AI won't fix bad go-to-market strategy or make mediocre marketing better. Instead, leverage it to dramatically increase the speed and scale at which you can execute existing strong strategies. Focus on AI as an enablement layer that fast-tracks painstaking operational activities rather than expecting it to generate strategy.

Rather than using AI for surface-level tasks, invest in training models on your ideal customer outcomes. This enables rapid validation of secondary and tertiary ICPs in enterprise selling, turning what used to be weeks of manual account mapping into automated processes that scale with your growth.

Move beyond binary account triggers to sophisticated probability-based scoring. Use AI to analyze multiple supplemental signals simultaneously, apply custom weightage based on your organization's data, and create pre-conversion assessments that identify prospects most closely aligned with your ICP before engagement.

Establish formal processes for testing new AI applications across your team. Look beyond mainstream solutions to Reddit, Product Hunt, and emerging creator tools. Many offer free access for testing, allowing you to filter genuine value from "GPT wrapper" solutions before making investments.

While AI can significantly boost content velocity, establish clear quality standards. Use AI for ideation and first drafts, but maintain human oversight for final outputs. The goal should be doubling content production while preserving the qualitative aspects that drive consumption and engagement.

Identify the most resource-intensive, repetitive tasks in your marketing operations first. List cleaning, lead routing, data enrichment, and reporting often provide the highest ROI for AI implementation. These foundational improvements create efficiency gains that compound across all marketing activities.