83% of modern companies have stated that the use of artificial intelligence in their business strategies is their top priority. Moreover, 9 out of 10 organizations support artificial intelligence to gain a competitive advantage (Authorityhacker 2024). This growing interest in AI has contributed to the increasing popularity of CRM systems, including Dynamics 365 solutions.
About artificial intelligence
Artificial intelligence is inspired by the neural structure of the human brain, and in its routine activities, it utilizes multi-level data processing — from algorithmic applications to deep learning methods and cognitive processing.
Today, large amounts of data take electronic form, and enormous amounts of information are systematically collected — in virtually every industry. As a result, AI-based tools process and interpret raw data, which is then used in various fields — from medicine and gaming to customer service in CRM systems.
The intensified use of AI began at the beginning of the 21st century, when processed data allowed for a deeper understanding of consumer behavior and preferences. Previously, the limited number of variables did not allow for hypothesis formulation and advanced scientific research, significantly limiting business activities. Artificial intelligence, based on machine learning, especially through deep learning technology and artificial neural networks, introduced organization and systematization.
Use cases of AI in CRM systems
Sales forecasting
The use of AI in CRM for sales forecasting allows companies to predict future outcomes based on the analysis of historical sales data. AI applies statistical models and machine learning to identify patterns and trends, such as seasonality, demand for specific products, and the impact of promotional activities on sales. This helps managers better plan sales strategies, manage inventories, and optimize marketing efforts to maximize revenue.
Lead optimization
AI can significantly improve the lead management process by automatically scoring and qualifying them. The CRM system uses machine learning algorithms to analyze data from various sources, such as website interactions, email campaign responses, and demographic data, to assess the likelihood of each lead converting. Based on this, AI assigns a score to each lead, helping sales teams focus on the most promising prospects. Additionally, the system can automatically segment leads based on their scores, enabling a more personalized approach.
Customer service and chatbots
The implementation of AI chatbots transforms customer service by offering quick and efficient solutions. This aligns with expectations and trends that show consumers highly value fast, effective, and specific service. Chatbots use advanced natural language processing (NLP) technologies to understand queries and provide answers. They can automatically resolve standard issues such as checking order status, providing product information, or assisting with returns. This reduces the workload for customer service staff and shortens waiting times for customers. In more complex cases, the chatbot can direct the query to the appropriate employee.
According to AuthorityHacker (2024):
- 52% of telecommunications companies currently use AI chatbots.
- 57% of B2B companies have used chatbots to better understand their audiences.
- 75% of consumers feel comfortable with chatbots handling routine customer service tasks, while only 33% accept chatbots managing complex queries.
All these AI use cases in CRM systems demonstrate how the integration of advanced technologies can significantly improve business process efficiency — from sales to customer service, ultimately leading to increased satisfaction and higher company revenues.
