# Rethinking Demand Generation with AI Integratio nArtificial Intelligence (AI) is revolutionizing demand generation, which significantly reshapes how marketers approach lead generation and conversion. ## The Evolution of AI in Demand Generatio nTraditionally, the demand generation process relied heavily on manual efforts by human marketers and Sales Development Representatives (SDRs). Everything from email campaigns to LinkedIn outreach was managed by people, and while effective, it was time-intensive and limited by human capacity. The arrival of AI marked a shift from these manual processes to a more automated approach. Initially, AI played a ‘co-pilot’ role, assisting humans and enhancing their productivity by suggesting copy or timing outreach. However, as technology advanced, AI began to autonomously handle tasks, paving the way for what is now an agentic phase, where AI operates more independently in demand generation roles. ## Implications of AI on Human Roles A heated debate surrounds the potential replacement of human SDRs with AI counterparts. Critics argue that outsourcing these roles to AI might eliminate valuable entry-level job opportunities that serve as stepping stones in sales careers. Nevertheless, a consensus emerges that no one aspires to remain an SDR indefinitely due to the job's high-pressure nature and limited growth potential. Thus, AI’s entry allows companies to rethink not just roles but also redefine career paths, like hiring entry-level roles directly into full-cycle Account Executive (AE) positions or AI management roles. ## AI Onboarding and Integratio nTo ensure campaign quality, the onboarding of AI systems like Piper—an AI SDR—mirrors that of human training. Companies must provide relevant content, including website data and marketing materials, to help AI systems understand the brand’s voice and guidelines. The initial phase involves diligent testing of AI responses to frequently asked questions, refining them until satisfactory. The transition from this ‘crawl’ phase, where AI operates with limited scope (like after-hours or weekend duties), to a broader ‘walk’ application parallels human training. AI systems initially assist with qualifying incoming leads and transition into a more autonomous role upon proven reliability. ## Real-world Applications and Challenges Many companies successfully leverage AI in managing inbound queries. By filtering through traffic and enhancing conversion, AI systems free up human resources to focus on strategic activities rather than routine follow-ups and outreach. With examples from companies achieving increased pipelines and meeting bookings, the potential benefits are clear when implemented with substantial web traffic. However, before AI can deliver its full benefits, companies must first establish a sound brand strategy and ensure sufficient inbound traffic. AI is not a panacea but acts effectively as a filter to optimize existing efforts. ## The Build vs. Buy Dilemma Organizations face decisions between building their AI solutions or purchasing existing ones. While building offers customization, it demands significant time, expertise, and resources. On the other hand, buying proven solutions could deliver faster returns and stability with a smaller initial investment. The decision largely hinges on evaluating time investment, team capability, and existing market solutions that align with organizational needs. ## Conclusio nAI’s growing role in demand generation ultimately challenges traditional ways of thinking, offering efficiency and refined targeting strategies. While it may reshape how early-career roles in sales unfold, it presents an opportunity for organizations to redefine how they engage customers and cultivate talent. Looking ahead, AI solidifies its role as a cornerstone of modern demand generation strategies for companies ready to i ovate.