AI for business performance.

AI as a performance layer. Better decisions, faster execution, measurable results.

I identify where AI improves performance, build working pilots hands-on, validate them with the teams who use them, scale what works and measure the business impact across the create and win lifecycle.

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Bethsabée Remus, fractional product marketing and innovation partner
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What I do

Most AI initiatives don't fail on technology. They fail on scope, adoption and value.

This is the operating model I use inside product, marketing and commercial organisations, drawn from a live AI-for-business-performance mandate in a global industrial group. Six steps, run in a loop, with business impact as the only scoreboard.

1. Identify high-value problems

Work with sales, product management, product marketing and marketing to find where time is lost and where quality breaks down.

  • Opportunity discovery across the commercial funnel
  • Value / feasibility / risk scoring
  • Prioritisation on business impact, not technical interest
  • Data, content and tooling readiness

2. Build prototypes, hands-on

Design and build working AI tools without waiting on IT. LLMs, automation and practical tooling applied to real problems.

  • Working pilots in weeks, not quarters
  • Engineering know-how and sales logic made accessible at scale
  • Guardrails, evaluation and cost/latency checks
  • Reusable components your teams can own

3. Validate in the field

Test with the people who will actually use the tools: sales teams, product managers, campaign managers.

  • Structured user testing and feedback loops
  • Kill what doesn't work, double down on what does
  • Adoption signals tracked from day one
  • Clear go / no-go decisions

4. Scale what works

Once a solution proves value, document it, train the teams and roll it out across business units and regions.

  • Playbooks, templates and training
  • Rollout across functions and geographies
  • IT involved only when enterprise-grade deployment is required
  • Ownership handed to internal teams

5. Measure business impact

Success is defined before anything is built, and reported to leadership with clarity.

  • Time saved on proposals
  • Faster pre-feasibility and qualification cycles
  • Improved opportunity qualification rates
  • Reduction in repetitive expert time

6. Build internal AI capability

The goal isn't just to ship tools. It's to raise the floor of what your teams can do with AI.

  • Workshops and hands-on enablement
  • Prompt, workflow and tooling playbooks
  • Responsible-AI principles and review paths
  • Data privacy and compliance checkpoints

Where I apply it

AI for business performance across the funnel, from discovery to closing

Identify → build → validate → scale → measure, applied at each stage of the business lifecycle rather than as isolated tool experiments.

01

Create business

GTM & opportunity, marketing excellence

Market intelligence, ICP definition, lead generation, positioning and content intelligence.

  • Lead classification and scoring
  • CRM enrichment with market signals and triggers
  • AI-powered account targeting and persona identification
  • Website conversion optimisation and campaign performance analytics
02

Win business

Order winning, commercial excellence

Copilots and assistants that shorten the path from qualification to a credible proposal.

  • Proposal generation assistants
  • Pre-feasibility and sizing copilots
  • Product selection advisors
  • Competitive intelligence and qualification support

Success measures

Defined before we build, reported with clarity

Measurable productivity and efficiency gains

Adoption across regions and functions

Number of deployed solutions with documented impact

Increased AI capability across the organisation

Reduced proposal generation and qualification cycle time

Faster access to engineering and expert know-how

Good fit

This is for you if…

You have AI on the roadmap

…but no shared view of which use cases deserve investment first.

You ran experiments

…that impressed in a demo but never became a growth lever. I help you scale the winners, stop the dead ends and turn AI into faster, better business performance.

You shipped an AI feature

…and now need positioning, adoption and proof of value. I help you build the rollout, messaging and metrics that make it a real growth driver.

Let's find where AI improves performance

Send an email and we'll pressure-test one performance opportunity together. You'll leave with a clear next step either way.

Book a call