As OpenAI races towards an ambitious revenue goal of US$100 billion by 2027, the ChatGPT maker is reportedly building an army of AI consultants to bridge the gap between cutting-edge technology and corporate boardrooms. The move signals a fundamental shift in how AI companies approach the notoriously difficult challenge of enterprise adoption.
Based on industry data and recent hiring patterns, OpenAI is significantly expanding its go-to-market team as its enterprise business continues to grow explosively. The startup’s annual revenue will reach $20 billion in 2025, up from $6 billion in 2024, and more than 1 million organizations are currently using its technology.
Enterprise implementation challenges
An aggressive hiring strategy reflects a broader truth about enterprise AI. So while the technology sells on demo, it requires a completely different skill set to implement at scale. Recent research found on Second Talent shows that while 87% of large enterprises have implemented AI solutions, only 31% of AI use cases reach full production, and the gap between pilot projects and enterprise-wide adoption remains large.
“The real story isn’t just hiring consultants, it’s what this reveals about the maturity of enterprise AI,” said one industry analyst, who requested anonymity. “We are moving from a world where companies bought AI out of FOMO to a world where serious implementation expertise is required to really capture value.”
The challenge is multifaceted. According to multiple industry studies, the top challenges for enterprise AI adoption in 2025 include integration complexity at 64%, data privacy risks at 67%, and reliability concerns at 60%. These are not problems that can be solved with better models alone. It requires human expertise in change management, workflow redesign, and organizational transformation.
competitive environment
OpenAI is not alone in recognizing the gap in enterprise implementations. Anthropic is taking a different approach by focusing on large-scale partnerships, with plans to achieve annual sales of US$9 billion by the end of 2025 and US$20 billion to US$26 billion by 2026.
The company recently announced partnerships with Deloitte, Cognizant, and Snowflake, essentially outsourcing the consulting layer to existing professional services firms.
According to industry research firm Sakura, “Anthropic is positioning Claude as an alternative for enterprises, “OpenAI for enterprises that don’t want to rely on OpenAI.”
Meanwhile, Microsoft is leveraging existing corporate relationships and consulting partnerships, and Google is bundling AI capabilities into its Workspace and Cloud ecosystems. Amazon’s strategy is focused on making AWS the go-to infrastructure for enterprise AI deployments.
What became clear with the adoption of OpenAI
The reported wave of consultant hires suggests that OpenAI believes direct engagement with customers is more effective than a pure partnership model. This is consistent with a broader trend in enterprise software where vendors increasingly require domain expertise to help customers realize value.
Job postings analyzed across multiple platforms show that OpenAI is hiring for roles across enterprise account director, AI implementation manager, and solution architect. All of these are focused on helping organizations move from proof of concept to production deployment.
Timing is important. As OpenAI’s enterprise market share declines from 50% to 34% while Anthropic doubles its presence in the underlying model from 12% to 24%, the company must prove that it can not only build the best technology, but also help enterprises successfully adopt it.
Reality of implementation
For enterprise IT leaders, hiring large numbers of AI consultants from vendors is both an opportunity and a warning. Opportunity: Access to deep technical expertise to navigate complex implementations.
Caveat: If the vendors themselves require hundreds of consultants to make their technology work, what does that say about the maturity of these solutions?
According to a recent industry report, “Most organizations treat AI as a tactical enhancement rather than a strategic enabler, resulting in fragmented execution.” Success requires more than just technology: organizational readiness, workflow redesign, and a fundamental rethink of how knowledge work is done.
The real question isn’t whether OpenAI or its competitors can hire enough consultants. What matters is whether companies are able to successfully absorb these technologies at the pace their industry demands.
Human challenges may prove more difficult to solve than technical challenges, as 42% of executives report that AI adoption is “driving their companies apart” due to power struggles, conflict, and organizational silos.
As the competition to sell AI intensifies, one thing is clear. That means the winners will not just be those with the best models, but those that can successfully navigate the messy and difficult task of organizational change.
OpenAI’s mass hiring of consultants suggests the company is learning this difficult lesson.
(Photo courtesy of Andrew Neil)
See also: AI Expo 2026 Day 1: Governance and data readiness enable the agent-based enterprise
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