96% of IT pros use AI now: Their top 7 agentic applications and biggest implementation roadblocks

2026-05-21 · Source: News and Advice on the World's Latest Innovations | ZDNET · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Intermediate, short

Summary

A global survey by Alteryx involving 700 data analysts and 700 IT leaders reveals that 96% of IT professionals currently use AI, though only 49% are frequent users. A significant 59% anticipate employing AI agents within the next 12 months, with half expressing willingness to grant these agents "unrestricted access" to data, despite 44% emphasizing the need for human oversight. Common agentic AI applications include drafting communications (59%), scheduling workflows (54%), and generating reports (48%). Data preparation for AI models consumes approximately six hours weekly for respondents, with 48% spending 6-10 hours, primarily using spreadsheets (61%). Furthermore, validating AI-generated outputs adds nearly four hours weekly, highlighting an "AI tax" of almost two days per week. Key barriers to AI adoption are difficulty explaining AI outputs (55%) and limited analytical skills (54%).

Key takeaway

For IT leaders and data scientists implementing agentic AI solutions, recognize that while adoption is high, significant time is spent on data preparation and validating AI outputs. You should prioritize robust data governance strategies and invest in tools and training that enhance AI explainability and analytical skills within your teams. This approach will mitigate the "AI tax" on productivity and ensure trusted, actionable insights from your AI deployments.

Key insights

IT professionals widely adopt AI, especially agentic applications, but face significant data quality and explainability challenges.

Principles

• AI adoption often layers on existing workflows.
• Human oversight is critical for AI output validation.
• Data governance is key for AI agent access.

In practice

• Agentic AI automates communications and workflow scheduling.
• Data preparation and AI output validation are time-intensive tasks.
• Spreadsheets remain dominant for foundational data work.

Topics

• AI Adoption
• Agentic AI
• Data Preparation
• AI Explainability
• IT Professionals
• Workflow Automation

Best for: CTO, VP of Engineering/Data, Executive, Data Scientist, IT Professional, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by News and Advice on the World's Latest Innovations | ZDNET.