The Future of
GTM in the

Age of AI - Sales

We are launching a 3-part series in partnership with several of our VC partners to discuss the future of Sales, Marketing, and Customer Success in the new world of AI. The goal is to lay out a groundwork and ideas on how startups can scale their GTM function, who the best people for it are, and what GTM teams will look like in the not-so-distant future. We want this to be a blueprint for both startups and our talent pool to think about where they can fit in in this new age of AI.

Welcome to Part 1

Sales

Part 2 Customer Success
Part 3 Marketing

Coming soon...

Early 2000s

Enterprise Field Sales Dominance

In the early 2000s, enterprise field sales was dominated by relationship-driven, Rolodex-heavy sellers, often veterans from IBM or Oracle. These small, highly compensated teams managed large territories, operating through long sales cycles that relied on in-person meetings and white-glove, consultative approaches. At the time, CRMs like Salesforce were only beginning to emerge, and sales processes had minimal automation.

Profile

Volume Sales

Relationship-Based Sales

Solutions Sales

Structure

Small Teams

Siloed & Large Territories

Large Teams

Motion

Short Sales Cycle

White-Glove Consultative Selling

Long Sales Cycle

Tools

Minimal Automation

Fully Automated

Late 2000s to Early 2010s

Rise of SaaS & Inside Sales (Salesforce)

In the late 2000s, enterprise field sales shifted with SaaS and inside sales. Traditional sellers were replaced by agile teams using technology. Equipped with tools like Salesforce, they managed territories efficiently, shortening sales cycles and favoring virtual meetings. Automation streamlined processes and transformed customer relationships.

Profile

Volume Sales

Solutions Sales

Structure

Small Teams

Large Teams

Segmented & Inbound-Heavy

Motion

Short Sales Cycle

Long Sales Cycle

Heavy Phone/Email Outbound

Tools

Minimal Automation

Fully Automated

2010-2022 (Pre-AI Surge)

Remote + Revenue Efficiency Focus

In the years leading up to the AI surge, our focus was on enhancing remote work and maximizing revenue efficiency. We implemented strategies that streamlined operations and improved productivity, setting the stage for future advancements.

Profile

Volume Sales

Solutions Sales

Digitally Native

Structure

Small Teams

Large Teams

Full-Funnel Integration

Motion

Short Sales Cycle

Long Sales Cycle

Self-Service & Insight-Led

Tools

Minimal Automation

Fully Automated

Now that brings us to today. We will talk about where teams are today vs where they are going in the next year or two.

Today - 2023-2025 the Renaissance

Let’s call this period the Renaissance, a return of the early 2000s enterprise-level seller, sometimes from tech, sometimes from Big Four consulting, sometimes from industry, but with some notable differences.

Profile

Volume Sales

Solutions Sales

Structure

Small Teams

Large Teams

Motion

Short Sales Cycle

Long Sales Cycle

Tools

Minimal Automation

Fully Automated

Tomorrow

The AI Evolution

1.

We have forgotten how to build trust and it starts with building relationships

In the last 20 years we have focused so heavily on efficiency, one size fits all models, scale, and growth that there are very few people or organizations who know how to build trust. What does this mean in practical terms? In the new age of AI, most sales are enterprise-level, complex, solution-based, and rely heavily on input data from clients. That last piece, data, is crucial. It is estimated that only 20% of an enterprise company’s processes are actually written down, which means 80% lives in the minds of the team. During a POC, an AI agent is only able to access about 20% of the intrinsic data, which will cause many POCs to fail since data is the crux of AI. Reps who can extract this data by building trust and deep relationships with the team will be the ones who thrive in this new market.

2.

The technical buyer era and how to sell to them

The most notable difference between the future and the early 2000s in these large, slow, enterprise, relationship-driven motions is the buyer persona. On average it will be a very technical person who does not want to attend a dinner, grab drinks, or go to your event unless there is networking with their ICP. Building relationships will center on the value you as a seller can provide and your understanding of their pain points and solutions that are equal to or better than what the buyer already has in place.

3.

AI is going to shrink the noise in the tech ecosystem and therefore create a much more streamlined sales motion

There will not be large-scale cold outreach campaigns. The matching of problem to solution will become so precise that reps will move back toward an inbound or matching motion.

4.

