Frequently Asked Questions

How do I get started with AI if I have no AI capabilities?

Start with three steps: (1) Document your top 3 most time-consuming manual processes, (2) Create a basic AI policy defining what tools employees can use and what data they can share, (3) Identify one person accountable for AI initiatives. These foundations enable successful AI implementation without wasting money on tools you are not ready to use.

Read the full beginner's guide

Do I need to document processes before implementing AI?

Yes. Process documentation is the foundation for successful AI implementation. You cannot automate what is not written down. Attempting to automate undocumented processes leads to automating chaos at computer speed. Start with your top 3 most time-consuming manual processes.

Should I buy AI tools before documenting processes?

No. Companies that buy AI tools before documenting processes often find those tools unused six months later. Document your processes first, train your team to understand AI capabilities, then select and implement tools that fit your documented workflows. This approach leads to faster adoption and better ROI.

What size company is AI implementation right for?

AutomationTactics works with mid-market companies with $20M-$200M annual revenue. These companies typically have critical processes that are manual, time-consuming, or error-prone, and have the budget and organizational capacity to implement AI properly.

What is the Document-Train-Automate methodology?

Document-Train-Automate is a three-step AI implementation approach:

• Step 1 - Document: Write down how your processes actually work before attempting automation
• Step 2 - Train: Build AI literacy so your team understands what AI can and cannot do
• Step 3 - Automate: Build targeted automations for documented workflows with trained teams

The core principle is that you cannot automate what you have not documented.

See full definition in glossary

How long does AI implementation take?

A typical AI implementation with AutomationTactics takes 90 days, broken into three phases:

• Process documentation: 2-3 weeks
• Team training: 3-4 weeks
• Building automations: 6-8 weeks

This timeline assumes active participation from your team and readiness to make decisions.

What industries does AutomationTactics work with?

AutomationTactics has deep experience in construction, utilities, and energy industries, but now works across industries with mid-market companies ready for AI implementation. Current case studies include design-build construction (Primus Builders) and behavioral health services (First Children Services).

View case studies

How much does enterprise AI implementation cost?

AutomationTactics offers a 90-day implementation engagement for $50,000. This includes process documentation, team training, and deployed automations. The investment is appropriate for mid-market companies ($20M-$200M revenue) with manual processes ready for automation.

What results can I expect from AI implementation?

AutomationTactics clients typically see 10 hours per week saved per employee using AI-automated workflows. Specific results depend on your processes and implementation scope.

Read detailed case studies

What is Shadow AI and why is it a risk?

Shadow AI is unauthorized use of AI tools by employees without company oversight. It creates risks when employees paste sensitive company or customer data into public AI platforms like ChatGPT. This leads to potential data breaches, compliance violations, and liability issues. A formal AI policy and approved tool access mitigate this risk.

See full definition

How do I create an AI policy for my company?

An AI policy should cover:

• Acceptable use guidelines
• Approved AI tools
• Data privacy rules (what can and cannot be shared with AI)
• Compliance requirements
• Approval workflows

Start by auditing current AI tool usage, then draft policies addressing the biggest risks. Form an AI steering committee to oversee policy enforcement.

Read the full AI policy guide

What is an AI Steering Committee?

An AI Steering Committee is a cross-functional governance body that oversees AI initiatives. It typically includes:

• Executive sponsor (CEO, COO, or CTO)
• IT representative
• Legal/Compliance representative
• Operations leader
• HR representative

The committee makes decisions about AI policy, tool approval, and implementation priorities.

Learn how to form a steering committee

What is an AI Maturity Framework?

An AI maturity framework assesses organizational readiness for AI across multiple capability areas. The AutomationTactics framework evaluates eight areas:

View the full AI Maturity Map

What is Human-in-the-Loop AI?

Human-in-the-Loop AI is an automation design pattern where AI handles routine tasks but humans review and approve critical decisions before execution. This ensures accountability, catches AI errors, and maintains human oversight. For example, AI drafts customer responses, but a human approves each one before sending.

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What is the difference between RPA and AI?

RPA (Robotic Process Automation) automates repetitive, rule-based tasks by mimicking human clicks and keystrokes. It works best for structured processes with clear rules. AI can handle unstructured data, make judgments, and learn from examples. Modern implementations often combine both: RPA for routine tasks and AI for exceptions requiring interpretation.

See RPA definition