New Research Report on Enterprise Generative AI Adoption

Key considerations, challenges, and strategies for unleashing AI at scale
With the accelerating adoption of Generative AI and ML within the enterprise, organizations are hard-pressed to balance investments with expectations and outcomes. In light of this, ClearML and the AI Infrastructure Alliance (AIIA) have commissioned a research report on Generative AI in Fortune 1000 companies.
The survey report, “Enterprise Generative AI Adoption: C-Level Key Considerations, Challenges, and Strategies for Unleashing AI at Scale,” reveals the economic impact and significant challenges top C-level executives face in harnessing AI’s potential within their organizations.
While the majority of respondents said they need to scale AI, they also said they lack the budget, resources, talent, time, and technology to do so. Download a copy of this research report to get a full picture of the tremendous economic impact and key challenges that top C-level executives face as they work to unleash the power of AI in their enterprises.



After reading this report, you’ll understand:

  • The mounting revenue expectations put on AI transformation leaders and their teams.
  • Where AI fits into the top priorities of the C-suite and their plans to adopt the technology.
  • Key challenges such as budget and resource constraints as well as lack of talent, technology, and time.
  • The profound inability of underfunded, understaffed, and under-governed AI, ML, and engineering teams in large enterprise organizations to quantify results.
  • The driving need behind standardizing on a single AI/ML platform across departments instead of using different tools in different teams.
  • The top-5 key challenges and blockers in adopting generative AI / LLMs / xGPT solutions across organizations and business units.

The extensive global survey includes responses from 1,000 CDOs, CIOs, CDAOs, CTOs, and VPs of AI and Digital Transformation in charge of adopting and spearheading Generative AI transformation in Fortune 1000 and large enterprises.