Not every role goes away. Not every AI works without humans. But if you’re still running a 2021 sales org, you’re already behind.
I’ve been getting a ton of questions about what the sales team actually looks like in 2026. And I’ve been living it—we went from 10+ humans in sales at SaaStr to 1.2 humans and 20+ AI agents, with the same net productivity.
Here’s a number that should make every sales leader pause: we budget $500,000 for AI agents last year across 21 agents. We spent maybe $10,000 on our core CRM, Salesforce. Think about that ratio. We’re spending 50x more on agents than on CRM. That’s the new reality.
But here’s what everyone gets wrong: it’s not about replacing all humans with AI. It’s about understanding which roles AI can handle today, which ones it can’t, and how the org structure fundamentally changes.
Let me break it down role by role.
What AI Can and Can’t Replace Today: The Real Numbers
Email-Based Outbound SDRs: 95%+ Replaceable
This is the big one. If your SDRs are primarily doing email-based outbound—prospecting, sequencing, initial qualification—AI can handle 95% of this today.
We’re seeing 6% response rates from AI SDRs at SaaStr. That’s comparable to (or better than) most human SDR teams. Our AI agents have booked 130+ meetings since August through just one vendor (Qualified).
And our newest agent, Agentforce? 72% open rate and 10%+ response rate—on leads our team had completely ghosted. Those were contacts sitting dead in Salesforce that no human ever followed up with. Now they’re closing deals.
But … you still need humans managing and training these agents. Every. Single. Day.
The companies getting this right aren’t just “turning on AI.” They’re going deep:
- Segmenting contacts into batches of 800-1,000 max per campaign
- Creating sub-agents for each persona (CRO, CMO, churned customers, etc.)
- Training each sub-agent specifically for that persona and use case
- Giving each agent different goals (book a meeting, sell a ticket, follow up on ghosted leads)
If you truly go deep, train a platform, and orchestrate it daily, you can replace most classic human email-based SDRs with AI today. But you can’t just push a button.
Inbound BDRs That Screen Leaders: 95%+ Replaceable
This might actually be easier than outbound. An AI should be able to qualify an inbound lead faster and better than 95% of BDRs can. Today.
Think about it: 95% of human SDRs don’t really know the product they’re selling. They can’t answer a tough question from a VP of Engineering, a CPO, or a CIO. They have to wait until they can grab some human to help.
An AI SDR? It knows everything. Every feature. Every integration. Every competitive differentiator. It never forgets what was discussed last week. No sick days. No drama. No pretending to understand when it doesn’t.
AEs (Account Executives): Maybe 5% Today. But That Will Change.
Here’s where I differ from the “AI will replace everything” crowd.
I don’t think all sales roles can be replaced by AI yet. AEs? Maybe 5% now. But that will change.
The nuance matters here:
What AI can handle today:
- Lower-touch deals that could close on a text message
- Self-serve PLG motions with AI assistance
- Follow-up sequences and deal management
What AI still can’t do well:
- Complex multi-stakeholder enterprise deals
- Building genuine executive relationships
- Creative problem-solving in high-stakes negotiations
- Reading the room in tough conversations
But here’s the wake-up call for 2026: Everyone is going to be surprised how many fairly big deals close without a traditional sales exec.
Here’s what’s wild: I talked to a sales leader at an agentic AI company recently. I asked him how many figures are in his mid-market deals. I was thinking $20K to $50K, maybe $75K on the high end.
He said they’re all seven figures.
Seven figures. For mid-market. Because when you price AI based on labor replacement instead of software seats, the math completely changes. You’re not competing with Salesforce’s $150/seat. You’re competing with a $120K SDR salary.
I’m already seeing this at AI-native companies where significant deals get “closed” by solutions engineers and the like without the traditional AE even being much involved.
Customer Support: 50%+ Replaceable Today
You can replace 50% of your support team with AI today IF you invest. Gartner says 80% eventually—and that tracks with what I’m seeing.
But again, only if you go deep, train a platform, orchestrate it daily, AND create a very responsive human-in-the-loop escalation strategy.
Zendesk’s CEO told me their enterprise customers hit 60-80% automation with months of training, while self-serve gets 20%. HubSpot’s Customer Agent now resolves 50% of support tickets autonomously and cuts resolution time by 39%. Training matters more than the tool.
The Economics
The math is undeniable:
Human SDR:
- Base salary: $75K-$95K
- Benefits, taxes, overhead: Add 25-35%
- Total loaded cost: $100K-$130K annually
- Ramp time: 3-6 months
- Management overhead: Weekly 1:1s, reviews, coaching
AI SDR equivalent:
- Tool costs: $2K-$8K annually for basic; $50K-$100K for enterprise with FDE support
- Integration and setup: One-time, 20-40 hours of eng time
- Ramp time: Days to weeks (if you put in the training work)
- Management overhead: Prompt refinement, daily monitoring
For basic tools, we’re talking about 3x-15x cost reduction for 70-80% of the output. For enterprise-grade agents with FDE support, you’re looking at roughly equivalent cost to one human but with the ability to scale to 10x the volume.
