IT leaders are bullish on AI agents, BMC survey finds

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.