Don't expect an AI agent to invent a successful sales process. First, have your human team identify and document what works—effective emails, scripts, and objection handling. Then, train the AI on this proven playbook to execute it flawlessly and at scale. The AI is a scaling tool, not a strategist from day one.

Don't deploy an AI SDR to find product-market fit or create a sales motion from scratch. It's a tool for amplification. You must first prove that a human can successfully sell your product with a specific playbook, then feed that playbook to the AI.

Contrary to the common 'instant results' narrative for AI, implementing an enterprise-grade data solution like Kernel.ai takes around four weeks. The process involves structured configuration, running large sample sets, and enabling actions like merging accounts. Complex enterprise CRMs require time and a dedicated process to properly integrate and clean.

An AI SDR is not a fully autonomous employee. To avoid idle agents and wasted investment, you need at least one dedicated person to manage, segment, and feed it new context, plus a backup to ensure continuity. It's an active management role, not a 'set and forget' tool.

Don't just "turn on" an AI sales agent and expect results. The only path to success is to first identify what works with your human reps—the scripts, the process, the data. Then, you must manually train the AI on that proven playbook, iterating and refining its performance daily for at least a month. The AI automates success; it doesn't create it from scratch.

Vendors selling "one-click" AI agents that promise immediate gains are likely just marketing. Due to messy enterprise data and legacy infrastructure, any meaningful AI deployment that provides significant ROI will take at least four to six months of work to build a flywheel that learns and improves over time.

Don't abandon AI after one bad result. Treat it like a new SDR and use a 'shuttle run' approach: give it a small task (find 5 accounts), review the output, provide feedback, and repeat for each step (contacts, emails). This upfront calibration is crucial for long-term success.

Implementing AI effectively isn't about finding a magic prompt. It requires an R&D mindset: investing time to build proprietary systems. Expect a learning curve and failed experiments; the goal is building a long-term competitive edge, not an overnight fix.

You can't delegate AI tool implementation to your sales team or a generalist RevOps person. Success requires a dedicated, technical owner in-house—a 'GTM engineer' or 'AI nerd.' This person must be capable of building complex campaigns and working closely with the vendor's team to train and deploy the agent effectively.