Meeting Summary
What We Heard
Brigitte's core motivation is efficiency, not FOMO. She doesn't want the answer to every growth problem to be "more headcount." The organization is doing a lot of manual, dated analysis work — and she wants to teach the team to work smarter using AI before the headcount requests pile up.
Julianne's initial framework proposed three 90-day buckets: AI literacy and individual productivity, optimizing the existing tech stack's AI features, and data governance/cleanup. She also proposed an AI Ambassador program across departments. The CMO (Emma Lawson) is already experimenting — they used AI on the Kendall campaign but didn't publicize it.
The key pivot in the conversation: The conversation pivoted from leading with organizational change and AI literacy toward discrete, high-leverage business problems first. The three business problems that surfaced organically: inventory/demand planning, marketing optimization & discoverability, and clienteling across DTC channels.
Core Recommendations from the Call
Recommendations
Start with discrete business problems, not organizational change
Don't try to make everyone "AI native" out of the gate. Focus on 2–3 high-leverage problems where AI can both accelerate revenue and delay headcount. Organizational change will follow naturally once people see results in their own workflows.
Go full-stack on Claude — drop Copilot
Copilot is a hobbled intermediated product. If you want the best reasoning and output, you can't run a hobbled tool next to a productive one. Claude from Anthropic is the current best-in-class for enterprise. Claude's MCP connectors effectively act as a data lake — you don't need to build one separately.
Hire a CIO — and make their first hire an AI person
A consultant is fine as a bridge, but this requires someone inculcated in KHAITE's culture, team, and workflows. The current "consultant CTO" model isn't sufficient. A CIO with an AI-focused first hire is the right sequence.
Be cautious on cost — consumption models have no controls
Stripes runs at ~$40K/month in token spend with strong governance. Without controls, people will plan weddings and hack restaurant reservations on the company's dime. Another argument for focusing on discrete business use cases vs. a blanket rollout.
Stripes Head of AI will be a resource for KHAITE
Once the Head of AI is onboarded (target: next 30 days), they can serve as a sounding board immediately and validate what consultants like Jake or Nick are proposing. Longer-term, potential for a secondment to KHAITE.
Agreed Priority Areas
Where to Focus First
Priority 1
Inventory & Demand Planning
Brigitte called this the area that "can make or break" the business. Size-level inventory liabilities, category complexity (new product ships monthly), and multi-channel/multi-geo distribution as Japan launches — all create massive AI leverage for smarter buys and protecting the 85%+ full-price sell-through.
Priority 2
Marketing, Content & Discoverability
With marketing spend up 48% to $18M, AI can stretch those dollars — content variants, ecom imagery, post-production workflows. Emma is already exploring vendor capabilities and LLM-based discoverability/GEO for the website redesign. Reformation's site reskin "is fueling" their growth.
Priority 3
Clienteling & Customer Intelligence
With DTC at 40% across five stores plus ecom, dispersed clientele across geographies and channels is growing fast. AI-powered per-client insights could meaningfully improve store economics — especially as Japan launches and new doors open.
Market Context
What Luxury Peers Are Doing
Burberry — Penguin
Gen-AI clienteling platform, 3 data scientists, natural language product search. 24% ATV uplift.
LVMH — MaIA
Company-wide AI agent, 2M+ requests/month. Advisors use enriched profiles for personalized outreach.
Brunello Cucinelli
Built proprietary "Callimacus" AI ecom platform. Conversational search. Closest comp to KHAITE.
Balenciaga — Intelo.ai
Agentic AI for merchandising. Agents as "digital teammates" resolving inventory challenges autonomously.
Ralph Lauren — Ask Ralph
AI styling assistant on Azure OpenAI. Trained on brand imagery only. Informs demand forecasting.
PVH (CK & Tommy)
OpenAI partnership for product design, demand planning, inventory optimization & customer engagement.
Revised Roadmap
What Happens Next
Now — Next 30 Days
Foundation
Evaluate and onboard Claude Enterprise, replacing Copilot as the primary AI platform. Begin scoping an inventory/demand planning AI initiative (Julianne flagged a new AI-driven tool to explore). Continue CMO-led marketing AI experimentation. Meet with Jake and Nick — validate with Stripes Head of AI once onboarded.
30–90 Days
First Wins
Deploy AI-powered demand forecasting on the highest-leverage SKU/channel combinations. Launch marketing content production workflows — copy, social variants, ecom imagery. Begin website discoverability/GEO optimization with Emma's team. Start CIO search process.
Q3 2026
Scale & Hire
CIO onboarded — first hire is an AI-focused person. Stripes Head of AI available for deeper engagement (validation, secondment model). Expand demand planning AI across all channels and geographies including Japan JV prep. Build clienteling intelligence for retail associates.
Q4 2026+
Strategic Platform
Unified customer data layer with AI segmentation across DTC + wholesale. Inventory optimization protecting full-price sell-through at scale toward the $250M FY28 target. Evaluate broader AI literacy program — after business results prove the value internally.
Guiding Principle
Don't change the culture to adopt AI. Solve business problems with AI, and the culture will change itself. Start with the three areas Brigitte and Julianne identified — inventory, marketing, clienteling — and let results drive adoption. The organizational literacy and ambassador programs come later, once the team has seen what's possible.
Action Items
Immediate Next Steps
KHAITE: Evaluate Claude Enterprise
Begin the process of standing up Claude as the primary AI platform. Assess MCP connector availability for existing tools (Sage, Greenhouse, Gorgeous, etc.).
Owner: Julianne & CTO
KHAITE: Scope the inventory/demand planning initiative
Julianne mentioned a new AI-driven inventory tool — evaluate it against the demand forecasting need. Size the business impact.
Owner: Julianne & Merch team
KHAITE: Meet with Jake & Nick; compare approaches
Evaluate both consultants. Once Stripes Head of AI is onboarded, loop them in to validate the recommended approach.
Owner: Brigitte & Julianne
KHAITE: Begin CIO search
The current consultant CTO model is insufficient for the AI transformation ahead. CIO's first hire should be AI-focused.
Owner: Brigitte
Stripes: Connect Head of AI with KHAITE post-onboarding
Sounding board immediately. Validation of consultant proposals. Longer-term: potential secondment model.
Owner: Jason