The current state of AI adoption: A new survey of 424 IT stakeholders reveals widespread interest in generative AI, with 94% incorporating it into their operations and management strategy, though only 17% have progressed beyond experimentation.
- Most organizations remain in early stages, with 41% testing simple use cases and 42% conducting initial pilots
- Only 5% of organizations report having mature generative AI implementations
- Multiple AI platforms are being deployed simultaneously, with 44% of organizations using two different solutions and 22% using three
Platform preferences and adoption trends: Microsoft Copilot leads the pack among generative AI solutions, while a significant portion of organizations are pursuing custom development.
- Microsoft Copilot is the most widely adopted platform at 71% usage
- OpenAI’s ChatGPT follows at 62%, with Google Gemini at 32%
- 24% of organizations are developing homegrown solutions using open source Large Language Models (LLMs)
Implementation challenges: Organizations face several significant hurdles in their AI adoption journey, with data management emerging as the primary concern.
- 49% struggle with data scattered across multiple repositories
- 45% report existing solutions are limited to simple reactive use cases
- 43% cite stakeholder confusion between generic GPT models and specialized generative AI solutions
Emerging technologies and awareness: While interest in agentic AI (AI systems that can act autonomously) is growing, understanding remains limited among IT leaders.
- 60% recognize the value of natural-language interfaces for reporting
- 58% see potential in autonomous agents
- Only 8% consider themselves very knowledgeable about agentic AI technology
Workforce impact perspectives: The survey reveals overwhelmingly positive sentiment regarding AI’s impact on employment.
- 63% believe generative AI will enhance existing jobs
- Only 1% express concerns about job displacement
- 98% anticipate future benefits including increased productivity and cost reduction
Future implications: While enthusiasm for AI technologies runs high among IT leaders, the gap between interest and mature implementation suggests a long road ahead for widespread enterprise AI adoption, with success likely depending on organizations’ ability to overcome data management challenges and build internal expertise.
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