AI startups are in a unique place, seeing major opportunities for growth while facing constraining bottlenecks in sourcing go-to-market (GTM) talent needed to scale revenue. While similar to trends seen in the rest of the tech sector, the artificial intelligence industry is experiencing a particularly challenging paradox when it comes to sales recruitment.
Building upon our own experience working with different AI companies, Betts Recruiting has put together this blog to dive into the hiring dilemma artificial intelligence startups face and introduce a proven approach to help resolve it:
Current Sales Recruitment Trends in AI
The Generative AI sector has grown exponentially since ChatGPT was introduced to the public, ushering in a new wave of automation solutions for every industry. As the space continues to evolve and mature, it introduces more innovation that scales both the value and complexity of new tools. Competition also continues to increase within this industry as more and more players enter, making it harder to stand out and creating a greater need among startups to lock down their unicorn seller.
Looking at our data from working with AI companies over the past year, several critical trends have emerged:
- Technical selling is required – Different degrees of technical knowledge are a “must-have” requirement for technology sales to close successfully
- Talent pool is limited – Despite growing interest in the industry, the number of candidates with both technical and sales experience in Gen AI remains limited
- Enterprise market dominates – More artificial intelligence companies are targeting enterprise clients, creating a demand for candidates experienced in enterprise-level selling
- Startups face stiff competition – Many of the biggest brands in tech have rolled out their own AI solutions, increasing competition for both customers and for the limited talent pool with the most sought-after experience
What is the AI Sales Recruitment Paradox?
The recruitment paradox in the artificial intelligence industry can be boiled down to a scalability challenge that rises from a contradiction. The more you grow, the more specialized your solution(s) must become – but the more you rely on technical specialization, the more you need to rely on sales specialists to successfully close deals. The more specialization you need from sales talent, the more expensive it becomes to recruit – starting the cycle all over again as you increase revenue targets to justify hiring the workforce you need to meet them.
AI companies have historically been selective about GTM recruitment, with an average interview-to-placement rate that falls below that seen in the rest of tech. This lower conversion rate translates directly to longer time-to-hire, which inevitably increases your Cost-per-Hire (CPH) for every senior-level sales job you try to fill. For early-stage startups operating with limited runway, these increased costs and delays can significantly impact growth and even threaten your sustainability.
Why Traditional Recruitment Approaches Fall Short
The traditional approach to sales recruitment – working with multiple outsourced contingency recruiters while leveraging internal resources, job boards and network referrals – becomes increasingly unsustainable as your startup seeks to scale upwards. Here are the top reasons why:
1. The Unicorn Seller Hunt is Expensive
Nearly every part of tech is seeking a unicorn seller, including the AI startup space. While this approach makes sense, if you are not careful about how you handle sourcing, it can result in:
- Extended vacancy periods as you search for a perfect match
- Higher recruiter fees due to the specialized nature of the search
- Increased total Cost-per-Hire that can quickly drain your hiring budget
2. Technical Requirements Create a Qualification Bottleneck
The technical knowledge requirements for AI sales roles have created a qualification bottleneck. Many companies require candidates to demonstrate proficiency in areas like:
- Basic understanding of machine learning concepts
- Experience with data platforms and analytics tools
- Ability to explain complex technical concepts to business audiences
These requirements significantly shrink the available talent pool, screening out candidates who meet other critical qualifications early in your search.
3. Competition with Tech Giants in AI
AI startups must compete for talent with established technology giants who often offer better compensation packages in addition to the perception of greater job stability. This puts increased pressure on startups to try to match these offers as best they can or lose out on top performing candidates. However, this type of “arms race” over talent acquisition and current comp rates can quickly expend your hiring budget.
True Costs for Hiring Technical Sales Talent
Many of the top—and most sought-after—GTM jobs in AI are hybrid technical sales positions that allow startups to bridge the gap between business and functionality messaging. However, this also means that in addition to the smaller talent pool and higher competition over viable candidates for these roles, average compensation rates will trend higher than for titles that require less specialization.