Customer Success: 60%+ Don’t Add Value Anymore
We need better AI platforms here, but we don’t need 60%+ of the CSMs we have today.
CSMs that don’t solve problems and just do QBRs without adding true value are not necessary in the age of AI. You can probably move on from them today.
Engineering: Actually More Productive, Not Fewer
I’m not seeing that AI lets you reduce net headcount in engineering at all.
What I see is a 20%-40% productivity boost, net net. Far more for prototypes and proof-of-concept production.
But it becomes an arms race. Everyone is more productive, software is shipping faster, so you need more great engineers than ever. It’s a cracked arms race in product development today.
AI Isn’t Magic. Especially If You Don’t Put In The Work.
Klarna CEO Sebastian Siemiatkowski became AI’s most aggressive advocate. By late 2024, headcount dropped 22% to 3,500 through attrition. Their AI chatbot was supposedly doing the work of 700 customer service agents. They hit nearly $1M revenue per employee.
But in May 2025, Klarna reversed course. They started hiring humans again.
Siemiatkowski admitted: “From a brand perspective, a company perspective, I just think it’s so critical that you are clear to your customer that there will always be a human if you want.”
And the real kicker: “Cost unfortunately seems to have been a too predominant evaluation factor… what you end up having is lower quality.”
This is the “Klarna Effect”—companies bragging about efficiency gains, then quietly re-hiring when reality bites.
The lesson: AI can replace a lot. But not everything. And if you go too fast without the right human oversight and training, you’ll end up backpedaling. The goal isn’t to eliminate humans—it’s to redeploy them to higher-value work.
The New Roles That Mostly Didn’t Exist Two Years Ago
The GTM Engineer
This is the AI nerd on your team. They could come from marketing (technical marketers, HubSpot nerds, anyone who’s built complex campaigns). They could come from RevOps if they’re technical enough. They probably can’t come from your standard sales team.
Find the one GTM nerd on your team. Promote them. Have them own this. They’ll manage the orchestration—which contacts go to which agents, what CTAs, what follow-ups, what happens when leads close.
Forward Deployed Engineers (FDEs)
If you’re buying AI sales tools and the vendor won’t give you a dedicated FDE or solutions architect, don’t buy from them. No matter how slick their sales pitch.
A worse product with great implementation support beats a great product you can’t get working.
The current market reality: $100K+ just to get one agent operational ($50-70K to get started, plus another $25K for a forward-deployed engineer to set things up).
The $250K SDR Managing 10 AI Agents
The classic SDR role—sending emails, qualifying leads manually—is going extinct.
But the SDRs who can work with AI are becoming the most valuable people on the team. I’m predicting $250K+ SDRs who manage 10 AI agents and 10x their output.
The Great Rebalancing: From Pipeline to Post-Sales
The data backs this up: 36% of SaaS companies reduced SDR/BDR headcount in the past 12 months while simultaneously increasing Account Executives (28%) and Professional Services (34%).
This isn’t economic belt-tightening—it’s strategic optimization.
Companies are recognizing that:
- AI handles top-of-funnel better than mid-pack humans
- Complex deal execution still needs human AEs
- Implementation and customer success drive expansion revenue
The winners are reallocating resources from prospecting to customer success and implementation excellence—trading top-of-funnel quantity for post-sale quality.
About AI SDRs vs. Human SDRs
Let me be clear: the truly great people—your A+ players—they’re not going anywhere. They’re still few and far between. They’re still invaluable.
But B players? That’s a different story.
An AI SDR is much, much better than a human B-player. Almost always.
A B-level AI SDR over a B+ human who brings drama, politics, and unpredictability? That’s becoming an easy call for the AI SDR.
Because AI agents are always there:
- No drama
- No ego
- No politics
- No bad days
- No “I forgot”
- No “that’s not my job”
Just… there. Always. Consistently executing at a B level.
The delta just isn’t big enough anymore.
The 2026 Sales Org Structure
Here’s what I’m seeing work at AI-first companies:
Gone or drastically reduced:
- Traditional email-based outbound SDRs (replaced by AI + 1-2 humans managing)
- Inbound BDRs doing basic qualification (replaced by AI chat/voice)
- CSMs who just do QBRs and don’t solve problems
Expanded:
- Solutions Engineers running technical deep-dives before contracts
- Forward Deployed Engineers / Implementation Specialists
- GTM Engineers orchestrating AI agents
- “Super SDRs” managing fleets of AI agents
- Account Executives focused on complex deal navigation
New hybrid roles:
- Field Data Engineers assessing integration requirements
- Solutions Architects designing implementations with prospects
- AI Trainers who spend 30+ days per agent getting them into production
The Bottom Line for 2026
Many AI-first B2B startups can scale to $10M, $50M, even $100M+ without a traditional sales team.
But that doesn’t mean it will work for you if you have a sales-driven motion.
And it doesn’t mean having humans won’t help. Maybe they are FDEs, maybe it’s a few reps. But even the hottest AI B2B startups will benefit from humans assisting PLG and managing their AI Agents.
The 2026 sales team isn’t “no humans.” It’s different humans doing different things. But honestly, probably fewer humans in a traditional sales function at least.
