Boards don’t ask about AI. They ask about growth.
Consumer goods and food & beverage leaders are under pressure to move faster, protect margin, and get more value from the insights they already have. This advisory work starts where enterprise credibility starts—with the business outcome.
AI should make your commercial decisions sharper, not your operating model more complicated.
For CPG and food & beverage teams, the opportunity is not to “become AI-native” for its own sake. It is to reduce the distance between insight and action—faster readouts, clearer growth choices, better use of existing data, and stronger commercial judgment across Insights, Strategy, and Commercial teams. Mariana helps you find where AI can strengthen the workflows that already shape demand, margin, innovation, pricing, and portfolio choices. The work is advisory-led, not software-led.
Practical AI adoption starts with the decisions that already run your business.
Most enterprise AI conversations begin too far from the P&L—with tools, platforms, and pilots—before anyone has named the commercial decisions that need to get faster, sharper, or more consistent. Mariana’s work starts with the workflows behind your most important choices. This is not a software build; it is a practical redesign of how teams use information, judgment, and AI to support growth.
Map the decisions that matter
Identify the decisions where better workflow design creates commercial value—pricing, innovation bets, portfolio priorities, demand signals, promotion planning, and executive readouts. The goal is not to automate everything, but to find where the process slows down and where AI can improve speed or quality without weakening accountability.
Find where insight gets trapped
In most teams the issue is not a lack of data; it is the distance between available information and confident action. Research sits in decks, dashboards answer yesterday’s question, and strong signals get buried. Mariana surfaces those points of friction so the team can see where insight is delayed, diluted, or disconnected from the decision it was meant to support.
Redesign the workflow around business outcomes
Once the decision points and friction are clear, the workflow is redesigned around the outcome the business actually needs: faster cycle times, clearer recommendations, stronger alignment, and better use of existing data. AI is introduced only where it strengthens the workflow—always anchored to how the business makes money and protects margin.
Build leadership confidence before scaling
Adoption fails when teams are asked to trust outputs they don’t understand or measure activity instead of progress. Mariana helps leaders define what responsible adoption looks like for their function: where human judgment stays central, what good use looks like, and which outcomes to track before expanding.
Turn readiness into a focused next step
The first step is not a large transformation program—it is a clear read on where your team is ready, where the friction sits, and which workflow deserves attention first. A focused conversation about your current workflows and goals is the fastest way to get there.
For Insights, Strategy & Commercial leaders in CPG and food & beverage.
This work is designed for leaders close enough to the business to see where decisions slow down, but senior enough to know that another disconnected AI pilot will not solve the problem. It is especially relevant if you lead or influence:
- Consumer, shopper, category, or strategic insights
- Commercial strategy or growth strategy
- Brand, portfolio, innovation, or customer planning
- Analytics, foresight, or business intelligence tied to commercial decisions
- Cross-functional work between Insights, Marketing, Sales, Finance, and Operations
You may already have AI tools, or an enterprise AI agenda underway. The practical question remains: where should AI actually improve the way your function works? This is built for CPG and food & beverage teams where insight quality, speed, and cross-functional execution directly affect growth.
What this delivers — and what it doesn’t.
What this delivers
- Faster movement from data and research to usable recommendations
- Clearer connection between insight work and P&L priorities
- Better use of existing research, dashboards, and internal knowledge
- Less duplicated manual work across teams and projects
- Stronger executive confidence in how AI is being used
- More disciplined prioritization of where AI creates real value
- A sharper role for Insights, Strategy, and Commercial teams in growth decisions
What this is not
- A generic AI adoption program
- A software implementation or systems integration engagement
- A technical engineering build
- A replacement for your IT, data, or analytics teams
- A theoretical innovation lab exercise
- A broad transformation initiative with no clear owner
- A complicated operating model your team is not ready to use
The outcome is not a new technology identity—it is a stronger way of working. Your team keeps the judgment. Your leaders keep the accountability. AI becomes a practical lever inside the workflow, not a distraction from the business.
Start with readiness, not reinvention.
If your team is exploring AI but the path still feels broad or too far from commercial impact, the most useful next step is a focused conversation—not a broad transformation pitch. Together we can map where your workflows are ready, where they are strained, and where AI could help your team make better decisions faster.
What enterprise leaders ask first.
No. This work is useful whether your team is experimenting informally, working within a broader enterprise AI agenda, or still trying to understand where AI belongs. The starting point is your workflow, not your tool stack.
The work is advisory-led. Mariana helps you identify where AI can improve decision quality, speed, and clarity, then redesign the workflow around the business outcome. If a build partner or internal team is needed, the work defines what should be built and why.
Training builds awareness. This work is about business application—the decisions, handoffs, bottlenecks, and recurring work inside your Insights, Strategy, or Commercial function.
Because the perspective is built from inside the category reality: brand pressure, innovation cycles, customer complexity, margin tradeoffs, and executive expectations. That operator context shapes how AI adoption is approached.
Book a call. A short conversation about your current workflows and goals gives you a practical read on where your team is ready, where the friction sits, and which workflow deserves focused attention first—with no obligation to go further.