Generative AI, particularly in the form of ChatGPT, is expected to be the buzzword of 2023 with its rapid development and rollout. While concerns about regulation and biases exist, Generative AI has already started making significant changes, particularly in the field of analytics. It has the potential to overcome bottlenecks and deliver insights that humans cannot process at a rapid pace. Goldman Sachs estimates that generative AI could boost global GDP by 7% and increase productivity growth by 1.5 percentage points over the next decade.
Business leaders cannot ignore the partnership between generative AI and Predictive Analytics as they seek to optimize inventory, budget stock, and work more efficiently with supply chains. The technology can analyze large datasets, identify trends, and predict future customer demand or changing consumer preferences. In the events industry, generative AI is being used to analyze attendee data from past events and gain insights for future events. This allows event organizers to make data-driven decisions.
Predictive analytics goes beyond sentiment analysis and considers metadata, external factors, and specific conversions to provide a comprehensive analysis of demand. JetBlue, for example, has implemented an AI-based customer service solution that saves time for agents by learning from customer sentiment and recurring queries to make actionable recommendations.
Generative AI models like ChatGPT can build deep analytic models by using data to create software code. This allows for automation in decision-making support and the development of bespoke training programs based on employee skillsets. Programs can also work with other analytical platforms to make automatic improvements to websites and forecast future traffic.
While generative AI has its limitations, businesses can still use it for content creation and to support decision-making. However, businesses should prioritize privacy and ensure they comply with regulatory frameworks. Generative AI has the ability to anonymize sensitive data and generate synthetic data without identifiable information, which can be beneficial in industries like pharmaceuticals.
In conclusion, generative AI has the potential to bring about significant changes and opportunities for businesses. While there is still work to be done in terms of regulation, businesses can leverage generative AI and predictive analytics to improve operations, make data-driven decisions, and enhance the customer experience.
