OpenAI expanded its enterprise sales team dramatically from 10 to 500 employees in under two years, with Anthropic rapidly following suit, targeting $20 billion to $26 billion in revenue by 2026. Both firms are aggressively hiring amid what might be the easiest enterprise sales environment in software history. However, this scenario poses challenges. Ben Horowitz highlighted in a recent Sequoia Capital discussion that buyers are already predisposed to purchase AI from OpenAI and Anthropic, producing a risky sales environment rather than an advantage. This phenomenon, termed the "Order-Taker Problem, " was acknowledged by Cloudflare CEO Matthew Prince in May 2023, who admitted many salespeople succeeded mainly by "taking orders" due to high demand for products solving widespread issues. When macroeconomic conditions shifted, Cloudflare cut around 100 sales staff who contributed only about 4% of new business, exposing a structural flaw in hot markets: with inbound demand so strong, true sales skill becomes unmeasurable, allowing mediocre reps to excel and ascend into leadership without genuine sales ability—until inbound demand declines. Sales commentator TechSalesGuy illustrated this with his brother’s experience at a high-demand company, where half the sales job involved simple order-taking. The recent surge of hires at OpenAI and Anthropic risks creating teams proficient at riding inbound momentum but lacking core sales competencies—skills that often lead to quick job changes rewarded by brand association rather than expertise. Horowitz contrasts this with the rigorous sales discipline developed at PTC in the 1990s, a company whose product was difficult to install, demo, and sell, compelling reps to master systematic account mapping, competitive displacement, and deal-by-deal technical justification. He references his benchmark hire at Databricks, Ron Gabrisko, who proved his skill by selling challenging products, applying the same principle when hiring for Okta—preferring candidates who interrogate and qualify the hiring company rather than simply showing enthusiasm. Such instincts and discipline forge real sales capabilities needed to close difficult deals. Historical market downturns exemplify this dynamic: Salesforce’s 2001 dot-com slowdown imposed qualification discipline on previously inbound-optimized reps; Facebook’s advertising growth slowed in 2012 as advertisers sought measurable ROI; and AWS faced real competition around 2015 as Azure and Google Cloud aggressively pursued enterprise customers. Companies that managed these transitions successfully had sales teams experienced in tough selling conditions beforehand, while those reliant on inbound talent struggled. The AI market shares this trajectory. A February 2026 a16z survey found 78% of enterprise CIOs using OpenAI and 44% using Anthropic, with consolidation underway.

As enterprise buyers start focusing on pricing, support, vendor risk, and integration depth, sales conversations will become more complex than today’s incoming-demand-driven approach. For investors, the stakes are significant. OpenAI plans to nearly double its 2026 workforce to 8, 000, heavily investing in sales and customer-facing roles. Anthropic targets $20–26 billion in revenue supported by partnerships with Deloitte, Cognizant, and Snowflake, outsourcing much implementation complexity. Both strategies embed costly organizational factors difficult to reverse. Additionally, Reuters reported in March 2026 that OpenAI and Anthropic compete for private equity joint ventures, with OpenAI offering 17. 5% guaranteed minimum returns to attract partners. These strategies depend heavily on ongoing inbound sales momentum; should this falter, the fixed cost structure poses serious risks. Compounding this issue, sales leaders cultivated in all-inbound environments tend to replicate hiring and management patterns suited only to easy markets, perpetuating a talent selection flaw that escalates through organizational layers. Horowitz suggests a value-investor approach to hiring the right sales talent: ignore prestigious logos, as they don’t guarantee exceptional sales ability. Instead, seek individuals undervalued by the market—those with careers at lesser-known companies where they had to fight for every deal against entrenched competitors, build pipelines without organic inbound, and systematically displace incumbents instead of merely responding to favorable RFPs. Such reps typically don’t come from OpenAI or Anthropic but from companies that demanded real sales craft. Their availability and experience make them valuable hires. Ultimately, the true test for these AI giants isn’t scaling teams during a boom but whether the newly hired salesforce can retain and grow enterprise accounts when the market no longer drives sales automatically.