Technical sales will become sales

What is currently called sales engineering or solutions architecture, and often viewed as a support role, will become the core GTM role. VPs of Sales Engineering will lead sales teams. This is a natural evolution tied back to the first point, which is building trust. The easiest way to build trust is to speak the same technical language as your buyer and understand their pain. These roles will carry a strong sales component, but also an engineering or, more likely, a technical solutions component.

5.

Sales teams will be paid 2-5X their current compensation

Because teams will be 2-10X smaller smaller on average and will operate with a more succinct inbound motion, reps will spend about 50% of their time building relationships and 50% managing their AI agents. Each rep may have 2-8 agents reporting to them, which will take up a significant portion of their time.

The Roles That Will Be Forever Changed

VP Sales

This role will transition to the VP sales engineering of VP solutions architecture. This role will focus on successfully transitioning POC’s to long term contracts by proving AI value in the organizations they are selling.

VP of Sales Engineering

Post-AI

Pre-AI

Post-AI

MM AE

As we know it will be gone - replaced by agent

AI Agent

SMB AE

As we know it will be gone - replaced by agent

SDR

As we know it will be gone - replaced by agent

Channel/Partner Sales

This role will exist but the people that are successful will transition into much more of a technical relationship builder then the average today and there will be far fewer, think 2X fewer positions.

Technical Channel Sales

Sales Ops

This role will transition to a GTM engineering role that is focused on maintaining and improving the efficacy of the AI agents involved in the sales motion.

GTM Engineer

Post-AI

ENT AE

This role will exist but the people that are successful will transition into much more of a technical seller then the average today and there will be far fewer, think 10X fewer positions.

Technical Enterprise AE

Post-AI

Pre AI

Post AI

VP Sales

VP of
Sales Engineering

This role will transition to the VP sales engineering of VP solutions architecture. This role will focus on successfully transitioning POC’s to long term contracts by proving AI value in the organizations they are selling.

Pre AI

Post AI

Channel/Partner
Sales

Technical
Channel Sales

This role will exist but the people that are successful will transition into much more of a technical relationship builder then the average today and there will be far fewer, think 2X fewer positions.

Pre AI

Post AI

Sales Ops

GTM Engineer

This role will transition to a GTM engineering role that is focused on maintaining and improving the efficacy of the AI agents involved in the sales motion

Pre AI

Post AI

ENT AI

Technical
Enterprise AE

This role will exist but the people that are successful will transition into much more of a technical seller then the average today and there will be far fewer, think 10X fewer positions.

Post-AI

Pre AI

MM AE

AI Agent

SMB AE

SDR

As we know roles MM AE, SMB AE, SDR will be gone - replaced by agent

Now where are these roles going to come from

Lets break down some of the different roles within tech and where they are going over the next 2-3 years.

The Future of Compensation

Alright, almost every traditional role is disappearing, well almost. But here is the exciting part. New roles are emerging and they are going to come with paychecks much higher than what we see today.

The Betts Prediction on Future Org Structures

Pre-AI

Post-AI

You’ll notice there are no entry level roles here, something we’ve been flagging for a long time. We expect to see a shift toward a Bain or McKinsey style model with associate roles built to support senior positions.

This would create far more opportunities for recent grads than they have today. Companies will need to treat this as a long term investment rather than a quick ROI. That can be a hard mindset shift for tech companies that move fast and expect immediate results.

Without it, the alternative is a world where Meta and OpenAI keep poaching top talent with $100M offers.

Kidding, that is not sustainable.

This would create far more opportunities for recent grads than they have today. Companies will need to treat this as a long term investment rather than a quick ROI. That can be a hard mindset shift for tech companies that move fast and expect immediate results.

We expect companies to create associate-level roles, similar to the Bain and McKinsey model we mentioned, to support senior positions like enterprise reps and sales engineers. To ensure long-term sustainability, companies will need to invest in early technical talent with SDR-level skills who can also manage AI agents for senior reps.

At Betts we have been working with top technology companies for the last 15 years and have seen go-to-market roles progress dramatically over that time. But there has never been a bigger shift then is happening right now. This shift in GTM is going to be the biggest in my lifetime and its going to be the swiftest.

"Every decade or so, sales transforms. But what we’re witnessing now isn’t just a shift, it’s a reinvention. The future of GTM is being written in real time."

This would create far more opportunities for recent grads than they have today. Companies will need to treat this as a long term investment rather than a quick ROI. That can be a hard mindset shift for tech companies that move fast and expect immediate results.

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