How to sell to Heads of Operations at AI & machine learning companies
Heads of Operations in AI & machine learning companies are primarily measured on operational efficiency. They respond to outreach that demonstrates an understanding of their unique challenges, such as optimizing AI model deployment processes and managing cross-functional teams. Highlighting specific pain points and providing actionable solutions will capture their attention and prompt a response.
Written and maintained by the SoloRiff team, who build outbound software and run outbound with it. The figures below are our own: we measured 561 ai & machine learning company domains over public DNS on 2026-09-03. Last updated 2026-09-03.
What actually hurts
- slow model deployment
- cross-team miscommunication
- resource allocation issues
- integration delays
The playbook
- 01
Identify recent AI project launches
Use platforms like LinkedIn to filter for companies that have recently launched AI projects or released new machine learning models. These events often indicate a need for improved operational processes, making them ripe for outreach.
- 02
Research operational bottlenecks
Dive into industry forums or case studies to identify common operational challenges faced by AI companies, such as slow model iteration or integration issues. Tailor your message to address these specific pain points directly.
- 03
Connect through industry events
Look for upcoming AI and machine learning conferences or webinars where these leaders are speaking. Mention their participation in your outreach to establish relevance and demonstrate your engagement with their work.
- 04
Acknowledge resource constraints
In your messaging, recognize that Heads of Operations often deal with limited resources and high expectations. Address how your solution can alleviate specific resource-related stressors, such as team overload during product launches.
- 05
Propose a strategic collaboration
Suggest a brief call to discuss potential collaboration on improving operational workflows. Make it clear how this conversation could lead to actionable insights that align with their current initiatives.
Can ai & machine learning companies even receive your mail?
We measured the DNS of 561 ai & machine learning companies, sampled evenly across company sizes, to see how many authenticate their own email. It matters in both directions: a domain that does not authenticate is a domain whose team is used to mail going missing — and if your own domain is in the gap, yours is the mail going missing.
Publishes a DMARC policy of quarantine or reject — the domain actually asks receivers to act on failures.
The gap is the finding: 26.3% of 1–10-person companies against 86.2% of the largest — 60 points apart. Small companies are where the unauthenticated domains are, and small companies are who most cold outreach is aimed at.
Where does your domain sit?
Same three lookups, run live against your domain. Nothing is stored and nothing is emailed to you.
How this was measured
Company domains were sampled within employee-count bands, then queried over public DNS for SPF (TXT at the apex), DMARC (TXT at _dmarc.) and MX. One domain per company, deduplicated. Anyone can reproduce any single row of this with dig.
DKIM is deliberately absent. A DKIM key lives under a selector that cannot be enumerated from outside the domain, so a company with flawless DKIM under a name we did not guess would be counted as having none. That would measure our guess list, not the industry.
Domains with no MX record are excluded rather than counted as failures — parked and redirect-only domains would otherwise drag every figure down and make the result an artefact of the sample.
Sampled within bands, so this describes the population of companies, not of employees: a 10-person company counts once, as does a 10,000-person one. Each band is at least 60 domains; bands below that are not published. Figures are percentages of the sample, not of the whole industry, and we publish no company names — only counts.
Measured 2026-09-03. Re-measured monthly.
The full census across every industry — sortable, with sample sizes, free to reuse under CC BY 4.0.
Subject lines that fit
- Streamlining your AI operations
- Optimizing machine learning workflows
- Improving deployment efficiency
Questions
- Why do Heads of Operations in AI ignore cold outreach?
- Heads of Operations often receive numerous cold outreach attempts that fail to address their specific operational challenges. If the outreach does not demonstrate a clear understanding of their unique pain points or provide actionable insights, it is likely to be overlooked.
- What operational challenges do AI companies face?
- AI companies frequently struggle with issues like slow model deployment, inefficient cross-team collaboration, and managing resource constraints. These challenges can lead to delayed project timelines and increased costs, making operational efficiency a top priority.
- How can I make my outreach relevant to Heads of Operations?
- To make your outreach relevant, focus on specific operational bottlenecks that AI companies face. Highlight any recent industry developments or challenges that resonate with their current projects, showcasing your understanding of their environment.
- What type of solutions do Heads of Operations look for?
- Heads of Operations in AI seek solutions that enhance efficiency, streamline processes, and improve collaboration among teams. They are particularly interested in tools that can help them manage resources better and reduce the time required for model deployment.
Or have it run itself
SoloRiff does every step above on its own — finds the companies, finds the people, writes each of them individually, and handles the replies. Drop your URL and watch it work before you sign up for anything.
Try it on your site