We help retailers and consumer-goods companies determine where AI will materially change the economics of the business — and where it won't — then capture the value.
10X Decisions Supercharging transformation with AI
AI progress only matters when it becomes economic value.
The question is no longer what AI can do. It is where AI actually pays. We help retailers and consumer-goods companies find the workflows where AI materially changes the economics — and decide where to invest.
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01 The enterprise AI challenge
Possibility is accelerating. Absorption is not.
Access to AI is no longer the constraint. The constraint is knowing where it changes the economics — and building an organization that can capture the value.
02 What changes in an AI-native enterprise
Seven shifts. None of them are about the model.
01 / 07
03 Where to begin
From AI possibility to investment decision.
Our first engagement, Find Value, answers four questions in six weeks: which workflows are worth changing, what the value at stake is, what must be true to capture it, and what to pursue now, prove first, defer or stop.
6 weeksFixed scope
3–5Workflows typically shortlisted — where evidence supports it
1 decisionWhere to commit money, people and attention
04 How we evaluate an opportunity
Five lenses on every workflow.
Every workflow is tested through all five before it reaches a leadership decision. Find Value goes deep on the first two — Work and Worth — and maps what the other three imply.
First six weeks: Work and Worth in depth · the other three mapped
05 People and leadership
Technology changes what's possible. People decide what changes.
Workforce
"Which jobs will AI replace?"
How should work be redesigned when intelligence becomes abundant?
- Human + agent operating models
- Role decomposition
- Redeployment
Executives need decision capability — about capital, talent, risk and advantage.
- Board briefings
- Leadership sessions
- Executive AI Learning Series
06 Begin
Which of your workflows are worth changing?
01 The challenge
Possibility is accelerating. Enterprise absorption is not.
Most retailers and consumer-goods companies have dozens of possible AI uses. The hard part is knowing which will materially change the economics — and which won't. That gap is economic and managerial, not technical.
Thesis Read as you scroll
Enterprise examples Retail & consumer goods
Three examples. The same pattern.
Every function has pilots. Few have a redesigned workflow with an owner, a number and a decision behind it.
Four questions Executives keep asking
Why capability doesn't become value.
Failure modes Self-check
Which of these do you recognize?
Select every pattern you've seen in your own programme. The readout shows which dimensions of the enterprise are exposed.
02 Find Value · the first engagement
Where does AI actually pay?
We examine the workflows that drive revenue, cost, capacity and working capital, determine where AI can materially change performance, and quantify which opportunities deserve management attention.
Outcome A defensible investment decision: a prioritized shortlist of workflows — typically three to five, where the evidence supports it — with the economics of each, what must be true to capture the value, and a clear call on what to pursue now, prove first, defer or stop. If nothing clears the investment bar, that is the answer — with the reasons and what would have to change.
6 weeksFixed scope, fixed end date
3–5 workflowsTypically shortlisted — only where evidence supports it
1 decisionWhere to commit money, people and attention
Every opportunity is measured in
Where it goes deepWorkWorthquantified in depthWorkforceWorkbenchWatchmapped for what they imply
What we examine Eight questions · five lenses
How the six weeks run
From AI possibility to investment decision.
Examples of outputs What leadership holds at the end
Six outputs. One fact base.
Illustrative examples, drawn from the sample portfolio below. Every figure traces back to an input you can inspect.
What you receive A sample portfolio
A defensible decision — and a clear call on every workflow.
A credible answer has to be able to say an investment shouldn't proceed. Select a workflow on the map, then step through its nine parts.
"Fundable" means ready for the next funded stage — a proof or a build, with clear gates — not a blank cheque. Work and Worth are quantified in depth; technology, workforce and governance are assessed for feasibility and firmed up in Prove.
Interactive: click any point or workflow name to open its illustrative example, then step through all nine parts.
Illustrative retailer and consumer-goods portfolio · positions are sample scores, not client data
Worked economics Store replenishment exceptionsInspect the calculation. Change the assumptions.Every input visible, costs included, cash kept separate from capacity. An illustration, not a client result.Open the calculator
How we engage
A defined engagement. Not another strategy deck.
Fixed scope, fixed duration, and every time ask named up front. Our AI-native process carries the heavy analysis, so your people's time goes to the decisions.
Fixed scopeAgreed functions, executives and workflows before kickoff.
Six weeksEnding in an investment decision on a date agreed at kickoff.
Evidence-basedEvery number is graded. Some workflows are recommended to stop.
Vendor-neutralTake the outcome to any build partner. Fees are fixed and set by scope.
What we need from you
What you get instead of…
Who you'll work with
03 The approach
Possibility, economics, decision, execution.
