Developing a Generative AI Marketing Strategy
Apply strategic frameworks like HBR's DARE to build phased roadmaps and align AI initiatives with business goals.
Learning Objectives
- • Apply the DARE framework to structure AI initiatives
- • Create a phased implementation roadmap (Crawl, Walk, Run)
- • Align AI projects with core business objectives
Moving Beyond Random Acts of AI
Many organizations are currently stuck in a phase of "random acts of AI"—scattered experiments with no cohesive strategy. To unlock real value, marketing leaders must transition to a strategic approach that aligns AI capabilities with business goals.
The Strategy Gap
While 90% of marketing leaders believe AI is critical for success, only 17% have a comprehensive strategy in place. This gap represents a significant competitive opportunity for those who move first to formalize their approach.
The DARE Framework
Harvard Business Review's DARE framework provides a robust structure for AI implementation in marketing:
1. Decompose
Break down marketing roles and workflows into individual tasks. Identify which specific sub-tasks are ripe for AI augmentation or automation.
2. Analyze
Evaluate the potential value and feasibility of applying AI to each decomposed task. Look for high-volume, repetitive, or data-heavy tasks.
3. Realize
Implement pilot programs. Select the right tools, train the team, and execute on the identified high-value opportunities.
4. Evaluate
Measure the results against KPIs. Assess not just efficiency gains, but improvements in quality and creative output.
The "Crawl, Walk, Run" Roadmap
A successful strategy requires a phased approach to manage risk and build organizational muscle memory.
Phase 1: Crawl (Months 1-3)
Focus on individual productivity and low-risk experiments.
- • Goal: Familiarity and quick wins
- • Actions: Enable ChatGPT/Claude for all staff; training on prompt engineering; use for drafting emails, brainstorming, and summarizing.
- • Governance: Basic usage policy and data privacy guidelines.
Phase 2: Walk (Months 4-9)
Focus on team workflows and integrated tools.
- • Goal: Process transformation
- • Actions: Implement enterprise tools (Jasper, Midjourney); integrate AI into content production workflows; pilot personalized email campaigns.
- • Governance: Quality control processes; brand voice fine-tuning.
Phase 3: Run (Months 10+)
Focus on business transformation and custom solutions.
- • Goal: Competitive advantage
- • Actions: Fine-tune custom models on proprietary data; automate complex customer journeys; real-time personalized content at scale.
- • Governance: Advanced ethics review; automated compliance checks.
Aligning with Business Objectives
Your AI strategy must serve your broader business goals. Map AI capabilities directly to key performance indicators (KPIs).
| Business Goal | AI Strategy | Key Metrics |
|---|---|---|
| Increase Revenue | Hyper-personalized upselling; predictive lead scoring | Conversion rate; Average Order Value (AOV) |
| Reduce Costs | Automate content repurposing; AI customer support | Cost per acquisition (CPA); Support ticket cost |
| Improve CX | 24/7 personalized chatbots; faster response times | NPS; CSAT; Retention rate |
| Accelerate Speed | Rapid prototyping; automated campaign generation | Time-to-market; Campaign frequency |
Strategic Imperative: Don't just ask "What can we do with AI?" Ask "What should we do with AI to drive our specific business goals?" Strategy leads; technology follows.