Challenge 4:

AI tooling and options are simply exploding. No doubt your teams will have access to LLMs which they can leverage on a personal basis. Your existing tech stack will probably be adding AI tooling within those platforms. The key is to take a step back and look at your 1:1, 1:Few and 1:Many ABM workflows. The most logical thing to do is to look at them to see where AI can drive efficiency (faster insight), effectiveness (faster personalization) and optimization (better measurement and attribution). Validate how your existing techstack can help, and identify areas where you may need to pilot new AI workflows.

Actionable Tip: Run an AI Readiness Workshop across marketing, sales, and ops to align goals, identify gaps, and create a 90-day AI integration roadmap for ABM.

AI is a powerful co-pilot—not the driver. Its real strength lies in speed, scale, and pattern recognition. Use it to accelerate high-effort, repetitive tasks: drafting outreach messages, summarizing large volumes of account intel, or surfacing engagement patterns across complex buying groups.

However, you still need the human layer for insight, creativity, and judgment—especially in high-value 1:1 or 1:few programs. Treat AI outputs as raw material to be refined by your strategists, writers, and account teams. The best results come when AI handles 70% of the lift and humans shape the final 30% for relevance and quality.

Actionable Tip: Create an internal “AI Workflow Model” that clearly defines which tasks are AI-generated, which are human-edited, and who owns final QA. This ensures quality control at scale.

AI unlocks the holy grail of ABM: personalization at scale. You can dynamically adapt messaging based on industry, role, funnel stage, or behavior. But this only works if you have a solid personalization framework and brand guidelines in place. Without these, you risk generic, off-brand, or even risky output.

Start by creating templated structures with variable fields for headlines, proof points, and CTAs. Use AI to populate these fields based on CRM data, engagement history, or firmographics. Set guardrails around tone, language, and compliance to ensure consistency across channels and regions.

Actionable Tip: Build a “Personalization Engine” using AI + structured templates. Tag your content assets by persona, industry, and funnel stage so AI can match the right messages to the right accounts, automatically.

AI shouldn’t sit on the side—it should be deeply embedded across your ABM operating system. This means integrating it into your CRM, MAP, ABM platforms, and orchestration tools. When done right, AI can help identify ideal accounts, score buying intent, trigger outreach, adapt messaging, and optimize campaigns in real-time.

Use AI for predictive scoring, lead-to-account matching, signal monitoring, and engagement analysis. Connect it with your data lake or CDP to ensure it has access to clean, rich data. And integrate outputs directly into sales workflows—whether that’s surfacing next-best-actions or suggesting personalized follow-up messages.

Actionable Tip: Appoint an “AI in ABM” lead or squad. Their role: ensure that AI tools align to strategy, connect seamlessly with the tech stack, and deliver real-time value without disrupting workflows.