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AI & Commercial Teams
Expertise
AI Readiness for B2B Commercial Teams
Human-in-the-loop commercial work means AI handles data gathering, analysis and first drafts, while experienced people make the judgements, own customer relationships and stay accountable for decisions. Market Edge helps marketing, sales and key account teams redesign their work this way and build the skills it requires.
Problems we solve
Tools without a plan
Teams experiment with AI individually, with no shared approach or standards.
Signs, causes and fixes →Unclear roles
Leaders don't know which marketing and sales tasks will change, and which shouldn't.
Signs, causes and fixes →Risk with client data
No clear rules for what can go into AI tools.
Signs, causes and fixes →Skills gap
People need new skills to question, check and use AI output well.
Signs, causes and fixes →What we hear from clients
Paraphrased and anonymized from recent conversations with marketing and commercial leaders.
“People are trying AI tools on their own. We haven't scaled it into how marketing and sales actually work.”
“We built in about 30 hours a tool that used to take a team months. You still need domain experts to check it.”
“Marketing roles are being affected by AI sooner and more visibly than finance or accounting.”
How we help teams work with AI
Four steps, each supported by a proven Market Edge framework.
01
Assess AI readiness
Add an AI literacy dimension to the Commercial Capability Assessment.
02
Redesign the work
Map marketing, pricing and KAM tasks to AI-assisted and human-owned steps.
03
Build skills
Applied training on your own markets, using AI inside Market Edge frameworks.
04
Set guardrails
Data-handling rules and human review points for commercial decisions.
Our point of view
AI is a force multiplier, not a replacement for judgment. The value comes when teams know what good looks like, check AI output (sources, sanity checks, expert review) and build AI into shared processes rather than individual experiments. Curiosity, validation and trust-building remain the human differentiators, and those are what we help teams develop.
How an engagement usually runs
Typical phases. Every engagement is scoped with you, and many clients start with one phase.
| Phase | Typical timing | What happens |
|---|---|---|
| Assess readiness | 2–4 weeks | AI literacy added to the capability assessment, plus a review of current use. |
| Choose use cases | 2 weeks | Marketing, pricing and key account tasks where AI saves time without adding risk. |
| Pilot with guardrails | One quarter | A small group uses AI inside Market Edge frameworks, with review points and data rules. |
| Scale | By team | Training and updated processes for the wider commercial organization. |
Human in the loop
Where AI helps, and where people decide
We use AI in our own work every day. That experience is what lets us tell clients plainly where it helps and where it shouldn't be trusted alone.
How we use AI responsibly →AISpeeds up market mapping, account research and transaction analysis.
AIDrafts plans, value propositions and campaign content for review.
PeopleDecide strategy, price and targeting, and stay accountable for them.
PeopleBuild trust with customers and with leadership teams.
Client results
All case studies →“Market Edge's strategic frameworks and tools have been an instrumental resource for our strategic marketing team for years.”
Kraton
AI & Commercial Teams insights
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AI & Commercial Teams FAQ
Will AI replace B2B marketing roles?
It is changing them quickly. People are more likely to lose ground to colleagues who use AI well than to AI alone. Judgment, customer relationships and getting decisions made stay human.
What does human in the loop mean for commercial teams?
AI gathers data, analyzes it and drafts; people decide strategy, price and targeting, check the output and stay accountable for the result.
Which marketing and sales tasks should use AI?
Market and account research, transaction analysis, first drafts of plans and content, and summaries of customer interviews are good starting points.
How should we handle customer data in AI tools?
Agree which tools are approved, what data can be entered and where it is processed, and require human review before anything reaches a customer.
How do you train teams to use AI well?
On their own work, inside frameworks they already use, with clear examples of what good output looks like and how to check it.
Planning how your commercial team works with AI?
Book a 20–30 minute sounding board conversation with a senior consultant who has sat in your seat. No cost, no commitment.