Insights from Jasper Carmichael-Jack, CEO of Artisan at 2025 SaaStr AI Summit
About Artisan: AI-powered sales platform building the end-to-end solution —from marketing personalization to AE automation across the entire revenue cycle.
They’ve rocketed to $6m ARR in just a few months. The latest AI B2B to go through hyper-growth.
While AI has exploded in coding (Cursor) and legal (Harvey) and parts of GTM (Clay), sales itself is still waiting for its breakthrough AI moment. Here’s why—and what’s coming next.
1. Sales Requires End-to-End Solutions, Not Point Tools
The Challenge: Code generation is elegant in its simplicity—input code request, output working code. Sales is messier. It spans marketing attribution, lead scoring, outbound sequencing, meeting booking, discovery calls, proposal generation, contract negotiation, and post-sale expansion.
The Current Reality: Most teams are using 8-12 different sales tools that don’t talk to each other:
- Outbound: Apollo/Outreach/SalesLoft
- Personalization: Clay/Lavender
- Meeting booking: Calendly/Chili Piper
- CRM: Salesforce/HubSpot
- Conversation intelligence: Gong/Chorus
- Proposal generation: PandaDoc/DocuSign
Why Point Solutions Fail: Data silos kill velocity. When your SDR tool doesn’t sync with your AE workflow, leads fall through cracks. When personalization doesn’t connect to conversation history, you sound robotic.
The Evolving Future: Single platform covering the entire revenue cycle—from first touchpoint to renewal. AI that learns from every interaction across every stage, creating compound intelligence rather than isolated automation.
Timeline Reality: True end-to-end platforms are 12-18 months away from market maturity. Early movers who consolidate now will have cleaner data and faster cycles when the technology catches up.
2. AEs Want to Sell, Not Admin—AI Will Handle the Rest
The Hard Data: Average AE spends only 28% of their time actually selling. The other 72%? Administrative quicksand:
- CRM updates: 14% of time
- Email follow-ups: 18% of time
- Scheduling coordination: 12% of time
- Proposal/contract admin: 16% of time
- Internal meetings/reporting: 12% of time
The Performance Gap: Most AEs are terrible at the non-selling stuff—and they know it. CRM data accuracy sits at 47% across most sales orgs. Follow-up email response rates are 60% lower when AEs write them vs. marketing-crafted sequences.
The AI Co-Pilot Solution:
- Follow-up Automation: AI analyzes call transcripts, extracts commitments, and sends contextual follow-ups within 2 hours
- Multi-threading Intelligence: Identifies all stakeholders from email patterns and LinkedIn activity, suggests optimal outreach timing
- CRM Hygiene: Auto-populates fields from conversation data, maintains deal progression accuracy above 90%
- Process Guidance: Real-time coaching based on deal stage, competitor analysis, and historical win patterns
ROI Projection: AEs with AI co-pilots close 34% more deals because they spend 65% more time in actual sales conversations. The math works: $200K AE salary + $50K AI tooling = $350K more revenue per rep.
Cultural Shift Required: Stop measuring AEs on activity metrics (calls made, emails sent). Start measuring outcome metrics (pipeline quality, deal velocity, win rate). Let AI handle the activities.
Yamini Rangan, CEO of HubSpot, echoed the same at SaaStr 2025:
3. Cultural Nuances Are AI’s Blind Spot (For Now)
The Localization Nightmare: LLMs trained primarily on English datasets miss critical cultural context that can kill deals:
German Market Example:
- Formal vs. informal “you” (Sie vs. du) – using the wrong form signals disrespect
- Business emails require specific opening/closing formalities
- Decision-making hierarchy is more rigid—bypassing proper channels kills momentum
Asian Markets Breakdown:
- Japan: Emails must follow specific honorific structures, indirect communication style
- China: Relationship-building precedes any business discussion, timing of outreach matters culturally
- Korea: Age and seniority heavily influence communication tone and approach
Current Workaround Strategy:
- Partner with local design partners in each major market
- Create region-specific prompt libraries that override base LLM behavior
- Human oversight for all culturally sensitive communications until AI improves
The Technical Gap: Base LLMs understand language but not context. “Thank you for your time” translates literally but may sound rushed in cultures where gratitude requires more elaborate expression.
Investment Reality: Companies serious about global sales need dedicated localization teams working alongside AI systems. Budget 20-30% more for international AI sales tools vs. domestic-only solutions.
Timeline for Improvement: Expect culturally-aware AI models by late 2025/early 2026 as training datasets become more globally representative. Early adopters building cultural intelligence now will have competitive moats.
4. The Testing Phase Is Over—It’s Time to Commit
The Pilot Purgatory Problem: Too many revenue leaders are stuck in perpetual “testing mode”—running 3-month pilots with 5% of their team while competitors scale AI across entire sales orgs.
