A Maturing Market With Uneven Quality
The AI automation vendor market has exploded. Everyone claims to offer enterprise-grade AI – but the gap between marketing claims and delivered outcomes is wide. Here is what every technical leader should evaluate.
Architecture and Scalability
Ask vendors to describe their system architecture. Red flags: monolithic systems, no monitoring built in, vendor lock-in on proprietary tools. Green flags: modular design, documented APIs, infrastructure you can audit.
Data Security and Compliance
Where does your data go? Is it used to train shared models? For Canadian businesses, PIPEDA compliance is non-negotiable. Look for SOC 2 Type II as a baseline for enterprise vendors.
Implementation Methodology
The best vendors have a structured process: discovery, design, build, test, launch, optimize. Be wary of vendors who jump straight to build without thorough discovery.
Measurable Outcomes
Demand specific KPIs upfront: hours saved per week, cost per processed transaction, lead response time. Any vendor confident in their system will agree to outcome-based metrics.
Post-Launch Support
AI systems require tuning after launch. Ask about SLAs, dedicated success managers, and processes for reporting issues and requesting changes.
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