🏔️ The AI Mountains in Sales – What the Study Shows and What to Do Now
The study "Mastering the AI-Mountains in Sales" (RUB, May 2025) maps how companies use AI in sales. It measures impact and shows what speeds up the climb. The mountain image helps: First understand, then take the next step. This article brings numbers, examples and immediately usable steps.
!INFO: Source and Authors - SMD Results Report – Mastering the AI-Mountains in Sales (Bochum, May 2025). Authors: Prof. Dr. Jan Wieseke, Prof. Dr. Christian Schmitz, Kiram Iqbal, Marcel Keen. Contact: 0234-32-26596 | [email protected].
📊 The 5 AI Levels in Daily Sales
The levels build on each other. Skipping is not possible. AI starts at level 1.
• 0 Traditional - Analog technologies like phone, mail • 0.5 Basic Digitization - Video conference, email • 1 Informing AI - Human acts, AI delivers info. Example: Web and market analysis tool, CRM insights • 2 Predictive AI - Human uses AI predictions. Example: Lead scoring, churn risk • 3 Advisory AI - Human gets AI recommendations. Example: Generative AI tool, price recommendations • 4 Delegating AI - AI takes over partial tasks. Example: Automated proposal creation • 5 Autonomous AI - AI acts independently. Example: Fully automatic price negotiation
📍 Where Companies Stand Today
Many are only halfway up: 42% Beginners, 38% Professionals, 20% Champions. 80% are still in the first half of the journey. The focus of usage is in presales. Sales interaction and after-sales are catching up.
📊 What It Brings – Performance vs. Beginners
| !HIGHLIGHT | Metric | Professional vs Beginner | Champion vs Beginner |
|---|---|---|---|
| Revenue | +9.2% | +23.0% | |
| Growth Goal Achievement | +7.9% | +19.1% | |
| Target Market Share | +11.1% | +25.7% | |
| Market Share Growth | +10.2% | +22.1% | |
| New Customer Acquisition | +12.0% | +22.4% | |
| Existing Customer Revenue | +4.8% | +17.3% | |
| Cost/Efficiency Goals | +10.7% | +20.6% | |
| Efficient Resource Use | +11.4% | +24.1% | |
| More Output with Less Input | +10.1% | +23.7% | |
| Cost Reduction Potential | +9.9% | +23.4% | |
| Profitability | +10.4% | +23.0% | |
| Total | +9.8% | +22.2% |
The effect grows disproportionately with each level. Champions are about 135% above Professionals - measured by distance to Beginners.
⚠️ Setbacks Are Part of It – and Teach
!WARN: About 40% of AI projects fail. This is normal. With experience, success rate rises strongly: from 26% without experience to up to 76% with high experience. The learning curve flattens later. Plan buffers for learning and fine-tuning.
🌉 The BRIDGE Levers – Six Controls in the Company
Six internal levers speed up the climb. Those who use 3 or more usually reach Professional. 5 to 6 levers often lead to jumps.
• Data Governance - Build and maintain clean data foundation • Marketing Agility - React quickly to market changes • Top Management Support - Give direction, remove blocks • Innovation Capability - Test and anchor new methods • User Empowerment - Enable users to apply AI themselves • Technical Skills - Build team capabilities
!TIP: Rule of thumb - 0-2 levers: slow progress. 3-4 levers: Professional. 5-6 levers: steep rise to 71-80% progress.
⛈️ STORM – When the Market Gets Rough
External factors work like weather in the mountains. High industry digitization, fast technology changes, hard-to-plan customer needs, strong rivalry and growth increase pressure - and promote AI progress. The effect ranges from +6 to +20 percentage points per factor. Use the momentum when the market pulls.
📋 Practical 30-60-90 Day Plan
Day 0-30: Understand and Set Focus
!CHECKLIST: Phase 1 Tasks • Draw value map per process: Presales, Sales Interaction, After-Sales • Measure maturity level: Where do we stand on 0-5 per process • Define 3 quick wins: 1 per process, with clear metric • Start data inventory: Sources, quality, gaps • Win sponsor: Set C-level patron
Day 31-60: Build and Test
!CHECKLIST: Phase 2 Tasks • Pilot two use cases: e.g. lead scoring and proposal creation • Define guardrails: Data protection, quality checks, approvals • Enable team: short learning sprints, do-it-yourself guides, office hours • Make metrics live: Dashboard for impact, costs, risks
Day 61-90: Scale and Secure
!CHECKLIST: Phase 3 Tasks • Roll out successful pilots. Standardize processes • Hand over to business units. Name product owners • Sharpen BRIDGE plan: Build missing levers specifically • Put budget on permanent basis. Fix quarterly review
🧠 Nudges from Behavioral Economics – Getting Movement
Small nudges help new things become habits.
!EXAMPLE: Proven nudges for AI adoption • Set standard: AI recommendation is default, human can override • Reduce friction: One-click start for pilots, clear templates • Show social norm: Team score "AI in use" in weekly • Give instant feedback: Mini bonus or visibility with usage • Use pre-mortem: "How could the project fail?" before start
📊 KPI Set for the Climb
• Pipeline Quality: Share of qualified leads, time to response • Close Rate: Win rate per segment, deal cycle • Customer Value: Existing revenue uplift, churn rate • Efficiency: Cost per close, time per proposal • Quality: Hallucination rate, error rate, manual corrections
🛠️ Minimal Tech Stack for First 90 Days
| !COMPACT | Component | Purpose |
|---|---|---|
| Data Workspace | Connect sources, clean, document | |
| Generative AI Tool | Texts, proposals, emails, meeting prep | |
| Analytics/BI | Make metrics visible, measure impact | |
| Workflow/Automation | Trigger tasks automatically | |
| Governance | Policies, logging, approvals |
👥 Roles and Routine – Who Does What
• Product Owner Sales: Vision and roadmap • Data Lead: Data quality, interfaces, catalog • AI Enablement: Training, templates, support • Business Owner per process: Presales, Sales Interaction, After-Sales • Legal/IT: Guardrails, security, compliance • C-Level Sponsor: Remove obstacles, make success visible
⚠️ Common Pitfalls and How to Avoid Them
!WARN: Frequent pitfalls to avoid: • Starting too big - Better: one clear use case, clear number, 6 weeks • Unclear data - Better: data contract per source, name responsible persons • Tool focus instead of problem focus - Better: first value chain, then tool • No change - Better: nudges, defaults, live dashboards • No success measurement - Better: before-after metrics, A/B approach