EME·Strategy PARIS · WORKING ANYWHERE

Operational AI adoption · Any sector

Make AI useful where work
actually happens.

EME-Strategy helps business teams turn operational friction into concrete AI use cases, adoption programs and functional POCs that teams can actually use.

Book a discovery call → See how the method works

15 years in B2B SaaS· Operator-built· Champion workshops· Shipped in two weeks· Cross-sector· No conflict of interest· Built. Handed over. Yours.· Paris · Working anywhere· 15 years in B2B SaaS· Operator-built· Champion workshops· Shipped in two weeks· Cross-sector· No conflict of interest· Built. Handed over. Yours.· Paris · Working anywhere·

The diagnosis
May 4–11, 2026

The bottleneck in enterprise AI adoption is not model capability or licensing terms: it is the absence of engineers who can translate a generic API into the way a business actually works.

On May 4, 2026, Anthropic and OpenAI both launched dedicated services ventures ($1.5B+ in capital combined) explicitly to embed engineers inside operating companies. Their thesis: the consulting industry is too slow to capture the next wave of AI adoption. The labs are vertically integrating into services.

Sources: Fortune, CNBC, Vanderbilt Report.

The territory

Generic AI does not know how your business actually works. EME-Strategy sits at that gap.

AI platforms

Models, tools, APIs, integrations.

The gap

Turning capability into usable business workflows.

Business operations

Sales, presales, CS, reporting, QBRs, account plans, approvals.

The forward-deployed engineer model from the labs solves the integration layer. It does not change how a Sales team writes its next proposal, or how a Presales engineer responds to next week's RFP. That is a different job, with a different profile.

01 / The real bottleneck

Start with the friction,
not the technology.

Most AI opportunities inside an organization are not obvious. They are hidden inside slow handoffs, manual tasks rebuilt from scratch, knowledge concentrated in one person, or decisions that always take too long because the right context is never assembled in time.

The question is not which AI model to use. The question is where work gets stuck, who carries that friction, and whether a concrete AI system can make it faster, clearer or more reliable.

Answering that question requires someone who reads business operations quickly, speaks the language of commercial teams, can qualify which use cases will actually land, and knows how to activate adoption in a single session.

That is a different profile from a technical integrator. It is an operator who has spent fifteen years inside the workflows that AI is now supposed to improve.

of generative AI pilots fail to move beyond the experimental phase. (MIT, 2026)

of organizations have not redesigned jobs or workflows around AI capabilities. (Deloitte State of AI, 2026)

0:6

For every dollar enterprises spend on AI software, they spend six on services. That ratio is where adoption is won or lost.

02 / The guide

Built by an operator,
not a forward-deployed engineer.

EME-Strategy is an independent practice built on fifteen years inside B2B SaaS commercial functions, spanning Sales, Presales, Professional Services, and GTM strategy across enterprise software and platform companies.

The work is to build operational AI systems that B2B commercial teams can run from day one. Pre-configured Claude Projects per function. Champion workshops on real work. Use cases scored, validated, and handed over with the tools to operate them.

No certification programs. No 80-slide playbooks. No conflict of interest with any AI platform vendor or systems integrator. Built. Handed over. Yours.

Background

Enterprise SaaS · Platform companies · Life sciences

Functions

Sales · Presales · CS · GTM

Currently active

12-week engagement · listed B2B SaaS

03 / Two ways to work together

One AI transformation partner.
Two levels of engagement.

Both engagements start with identifying the friction. The scope changes depending on how much of the organization needs transformation: a structured program across functions, or a focused fix for one specific workflow.

AThe strategic engagement

Internal AI transformation, function by function.

For organizations with AI ambitions and operational friction across departments. A structured engagement to identify business frictions, activate champions, qualify use cases, build a POC portfolio and measure adoption across Sales, Presales, CS or Operations.

ForEnterprise & scale-up commercial teams

Format12-week blocks · ~half-time

OutputChampion activation, POC portfolio, adoption measurement, IT-ready use case briefs

Customer story B2B software

B2B software Internal AI transformation Champion-led adoption POC portfolio

"From scattered AI experiments to a structured transformation program."

Challenge

AI opportunities existed across departments, but initiatives were fragmented, unevenly framed and difficult to prioritize.

Engagement

An internal transformation program combining champion activation, use case qualification, functional POCs, adoption measurement and executive-ready reporting.

Impact

A growing portfolio of prioritized AI use cases, with adoption tracked through champions, usage signals and business feedback.

Example POC shown: account planning workflow.

10-15 POCs

Multi Functions

Champions Adoption

Live Roadmap

Active engagement · impact measurement in progress

See the method →

BThe operational fix

One painful workflow. One concrete fix.

For one specific operational pain. A focused engagement to identify the friction, qualify the right response, and deliver a usable workflow, automation, dashboard or lightweight app in under two weeks. Deployed and yours.

ForSMBs, any sector

FormatOne-shot · under 2 weeks

OutputA deployed web app, automation, generator or template

Customer story Luxury retail

Luxury retail Operational fix Execution data

"From WhatsApp coordination to boutique-level operational visibility."

Challenge

Boutique openings and field feedback relied on local habits, WhatsApp loops and manual trackers.

Engagement

A lightweight operating tool for boutique openings, feedback loops, review collection and HQ visibility.

