By Mack McKelvey
Luxury is an industry where details matter, restraint has value and judgment shapes every decision.
Leaders need to know which signals deserve attention, when to act and when a short-term opportunity could come at the expense of the brand.
That discipline is harder to protect as behavior shifts across markets and channels.
Merchandising, retail, ecommerce, finance and marketing teams often work from different versions of the truth, leaving leaders to assemble context after the window to act has started to close.
Adaptive decision intelligence is designed to close that gap.
By connecting internal performance data with external signals, it brings the most decision-relevant evidence to the executive responsible for the call. The goal is not to automate taste – it’s to give judgment better timing and context.
Mack McKelvey, CEO of marketing strategy firm SalientMG, spoke with Greg Genung, author of Squeezed: Reclaiming Time in the Age of AI and founder/CEO of Snowfire AI.
Snowfire is SOC 2 Type I and Type II compliant and describes isolated data storage with no external large-language-model training on organizational data. These controls keep access limited, reasoning inspectable and human accountability explicit.
Mr. Genung's argument: AI's greatest value is helping executives identify what matters, make better decisions and reclaim time for work only humans can do.
Here is the interview with Mr. Genung:
THE DECISION GAP
Do luxury executives have the real-time intelligence they need to make high-impact short and long-term decisions?
No. Not even close. They have plenty of information, but they lack the shared context that turns information into a decision.
A dashboard may show that full-price sell-through is down in one region, but it rarely explains how that relates to customer behavior, inventory, supply chain, margins and brand priorities.
Executives must assemble the story across meetings, spreadsheets and messages, often after the moment that mattered most.
That is the attention crisis I write about in Squeezed. Information abundance creates attention scarcity.
Information is not a signal, and intelligence is not a decision.
Value is created when a team understands what changed, why it matters, who owns the response and what happened next.
Luxury companies need that decision layer, not more dashboards.
What is adaptive decision intelligence, and how is it different from business intelligence, predictive analytics or a digital twin?
Business intelligence can tell a luxury leader what happened. Predictive analytics can estimate what may happen next. A digital twin can explore specific scenarios.
Each still leaves the executive to connect the answer to a decision and to guess about the downstream effects.
That distinction is particularly important in the luxury space because the most important signal is not always the largest one.
A subtle shift among a small group of top clients or growing demand for a limited product in one market may carry more weight than a much larger movement elsewhere.
Adaptive decision intelligence continuously monitors governed internal metrics and external signals. It recognizes when conditions deserve attention, routes a recommendation to the person with authority and preserves the evidence so the organization can learn from the outcome. It does not own the decision. It helps identify what needs answering now, what should inform it and who must make the call.
Greg Genung
Why should this be an urgent executive issue for luxury companies now? What has changed in the market or in customer behavior?
The speed of change has outrun the reporting cycle.
Luxury demand can move by geography, channel, category and client segment at once. A small number of high-value clients can change a market's performance, while cultural moments, trends, travel patterns, currencies and competitor actions alter the context before a monthly review is assembled.
AI is also making answers plentiful, creating more output for leaders to process. The scarce skill is deciding what deserves attention.
Companies that wait are allowing fragmented decision habits to become a competitive constraint.
In luxury, the real advantage is knowing which changes deserve attention and which don’t.
LUXURY JUDGMENT
Luxury is built on judgment, taste and discretion. How can an adaptive system support those qualities?
AI can compare and surface patterns at a scale no executive team can match. It cannot decide what a house should stand for, own a private-client relationship or accept accountability for a choice that changes the brand. Those remain distinctly human responsibilities.
Luxury leaders define the objectives, brand principles and non-negotiables.
Technology can show where evidence supports or challenges the current view, model consequences and make the reasoning traceable. That gives merchandising, finance and brand leaders a common context in which to exercise judgment.
Speed alone is not the competitive advantage. It is asking better questions and taking responsibility for the answer.
FROM SIGNAL TO ACTION
Walk me through a decision a luxury leadership team may be making today. How would the process change with adaptive decision intelligence?
