI, a scalable operating model, and a 12-month plan the exec team can rally behind.

How I'd operate

Guiding principles

Business outcomes first. Every initiative ties to move-ins, occupancy, margin, labor, or resident experience.

Build on what's working. Extend the foundation you've built — don't rip and replace.

Adoption is the real work. A capability nobody in the field uses is worth nothing.

Responsible by design. Governance, security, and ethics move with delivery, not after it.

A First 90 Days:
Helping LCS Become AI-Native