AI Readiness Survey

Department: Information Technology | Company: ZEEX
Step 1 of 1
0%
AI Strategy & Resources
How does IT support departments in adopting AI tools or automation? *
How prepared is IT for AI-related cybersecurity risks? *
What is the biggest challenge preventing IT from adopting AI or automation? *
How does IT handle employee usage of external AI tools (ChatGPT, Gemini, Copilot, etc.)? *
How prepared is IT to manage AI-generated content risks (fake emails, deepfake voice, fraud)? *
How prepared is IT to prevent prompt injection/data leakage in AI tools? *
Does IT have controls to restrict AI tools from using company data for training? *
How mature is IT’s incident response plan for AI-related issues? *
Does IT have a defined AI roadmap for the next 12–24 months? *
How does IT evaluate new AI tools/vendors before adoption? *
What is IT’s long-term ambition for AI usage in the organization? *
Does IT have an approved list of AI tools for employees? *
How does IT evaluate AI tools for data privacy risks? *
Does IT have policies for using company data in AI tools? *
How prepared is IT to support AI model deployment (MLOps) if needed? *
How does IT handle vendor lock-in risk for AI tools? *
Does IT have an AI governance committee or defined ownership? *
How ready is IT to support AI copilots across the organization (coding, HR, finance, support)? *
Performance and Application
What is the current level of IT automation in daily operations? *
How does IT currently handle repetitive operational tasks (account creation, approvals, reports)? *
How mature is IT’s incident management process? *
How does IT support business teams in identifying automation opportunities? *
How does IT manage patching and updates? *
How prepared is IT to implement AI-powered IT operations (AIOps)? *
How mature is your DevOps / CI-CD process (if software is developed in-house)? *
How ready is IT to support AI-based automation in internal workflows (ticketing, approvals, HR, finance)? *
Data Infrastructure
How organized and accessible is your organization’s data across systems? *
What is the maturity level of your data governance practices? *
How well is data quality ensured in business-critical systems (ERP, CRM, HRMS)? *
What is the current status of API availability across key systems (HRMS, ERP, CRM, etc.)? *
How does IT manage data integration between systems? *
How is unstructured data handled (emails, PDFs, scanned documents, chats)? *
How consistent are data definitions across departments? *
How mature is the organization’s master data management (customers, vendors, employees)? *
How is data lineage handled (tracking where data comes from and how it changes)? *
How often are data access permissions reviewed and cleaned up? *
Does the organization have a centralized data warehouse or lake? *
How mature is the organization’s data classification (public, internal, confidential)? *
How does IT manage data loss prevention (DLP)? *
How mature is metadata management (tags, data labels, ownership)? *
What is the current approach to controlling access to sensitive data? *
How strong is your organization’s backup and disaster recovery readiness? *
How mature is your organization’s cybersecurity monitoring? *
How secure is your organization’s endpoint environment (laptops/desktops)? *
How mature is IT’s identity and access management (IAM)? *
How does IT manage cloud security (if cloud is used)? *
How does IT ensure compliance with privacy laws and regulations (GDPR, DPDP, ISO)? *
How open is the organization’s IT architecture to AI integration? *
How mature is your organization’s cloud adoption? *
Organization
How is IT currently contributing to business growth and efficiency? *
How mature is your IT documentation and knowledge base? *
How does IT handle shadow IT (employees using unapproved apps/tools)? *
How skilled is the IT team in AI and automation technologies? *
How does IT manage change management when new AI tools are introduced? *
Select the Roles and Responsibilities that are performed by IT department in your organization. *
Technology Enablers
How often does IT evaluate whether current tools/software are still meeting business needs? *
How does IT measure performance and service quality? *
How does IT handle capacity planning (storage, bandwidth, compute)? *
How often does IT review the ROI/value of major IT systems? *
How are system logs and monitoring data currently used? *
How well are business-critical systems integrated with reporting dashboards? *