Take inventory allocation. Useful context may be scattered across sell-through reports, ecommerce searches, boutique appointments, client-advisor notes, waitlists, returns, travel patterns and competitor activity. Individually, each tells only part of the story.
An adaptive system connects those inputs. It might find that interest in a category is accelerating among high-value clients in one city while full-price conversion weakens elsewhere. It can present options, such as reallocating a limited quantity, preserving scarcity while monitoring demand or supporting the market through clienteling. The team still decides. What changes is the time spent finding facts and the speed of learning from the outcome.
Which signals are luxury executives most likely to miss because customer, retail, ecommerce, finance, merchandising and marketing data sit in different systems?
The most valuable signals often live at the intersections.
A decline in store traffic may look unremarkable until paired with more appointment requests from top clients.
Product-page interest matters more alongside a waitlist, strong full-price conversion and a shortage in the nearest boutique.
A campaign may look efficient while returns or discount sensitivity weaken its economics.
Luxury leaders should be able to connect repeat purchases, client-advisor activity, browsing intent, sell-through, availability, returns, margin, event response and outside conditions.
The goal is not to monitor everything equally. It is to define the changes that matter and route them to the right owner.
Luxury has never been about more for the sake of more. It is about knowing what matters.
Mack McKelvey
Luxury demand can shift because of culture, geography or the behavior of a relatively small group of high-value customers. How does the system distinguish a meaningful change from noise?
A single movement should rarely trigger a major decision. Meaning comes from context, corroboration and materiality.
The system needs a trusted baseline, consistent metric definitions and decision conditions tied to a business objective. It should test whether a change persists, whether related signals support it and whether it crosses a meaningful threshold.
Segmentation is essential in luxury.
A small change among a strategically important client cohort may matter more than a large movement in anonymous traffic.
The system should also show its work: which sources contributed, how current the data is and what assumptions support the recommendation.
Adaptive intelligence should reduce false urgency, not manufacture it.
TRUST AND CONTROL
What would you say to a CEO who does not want an algorithm making brand-sensitive decisions or learning from private client data?
I agree with the premise: an algorithm should not own a brand-sensitive decision.
AI can analyze, surface signals and recommend an action, but the executive decides what matters and owns the consequence.
That boundary requires governance: role-based access, masking, audit trails, monitoring and data lineage.
Leaders should know where client data is stored, which models can access it and whether it trains an external model. These controls keep access limited, reasoning inspectable and human accountability explicit.
GETTING STARTED
Where should a luxury company begin, and what should the leadership team expect to prove in the first 90 days?
Begin with one consequential decision, not an enterprise-wide AI manifesto.
Choose one that recurs, crosses functional boundaries and has a measurable cost when it is late or poorly informed. Inventory allocation, client retention risk, margin protection or market prioritization can work if the owner is clear.
Measure decision latency, agreement on metrics, traceability and outcomes.
In 90 days, the team should prove that connected context speeds decisions, improves alignment and returns time to leaders. That operating change turns a use case into an executive capability rather than another tool.
LOOKING AHEAD
Two years from now, what will the luxury companies that invested early in adaptive decision intelligence be able to do that their competitors cannot?
They will have built institutional learning around decisions.
Most companies store data but lose the reasoning that connected a signal to an action.
An adaptive system preserves what leaders knew, which assumptions they made, who owned the call and what the outcome revealed. That decision memory compounds.
Early movers will recognize change sooner, coordinate functions around shared context and act before a signal becomes an obvious market fact. Their leaders can reclaim time from report assembly and repetitive analysis, putting it back into strategy, creativity, talent and client relationships.
The biggest gains will go to companies that challenge AI and apply human judgment where it creates the greatest value.
Luxury has always depended on knowing what to elevate, protect and hold back. Adaptive decision intelligence does not change that responsibility. Done well, it protects it.
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","iv":"014ab2588ed78ab19d386679c6734771","s":"0e4f4a01de0985a9"}