The HR Tech space is flooded with AI promises: instant talent, bias-free hiring, predictive success. For a C-suite leader under pressure to act, it’s a minefield of "vapourware" and flashy demos that fall flat in practice.

As we've established, a bad Infrastructure investment is not just a sunk cost; it's a direct threat to your Cost of Hire Ratio (CoHR Blog 1.1) and exposes the business to massive Compliance Risk.

This is where the "Canal Logic" (task-based) vs. "Railroad Logic" (system-based) becomes a critical purchasing framework.

The "Canal" vendor tries to sell you a "feature"—a faster way to do a single, broken task. The market data shows this is failing. 87% of companies have adopted AI for simple, top-of-funnel tasks, yet only 11% are doing deep, strategic integration. This gap is why buyers report higher Importance (7.9/10) for AI than Satisfaction (6.9/10). They bought a faster boat but are still stuck in a slow, shallow canal.

A "Railroad" vendor sells you a system—an integrated platform that supports your entire Ecosystem Playbook.

The Business Outcome: Protecting the CoHR and Mitigating Risk

Your due diligence must focus on protecting your CoHR by avoiding costly, ineffective tech. This requires tough, pointed questions that move beyond features and focus on implementation.

Before you sign any contract, ask your vendors these questions:

1. Data Integrity (The Bias Question): "What data is the AI trained on?"
   This is the most important question. If the data is not transparently sourced, is biased, or is inaccurate, the AI will simply automate that bias at scale. This exposes you to legal risk and destroys your Quality of Hire. Demand transparency on their training data and their methods for bias mitigation.
2. ROI Verification (The CoHR Question): "Can you show me real ROI, not just activity metrics?"
   Do not accept "we sourced 50% more candidates." That is a "Canal Logic" metric. Demand "Railroad Logic" proof. Ask for case studies focused on CoHR and TtHR reduction. A true ecosystem partner will be able to show how their Infrastructure enables the Rediscovery (Blog 3.3) of your 1st Party Data, delivering a hard, quantifiable return.
3. Support Model (The Ecosystem Question): "What does your Customer Success model really do?"
   You do not need another passive vendor. You need a strategic partner who will reinforce your Playbook. Your Customer Success team should be a "cadre of strategic partners" who challenge your assumptions, share best practices, and help you enforce the Kickoff Meeting (Blog 2.1) discipline. Their job is to make your team Snipers (Blog 1.4), not just button pushers.

One platform I've used successfully is hireEZ, which has a strong focus on this AI-First, People-Centric model. But regardless of the tool, your standard must be high. Your Infrastructure must augment human expertise, not just try to replace it.

The single most important factor in vetting AI is its training data. This brings us back to the foundational human skill required for governance. In Blog 2.5, we define the new core competency for your human Players: Understanding Data.