This paper examines the impact of big data analytics and artificial intelligence technologies on improving digital marketing and demand forecasting. It also analyzes the ethical and policy issues of AI-powered marketing and analytics, focusing on consumer engagement and the scalability of the organization. This study is undertaken using the analytical literature approach, with case studies from global corporations like Amazon and Walmart. It examines traditional forecasting models alongside big data-driven approaches, outlining the barriers to the adoption of modern analytics and AI technology faced by small and medium enterprises (SMEs) and mid-size companies. The findings demonstrate that big data and AI technologies enhance forecasting precision by capturing real-time analytics from consumers, social media, and other macroeconomic factors. AI-powered digital marketing facilitates hyper-personalized customer engagement, reinforcing loyalty. On the other hand, on the responsible adoption of AI, issues like data privacy, algorithmic discrimination, and abiding by compliance frameworks like GDPR and CCPA still pose challenges. This underscores the need for organizations to construct frameworks for responsible AI, outline data usage policies, and sustain scalable models.