The Proof Points Are In:
- Outbound Response Rates: AI-personalized emails: 8-12% response rates vs. manual emails: 2-4%
- Lead Qualification Speed: AI qualification: 2-3 minutes per lead vs. human SDR: 15-20 minutes
- Pipeline Velocity: AI-assisted deals close 23% faster due to consistent follow-up and process adherence
- Capacity Scaling: One human SDR + AI tools can handle the workload of 3-4 traditional SDRs
The Competitive Reality Check: While you’re piloting, your competitors are:
- Hiring fewer SDRs and investing savings in AI tools
- Responding to leads 10x faster with AI-powered routing
- Personalizing outreach at scale you can’t match manually
- Building proprietary datasets that make their AI better over time
The Implementation Framework:
- Month 1: Deploy AI for your highest-volume, lowest-complexity tasks (lead scoring, email sequencing)
- Month 2: Expand to medium-complexity workflows (meeting scheduling, basic qualification)
- Month 3: Tackle high-value, high-complexity processes (deal coaching, competitive intelligence)
ROI Measurement Standards:
- Cost per qualified lead: Should drop 40-60% with AI
- Time to response: Should improve from hours to minutes
- AE productivity: Should increase 25-35% in first quarter
The Laggard Penalty: Every month you delay implementation, your data gets staler while competitors’ AI gets smarter from fresh interactions. The AI advantage compounds—there’s no catching up later.
Perplexity’s CBO echoed the same again at SaaStr AI 2025:
5. Human + AI Collaboration Is the Future, Not Replacement
The Hybrid Intelligence Model: The future isn’t AI replacing humans—at least not strong sales execs. It’s AI amplifying human capabilities in ways that create exponential value.
What AI Handles (The Heavy Lifting):
- Research & Personalization: Analyzing 50+ data points per prospect in seconds (company news, tech stack, hiring patterns, social media activity)
- Scale Operations: Managing 1,000+ prospect sequences simultaneously with individual customization
- Process Adherence: Never forgetting follow-ups, always updating CRM, consistently applying qualification frameworks
- Pattern Recognition: Identifying buying signals across thousands of interactions that humans would miss
What Humans Own (The Relationship Building):
- Strategic Thinking: Understanding complex buyer politics and navigating organizational change
- Emotional Intelligence: Reading between the lines on calls, adapting to personality types, building trust
- Creative Problem-Solving: Crafting unique value propositions for complex deals
- Executive Presence: Commanding respect in C-suite conversations and high-stakes negotiations
The Productivity Multiplier Effect:
- SDR + AI: Can effectively prospect 10x more accounts with higher personalization quality
- AE + AI: Can manage 2-3x larger pipeline while maintaining relationship depth
- Sales Manager + AI: Can coach entire team with data-driven insights rather than gut feelings
Hiring Strategy Evolution:
- Stop hiring: Junior SDRs for manual prospecting tasks
- Start hiring: AI-savvy SDRs who can manage multiple AI tools and focus on relationship building
- Upskill existing team: Train current reps on AI tool management and strategic selling skills
The Competitive Advantage Math:
- Team A: 10 traditional reps = 10x human output
- Team B: 6 AI-enhanced reps = 15x human output + AI scaling
- Result: Team B handles 50% larger territories with 40% lower payroll costs
Culture Change Required: Sales teams must evolve from “activity heroes” (who makes the most calls) to “outcome heroes” (who drives the most revenue per hour invested). AI makes the activities scalable—humans make the outcomes meaningful.
Bottom Line: The Revenue Leader’s Playbook
The Window Is Closing Fast
While you’ve been testing, your competitors are scaling. The companies that commit to AI-first sales operations in 2025 will have an insurmountable 18-month head start by 2027.
The Math Is Simple:
- Manual SDR: 50-100 personalized emails/day
- AI SDR: 1,000+ personalized emails/day at higher quality
- AE with AI co-pilot: 40% more time selling, 60% less admin overhead
- Result: 3-5x pipeline velocity with same headcount
Your 90-Day Action Plan:
- Week 1-2: Audit where your team spends time (spoiler: 70% isn’t selling)
- Week 3-6: Pilot AI tools for your biggest time-sinks (prospecting, follow-ups, CRM updates)
- Week 7-12: Measure ROI ruthlessly—if it’s not 2x better than human performance, find a different tool
The Uncomfortable Truth: Your best AEs are already using AI tools informally. Your choice is to lead this transformation or have it happen around you.
The sales AI explosion isn’t coming—it’s here. The only question is whether you’ll be leading it or learning about it from your competitors’ case studies.
Stop testing. Start scaling. Your 2H numbers depend on it.
