How to Choose (and Actually Use) AI Tools

Oct 14

Most AI flops aren’t about the tech. They happen because we pick tools without a goal, don’t check fit with our setup, and never run a clear process. This approach can fix that.

Here’s the “rubric” in a nutshell:

Outcome first → pick one measurable win.
Category, then brand → map the job-to-be-done before shopping.
Stack fit → verify login, data, and workflow integration.
Pilot with playbooks → one or two repeatable flows, time-boxed.
Data & governance → protect sensitive info, set light approvals.

Start with the outcome

Don’t start with a tool. Start with a win you can measure.

Pick one, like:

Revenue: “Book 4 more sales calls this month.”
Time: “Cut report writing from 90 → 30 minutes.”
Quality: “Raise email reply rate from 8% → 15%.”

Write this down (one line each):

Who benefits?
When will you run it? (daily 8:30 a.m., Fridays, etc.)
How will you measure it? (baseline + target)
Who owns it?

If you can’t answer these, you’re not ready to pick a tool.

Pick a category first, then a brand

Tools change fast. Jobs don’t. Categorize the job(s) you want done, then choose a brand that fits.

Examples:

“Summarize a long PDF” → General chat/analysis (then pick ChatGPT, Claude, or Perplexity).
“Make a flyer and matching social post” → Design suite (then pick Canva).
“Create hero images” → Image generator (then pick Midjourney, DALL·E, or SDXL).
“Move leads from form → CRM” → Automation (then pick Zapier AI).

Quick score (1–5): Fits the job, output quality, easy for our team, data controls, price. Keep the top 1–2. Ignore the rest for 30 days.

Here’s a short list of categories and corresponding tools:

  
      Category
      Tools
    
      General Chat & Analysis
      ChatGPT, Claude, Perplexity
    
      Work Copilots (Email, Docs, Slides)
      Microsoft Copilot, Google Gemini
    
      Design & Marketing Assets
      Canva Magic Studio
    
      Images (Concept Art, Product Shots)
      Midjourney, DALL·E, Stable Diffusion XL
    
      Video (Ads, Explainers, Mood Reels)
      Runway Gen-3/4
    
      Voice & Audio
      ElevenLabs
    
      Coding & Tech Delivery
      GitHub Copilot, Cursor
    
      Automation & Orchestration
      Zapier AI
    
      Docs / Knowledge & Team Notes
      Notion AI

💡Download our full AI Reference Guide. It provides a quick look at popular AI tools, what they are good for, and a few more important details to help you choose.

Evaluate Fit with Your Stack

When it comes to choosing the right AI tool for an enterprise-level solution, a flashy demo isn’t enough—real adoption happens only when a tool fits your existing stack and your team’s needs. Here’s a practical evaluation checklist to include in your decision process, helping you avoid stalled rollouts and hidden risks.

Before adopting any AI tool, run through these critical checks:

Authentication & Access

Does the platform support enterprise-grade sign-in, such as Google or Microsoft SSO, or SAML? This ensures secure, scalable access and easy user management.
Is there granular, role-based permission control so you can specify which users get access to what functionality?

Productivity Suite Integration

Make sure the tool connects directly with your core workspace: Can it read, write, or create files in Google Docs/Sheets/Drive, Microsoft Word/Excel/SharePoint/Outlook?
Look for official add-ins, plugins, or APIs—avoid tools that only export/import via CSVs or require manual uploads.

Workflow & CRM Compatibility

Check for ready-made connectors to your business-critical platforms: CRM (HubSpot, Salesforce), helpdesk (Zendesk), and project/workflow software (Asana, Jira, Slack).
Ask whether integrations are native, or if you need extra middleware, plugins, or developer support to make things work.

Compliance & Governance

Does the tool provide robust compliance features for business users? Essentials include:
- Data retention policies and archiving controls
- Audit logs that track edits, deletes, and permissions
- Administrator panel with data privacy management
- Certification (SOC2, GDPR, and other relevant regulatory concerns)

What to Watch For

Green Flags: Verified listings on the Microsoft 365 or Google Workspace app store, a configurable admin panel, real-time audit trails, enterprise-grade documentation.
Red Flags: CSV-only integration, personal (non-business) email sign-in, missing data retention or compliance documentation, unresponsive vendor support.

Pro Tips

Request a vendor demo that walks through a workflow in your preferred stack—and make them show compliance features “live.”
Pilot the tool in one department first to uncover practical challenges before a full roll-out.
Document integration scenarios for onboarding and troubleshooting; never rely solely on sales promises.

By investing extra time early to check for true stack fit and compliance controls, you’ll dodge costly surprises and lead your team to AI adoption that truly sticks.

Pilot with 1–2 small playbooks

“Let’s try it” is not a plan. A playbook is a short, repeatable process.

Pick one per outcome, like these:

Daily Outreach (15 min/day)
Draft in ChatGPT/Claude → add one personal line → send → log in CRM.
Measure: replies and meetings booked.
Idea → Post → Visual (≤30 min)
Outline in Notion/ChatGPT → draft → design in Canva → schedule.
Measure: engagement, clicks, inbound DMs.
Lead-Capture Automation (60–90 min)
Form → AI summary/score → CRM → Slack ping → simple dashboard.
Measure: time to triage, booked calls from “hot” leads.
Dev Acceleration
Unit tests with Copilot/Cursor → short release notes → 45-sec video.
Measure: coverage up, fewer support questions.

Rules: time-box setup to 90 minutes; run 10–15 cycles; save inputs/outputs. After two weeks: keep, tweak, or kill.

Data & governance (light but real)

Trust matters. Enough said, right?

Three buckets:

Public: safe to share (marketing copy).
Internal: for your team only.
Restricted: PII, contracts, secrets — keep out of consumer AI tiers.

Simple rules:

Use business/enterprise logins when you can.
One quick human review before posting externally.
If the tool cites sources, skim them.
Keep a short Run Log (date, tool, prompt link, output, approver).

Two quick examples

A) Solo Realtor

Outcome: 3 more listing appointments this month.
Category → Tool: General chat + design (ChatGPT + Canva).
Playbooks: Daily Outreach; Idea → Post → Visual.
Data: No client PII in prompts; one-review rule for posts.
Measure: reply rate, appointments, post engagement → site clicks.

B) Nonprofit Training Program

Outcome: Cut intake time from 7 days to 3.
Category → Tool: Automation + chat (Zapier AI + ChatGPT).
Playbooks: Lead-Capture Automation; Idea → Post → Visual (alumni stories).
Data: Keep sensitive info out of AI steps; bypass fields if needed.
Measure: time-to-triage; % of “hot” leads contacted in 24 hours.

Final word

AI is a toolbox. Pick the job, choose the right category, make sure it fits, run a small playbook, and protect your data. Do that, and you’ll see results fast—without burning time or budget.

Need help putting it all together? Talk to us!

Want to learn more about AI? Join an upcoming virtual AI coaching session!

Joel Wells