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AI Readiness Survey

Department
Information Technology
Company
Knowledge Fortune
Respondent
Miss. Neha
Department Score
63.4 / 100
AI Strategy & Resources
Category Score : 68.68
Q Question Answer
Q1 How does IT support departments in adopting AI tools or automation? IT supports limited AI tool adoption with approvals
Q2 How prepared is IT for AI-related cybersecurity risks? Some controls exist (access, monitoring, policy)
Q3 What is the biggest challenge preventing IT from adopting AI or automation? Skill gap in AI and modern tools
Q4 How does IT handle employee usage of external AI tools (ChatGPT, Gemini, Copilot, etc.)? AI tools are blocked completely
Q5 How prepared is IT to manage AI-generated content risks (fake emails, deepfake voice, fraud)? Some awareness training + controls
Q6 How prepared is IT to prevent prompt injection/data leakage in AI tools? Some controls (policy + awareness)
Q7 Does IT have controls to restrict AI tools from using company data for training? Not sure
Q8 How mature is IT’s incident response plan for AI-related issues? AI-related scenarios included partially
Q9 Does IT have a defined AI roadmap for the next 12–24 months? Formal AI roadmap aligned with business goals
Q10 How does IT evaluate new AI tools/vendors before adoption? Structured evaluation with security review
Q11 Does IT have an approved list of AI tools for employees? Limited approved tools
Q12 How does IT evaluate AI tools for data privacy risks? No evaluation
Q13 Does IT have policies for using company data in AI tools? No policy
Q14 How prepared is IT to support AI model deployment (MLOps) if needed? No capability
Q15 Does IT have an AI governance committee or defined ownership? No ownership
Q16 How does IT handle vendor lock-in risk for AI tools? Evaluated during selection
Q17 How ready is IT to support AI copilots across the organization (coding, HR, finance, support)? Not ready
Q18 What is IT’s long-term ambition for AI usage in the organization? Use AI only for IT monitoring
Performance and Application
Category Score : 66.89
Q Question Answer
Q19 What is the current level of IT automation in daily operations? Almost none (manual work dominates)
Q20 How does IT currently handle repetitive operational tasks (account creation, approvals, reports)? Manual with some templates
Q21 How mature is IT’s incident management process? Defined process + automation + predictive alerts
Q22 How does IT support business teams in identifying automation opportunities? Only when business requests
Q23 How prepared is IT to implement AI-powered IT operations (AIOps)? Tools + pilot readiness exists
Q24 How mature is your DevOps / CI-CD process (if software is developed in-house)? Basic deployment process
Q25 How ready is IT to support AI-based automation in internal workflows (ticketing, approvals, HR, finance)? Limited readiness
Q26 How does IT manage patching and updates? Regular patch schedule
Data Infrastructure
Category Score : 53.35
Q Question Answer
Q27 How organized and accessible is your organization’s data across systems? Data is scattered, mostly in Excel/manual files
Q28 What is the maturity level of your data governance practices? Basic rules exist but not enforced
Q29 How well is data quality ensured in business-critical systems (ERP, CRM, HRMS)? IT supports periodic audits and cleanup
Q30 What is the current status of API availability across key systems (HRMS, ERP, CRM, etc.)? APIs exist but limited or unstable
Q31 How is unstructured data handled (emails, PDFs, scanned documents, chats)? Stored but hard to search
Q32 How consistent are data definitions across departments? Some common terms exist
Q33 How is data lineage handled (tracking where data comes from and how it changes)? Tracked informally
Q34 How mature is the organization’s master data management (customers, vendors, employees)? Partial standardization
Q35 How often are data access permissions reviewed and cleaned up? Only when someone leaves
Q36 Does the organization have a centralized data warehouse or lake? Planning stage
Q37 How does IT manage data loss prevention (DLP)? Basic restrictions only
Q38 How mature is metadata management (tags, data labels, ownership)? Basic tags
Q39 What is the current approach to controlling access to sensitive data? Basic access controls exist but not reviewed
Q40 How strong is your organization’s backup and disaster recovery readiness? Backup exists but recovery not tested
Q41 How mature is your organization’s cybersecurity monitoring? Basic antivirus and firewall only
Q42 How secure is your organization’s endpoint environment (laptops/desktops)? Basic antivirus only
Q43 How does IT manage cloud security (if cloud is used)? Basic security settings only
Q44 How mature is IT’s identity and access management (IAM)? Basic login control
Q45 How does IT ensure compliance with privacy laws and regulations (GDPR, DPDP, ISO)? Some policies but weak enforcement
Q46 How open is the organization’s IT architecture to AI integration? Mixed systems, limited integration capability
Q47 How mature is your organization’s cloud adoption? Partial cloud usage
Q48 How does IT manage data integration between systems? Some integrations exist but fragile
Q49 How mature is the organization’s data classification (public, internal, confidential)? Defined classification
Organization
Category Score : 64.13
Q Question Answer
Q50 How is IT currently contributing to business growth and efficiency? Mostly reactive support (ticket fixing, device issues)
Q51 How mature is your IT documentation and knowledge base? Very poor / no documentation
Q52 How does IT handle shadow IT (employees using unapproved apps/tools)? Track and restrict some apps
Q53 How skilled is the IT team in AI and automation technologies? Some trained members exist
Q54 How does IT manage change management when new AI tools are introduced? Training + documentation
Q55 Select the Roles and Responsibilities that are performed by IT department in your organization.
Technology Enablers
Category Score : 64.00
Q Question Answer
Q56 How often does IT evaluate whether current tools/software are still meeting business needs? Annually
Q57 How does IT measure performance and service quality? Only ticket count and response time
Q58 How does IT handle capacity planning (storage, bandwidth, compute)? Basic estimates based on past usage
Q59 How often does IT review the ROI/value of major IT systems? Rarely
Q60 How are system logs and monitoring data currently used? Used for troubleshooting
Q61 How well are business-critical systems integrated with reporting dashboards? Some dashboards exist