Checklist
AI Automation Readiness Checklist
A practical nine-part assessment and 0-27 scoring framework for deciding whether a business process is ready for automation.
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Explore research-backed guidance, frameworks, practical explainers, and operational resources for AI automation, cybersecurity, and technology transformation.
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Implementation Framework
From AI Pilot to Production: A Practical Implementation Framework
Moving an AI workflow into normal operations requires ownership, testing, controls, support, measurement, and a plan for change after launch.
Practical Guide
AI Automation Readiness: What to Assess Before Automating a Business Process
A practical way to decide whether a business process is ready for automation before software, vendors, or AI models enter the conversation.
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Resource library
155 resources
Practical Guide
AI Automation
Evaluating AI Automation Vendors: What Businesses Should Examine Before Buying
A practical vendor-evaluation guide covering business fit, integration, security, governance, operating cost, support, and the evidence behind product claims.
Governance Guide
AI Automation
Writing an Internal AI Use Policy That Employees Can Follow
A practical framework for setting understandable boundaries around approved AI tools, sensitive information, human accountability, prohibited uses, and escalation.
Security Guide
AI Automation
Third-Party Risk in AI Integrations: Questions to Ask Before You Connect a Vendor
A security-focused guide to understanding vendor access, data handling, dependencies, contractual responsibilities, monitoring, and exit planning before connecting AI services.
Practical Guide
AI Automation
Common Automation Project Failure Points and How to Catch Them Early
A practical look at the warning signs that automation projects are drifting toward fragile design, poor adoption, weak controls, or unclear business value.
Governance Guide
AI Automation
Human Review Models for Automated Decisions
A practical comparison of approval, exception, sampling, escalation, and post-action review models for automated and AI-assisted workflows.
Security Guide
AI Automation
Logging and Monitoring Automated Workflows
What to record, what to alert on, and how to build useful operational visibility without turning logs into another source of sensitive-data risk.
Practical Guide
AI Automation
Choosing Between Rules-Based Automation and AI
A practical way to decide whether a workflow needs deterministic rules, AI-assisted interpretation, or a combination of both.
Governance Guide
AI Automation
AI Risk Classification for Businesses: A Practical Tiering Approach
A practical way to classify AI uses by consequence, autonomy, data sensitivity, uncertainty, and reversibility so governance effort matches risk.
Security Guide
AI Automation
Secrets and Credential Management for AI Automation
How to manage API keys, tokens, service identities, and other credentials without turning automation into a long-lived security liability.
Practical Guide
AI Automation
Measuring ROI From Business Automation: What to Count and What to Question
A practical framework for measuring automation value without reducing every outcome to headcount or optimistic time-savings estimates.
Governance Guide
Responsible AI & Governance
AI Incident Escalation: What to Record, Who to Involve, and When to Pause
A governance guide for responding when an AI-enabled process behaves unexpectedly, creates risk, or produces a potentially harmful outcome.
Security Guide
Cybersecurity
Service Account Security: A Practical Baseline for Automated Workflows
How to reduce credential and privilege risk when integrations, scheduled jobs, and automated workflows use non-human identities.