Impact

Operational retail efficiency and experience consistency, measured through execution data.

J-60 Opening checklist

1/1/1 Owner · due date · status

Live Boutique progress view

QR Review flow by boutique

Active project · operational impact measured through execution data

See what gets built →

A · The strategic engagement: the method

Identify the friction. Shape the use case.
Make adoption measurable.

Every engagement follows the same three movements: map where work actually gets stuck, qualify which AI response will land with the team, then build and activate with adoption tracked from day one.

Map the work

Read the business workflow directly with the team. Surface friction points, frequency and data available. Determine whether the use case is ready to build or needs further qualification.

2–3 days preparation

Qualify and build

Work with the champion on their actual tasks. Score the use case against business impact, data readiness and adoption risk. Build the first functional proof with the team, in one session.

1–2 workshops

Measure adoption

Use case documented and prioritized. POC handed over or briefed to IT. Adoption baseline set. Active use cases enter a measured production track with champion usage as the signal.

5 working days

Concrete output

From vague AI ambition to concrete business usage. Four steps. No detour.

Step 01

Pain capture

Workshop with the champion on their actual work. Friction surfaced, frequency scored.

"Sales rewrites the same RFP answer 4× per quarter."

Step 02

Use case scoring

Business impact, data readiness, implementation effort. Three categories, clear gates.

"Cat. A · public data · ready to build now."

Step 03

PoC built

Claude Project configured with company context. Champion co-builds, validates output.

"Account brief generator · 6 min · production-ready."

Step 04

Industrialization brief

Functional spec handed to IT. Data sources documented, constraints listed.

"Brief handed to DSI · scoped for sprint backlog."

The missing role

The missing role sits between business pain, AI capability and operational adoption.

The Champion stays the operator. EME-Strategy orbits, bringing pain capture, process insight, data readiness, and use cases into the same workspace. No new role to hire. No platform to learn from scratch. Just the right four pieces, connected at the right moment.

B · The operational fix: building blocks

Most AI opportunities fall into
a few operational patterns.

Across sectors, the same frictions recur in different forms. A handful of reusable AI patterns covers most of them, which is why a concrete fix ships in days, not months. Here are the patterns activated most often.

What you get is not a report. It is usable AI in operation.

Adoption program Functional POC Workflow Dashboard Automation Generator Lightweight app

Interactive checklist

A process living in one person's head, turned into steps with owners and progress tracking.

Store opening, J-6 months → launch. Client file assembly. Employee onboarding.

3-day brief → 20-min guided flow

Financial simulator

Variable inputs, calculated outputs, exportable result. The decision made on numbers, not gut.

Lease vs. buy TCO. Project break-even. Borrowing capacity + notary fees.

2-day decision → answered in one session

Document generator

A form that turns inputs into a clean, branded, laid-out PDF. Every time, in seconds.

Quotes, engagement letters, term sheets, visit reports, handover records.

Rebuilt from scratch each time → 4-min output

Multi-entity dashboard

Scattered KPIs aggregated into one consolidated view, plus a per-entity drill-down.

Store performance. Case pipelines. Agency reporting. Subcontractor scheduling.

Weekly manual assembly → always current

Score & qualification

A short questionnaire that returns a score plus the points that need attention.

Deal financeability. Tenant file strength. Process maturity. Lead routing.

Qualification call needed → answered by form

Smart form & automation

Conditional logic that routes, generates, or triggers: follow-ups that actually get sent.

Prospect qualification. Client intake. Quote follow-up at D+7. Renewal reminders.

Follow-up forgotten → triggered automatically

Built across Retail Leasing & B2B finance Legal Construction & trades Associations Healthcare Real estate Recruitment & HR

04 / What's at stake

Two trajectories.
One choice.

Without the bridge

The platform is bought. License renewed. Champions self-selected, frustrated by tools that don't match their work. Pilots stall. The CFO asks what the investment produced. Nobody has an answer that survives the meeting.

A year later: another vendor swap, another rollout, the same gap.

With the bridge

One champion per function, autonomous within 30 days, building peers' use cases laterally. A use case library that grows every two weeks. Validated PoCs entering the IT backlog with documented briefs.

The CRO walks into the QBR with adoption data. The CEO walks into the board with named outputs.

Active engagement · 2026

A twelve-week activation inside a publicly listed B2B SaaS company.

Direct partnership with the DSI as Program Head and the CRO as Commercial Sponsor. Champions activated across Sales, Presales, Marketing, and Customer Success. Three parallel streams: business adoption, RevOps data readiness, IT platform industrialization.

Each engagement matures the asset base: pre-configured Claude Projects per function, the workshop framework, the use case scoring methodology. Faster deployment with each next client. A compounding library.

Client name available under NDA on request.

Output 01

Champions operating independently on ≥1 use case within 30 days

Output 02

Use case library seeded, cross-pollinated bi-weekly across departments

Output 03

Functional PoCs with documented briefs entering the IT industrialization backlog

05 / Start

Bring one business friction.
Leave with a clearer AI use case.

A first call works best with a real business pain on the table: something slow, manual, repeated, unclear or stuck in one person's head. We will help clarify whether it should become a workflow, a POC, an automation, a dashboard or an adoption track.

Book the call → Or just say hello

Make AI useful where work actually happens.