The problem is no longer finding things AI can do. It is deciding where AI actually pays — and then capturing the value. Our approach follows the decisions leadership has to make.
How we evaluate an opportunity Five lenses · scroll or select
First six weeks: Work and Worth in depth · the other three mapped
The journey From your side of the table
Decide where to invest. Then capture it.
Supporting
Significant
Primary
Covered in the first six weeks
How we deliver AI-native, not a pyramid
An AI-native process, led by senior people.
AI runs through every step of how we work — so analysis that once took a team weeks takes days, evidence is broader, and more of our time goes to your leaders and the decisions in front of them.
Entry point
Begin where the economics are.
The first engagement answers where AI pays in your business, what it is worth, and what it would take — so leadership can decide where to invest.
04 Workforce
"Which jobs will AI replace?"
Role decomposition Interactive
Roles don't disappear. They decompose.
Choose a retail or consumer-goods role. Move the scenario slider to explore which tasks agents could take on, which become shared, and which stay firmly human.
Illustrative scenario · not a forecast
AssistDraftAct with reviewAct within limits
Task assignments reflect illustrative assumptions for a typical role. More agent involvement is not the goal and is not automatic — the right allocation is a design choice made with the people who do the work.
Human-led0
Human + agent0
Agent-led · human accountable0
Share of role time
What we work on Ten topics
The work behind the work.
Who we work with
Every leader brings a different question.
05 Executive programmes
You don't need to become an AI engineer. You do need to decide.
We work with executives on the strategic and organizational consequences of AI — the choices only a leadership team can make.
Decision capability Six domains
Where leaders need enough understanding to choose well.
The emphasis
Decision capability, not generic AI training.
What this isn't
- Prompt-writing workshops
- Tool demos and vendor tours
- Generic "what is AI?" primers
- Certificates of completion
What this is
- Working through your own capital and operating-model choices
- Shared vocabulary across the leadership team
- Scenarios tested against your industry and economics
- Decisions the group commits to at the end
Executive AI Learning Series
The highest-leverage move is often educating the people who decide.
Every AI investment passes through a leadership team. When that team shares a vocabulary and an honest view of what AI can and can't do, stronger workflows get funded — and weak ones get stopped earlier.
Better capital decisionsLeaders who understand unit economics and cost to run fund workflows, not demos.
Faster, cleaner governanceA shared view of risk and accountability shortens every approval that follows.
Adoption that sticksTeams follow leaders who can explain why the work is changing.
Session planner
Shape a session around your team.
Pick an audience, a format and up to three areas. The outline updates as you choose — then bring it to a first conversation.
Audience
Format
Areas
Draft outline
06 Insights
Notes from the work.
What we're learning about AI, value and work in retail and consumer goods.
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Executive overview Everything on one page
10X Decisions, in two minutes.
No scrolling story — just what we do, for whom, what you receive, who leads it and the next step.
CEOs, COOs, CFOs and CHROs, and the leaders of marketing, merchandising, supply chain, inventory and supplier management at established retailers and consumer-goods companies.
Find Value — where does AI actually pay?
Six weeks, fixed scope, fixed fee set by scope. We examine the workflows that drive revenue, cost, capacity and working capital, quantify where AI changes performance materially, and give leadership a fact base for deciding where to commit money, people and attention. It goes deep on Work and Worth, and maps what Workforce, Workbench and Watch imply.
- What changes?Which workflows are worth changing
- What is it worth?The economic value at stake
- What will it take?What must be true to capture it
- Is it worth doing?Pursue now, prove first, defer or stop
A defensible investment decision — typically 3–5 workflows worth funding, where the evidence supports it.
Each workflow comes with its economics (revenue, margin, COGS, labour capacity, working capital, cost to implement), the redesign, data needs, workforce impact, ownership, risks and a recommendation. A credible answer has to be able to say an investment shouldn't proceed — and if nothing clears the bar, that is the answer, with the reasons.
An executive sponsor, one or two participating functions, 5–8 executive interviews, read-only data by the end of week 1, four approval points, and around 8 hours of leadership time in total.
Full list →A small senior team with an AI-native process: faster, broader analysis, and more senior time on the decisions. Vendor-neutral, with no referral fees.
How it works →A 45-minute conversation about the workflows you're considering.
07 Contact
What are you trying to change?
Start with your situation. We'll come to the first conversation having thought about it.
Click to select one or more. Your choices shape the brief.
Who you'll talk to
The people who lead the work
Value delivered across clientsAkshay's work before 10X Decisions · clients not named · figures client-reported, shown as ranges
For procurement Supplier assurance