AI automation vs traditional automation
Traditional workflow automation moves data between systems on fixed rules: "when a new form is submitted, create a CRM record and send a Slack message." Zapier, Make, Power Automate. Predictable, reliable, but rigid — every condition has to be specified up front.
AI automation adds language-model judgment to that flow: "when a new form is submitted, read the message, classify intent (sales / support / spam / partnership), draft a personalized reply matched to that intent, and route to the right person." The LLM is the judgment layer; the workflow plumbing still runs underneath.
Missed-call follow-up
When an inbound call goes unanswered, AI drafts a text-back response that references the time of day, any prior history (returning customer? service callback?), and routes the reply to the right team member. Productized SaaS exists at this layer (Numa, etc.) but custom builds outperform on shops with non-standard workflows.
Customer reactivation
Dormant customer records get pulled from the CRM. AI reads each customer's service history and generates a hyper-personalized SMS or email that references their actual past work — equipment age, last service date, seasonal context. The Cassidy HVAC reactivation engine using this approach recovered over 60% of dormant patients within 6 weeks.
Document and invoice processing
Inbound documents — invoices, BOLs, rate confirmations, intake forms — get read by an LLM, key fields get extracted (vendor, amount, date, line items), and the data lands in the right system without a human transcribing it. HG Oil Holdings' AI invoicing assistant cut manual handling time by 75% and freed staff for higher-value work.
Lead scoring and routing
Inbound leads (form submissions, email, chat) get classified by intent and priority by an LLM. High-intent leads get routed to the sales pipeline with a pre-drafted reply; low-intent leads get an autoresponder and a tag; spam gets discarded. Saves hours per week of manual triage.
Red flags in vendor pitches
The AI automation space is full of vendors selling rebadged Zapier. Specific red flags:
- The vendor can't tell you which LLM is in the loop or how it's prompted.
- The "AI" is actually a decision tree with branching IF/THEN rules dressed up in modern UI.
- The pricing is wildly out of line with token costs (vendor markup beyond reasonable margin).
- The vendor refuses to show you the actual outputs the AI produces — "that's proprietary."
- The demo only works on the vendor's pre-built example, not your real data.