Top Tech Sales Roles for AI
Some of the top specialist or technical sales positions in the artificial intelligence industry include Sales Engineers (SEs), Enterprise Account Executives (EAEs) and Solution Architects (SAs). These titles are typically filled with professionals who understand how to navigate both business and feature-driven conversations from pre-sales to post-sales to ensure success for customers.
As can be seen in our Enterprise Compensation Guide, these roles also usually command significant salaries and OTE (on-target earnings):
- Sales Engineers: $120K-$170K salary + $30K-$60K OTE
- Enterprise AEs: $150K-$175K salary + $150K-$175K OTE
- Solutions Architects: $120K-$180K salary + $10K-$35K OTE
Hidden Cost-per-Hire
While base compensation represents the most visible expense, the true cost of acquiring technical sales talent extends far beyond salary and commission. When utilizing traditional agency recruitment, companies typically pay fees ranging from 15-30% of a candidate’s first-year salary. For an Enterprise Account Executive with a $150,000 starting comp package, this translates to additional agency fees of $45,000 or more per placement.
Adding to these recruitment costs is the revenue impact of position vacancies as time drags on: as can be seen in our Scale Guide series, startups at Series B for example will see potential revenue losses in the tens of thousands of dollars the longer it takes to source and hire a qualified EAE. This means that between OTE, time-to-hire and interview-to-placement attrition, your CPH can rise to 25% or more of your total recruitment costs.
Breaking the Paradox: A New Approach to AI Sales Recruitment
To overcome the AI startup sales recruitment paradox, you need a more flexible, efficient and cost-effective approach to talent acquisition. Our Recruitment as a Service (RaaS) model offers you a more refined and strategic way to source your unicorn sellers at scale. Unlike the traditional agency or RPO (recruitment process outsourcing) approach with per-placement fees, RaaS provides unlimited hiring potential for a fixed annual cost, along with additional benefits:
- Powered by Betts Connect: Leverage our Betts Connect platform to source candidates when you need to, as you need to, and for how many you need
- Cost predictability: Fixed subscription pricing makes budgeting more predictable
- Scalability: Ability to make multiple hires without incremental placement fees
- Expert support: Access to Betts recruiters and a Connect CSM combines talent acquisition and technical support to streamline the process
- Data-driven matching: AI-powered candidate matching based on specific requirements
- Faster time-to-hire: Streamlined processes that reduce time-to-fill metrics
RaaS Case Study: Harvey AI
Harvey AI, a LegalTech solution provider backed by Sequoia and OpenAI, faced a critical challenge in scaling their sales team. They needed to hire Enterprise Sales Managers urgently to support their expansion, but lacked a dedicated recruiter team and the bandwidth to manage the hiring process.
Harvey partnered with Betts Recruiting using our RaaS model, which provided:
- Access to Betts’ specialized AI talent network in the NYC region
- Advanced filtering capabilities through Betts Connect to identify candidates with the precise skill combinations needed
- A cost-effective subscription approach that eliminated per-hire fees
The results transformed Harvey’s talent acquisition approach, achieving:
- Over 150 qualified candidates were evaluated by Betts
- 45 candidates meeting Harvey’s specific requirements were presented within the engagement period
- Time-to-hire for Enterprise Sales Manager positions decreased to approximately one month
- The improved hiring velocity enabled Harvey to accelerate their sales organization buildout and maintain momentum toward their Series C funding targets
A Strategic Choice for AI Sales Recruiting
The old school way of recruiting was not designed for the highly competitive landscape AI startups face today. RaaS by Betts offers a more streamlined approach to building your go-to-market teams at scale, without sacrificing finding qualified candidates for speed or affordability.
Contact Betts here to discover how our Recruitment as a Service model can transform your talent acquisition strategy and help you build the sales team you need to scale successfully.