Tremendous progress of AI has significantly changing the customer decision management by green signal towards organizational process at large and complexity in data management and which predict the standardised concept and insights towards AI. AI based mechanism utilises the techniques such as language processing, machine learning and predict the customer decision. It facilitates the real time decision making also. As a result, companies must transform them self to adaptive AI strategy for customer engagement. From the point of behavioural aspects the customer decision is influenced by several factors such as cognition, emotions and conditional social context. AI always helps in classification of behaviour patterns and focused on customer interaction across the digital platform. AI enables the personalised information, smart automation and real time insights. Instead of advantages the application if AI in customer decision with behavioural, irrespective of its advantages the application of AI in CDM (Customer decision management) create significant behavioural, ethical and fair governance concerns. The behavioural analysis of AI driven aspects on decision system is very essential to examine the influence on CDM and to have a sustainable customer relationship. This study contributes to the existing studies by examining the relationship between user trusts, recommendations of AI on CDM in present condition. This article used survey based research method with simple statistical tools to describe the objectives and AI influence on CDM. Artificial intelligence is a new platform for every activity in market. Post pandemic shifted traditional method of purchase decision to modern management decision with the help of AI. Trust on AI and recommendations of AI generated   aspects    influence   on CDM.  Additionally, when users are satisfied with their interactions such as receiving quick responses, accurate suggestions, and a smooth experience they become more engaged and open to following AI guidance. All three of these factors come together to shape Customer Decision Management, which represents how individuals think, compare options, and decide based on AI inputs. Ultimately, this AI-influenced decision process leads customers toward their final Purchase Decision (Figure 1).

Figure 1: Study Model

Now a days tracking the existing customer is a challenging for a marketer due to rapid changes in market environment due to technology intervention. Artificial intelligence makes marketer to collect personalised content of customer and modify the product or service according to customer needs. AI emphasised the operational efficiency to personalisation more effectively and moving to improve the impact on consumer purchase decision. There are several online platforms reviews emerged as new concept created customer relationship management which enhance the customer purchasing decision in present conditions of Market [1]. Artificial intelligence always impacting significantly on retailing and AI become very popular way of focus on customer behavior in market. The marker must be optimistic in implementation of new strategies through AI [2]. The crucial development of market environment has changed the customer’s way of shopping. There is a growing number of web shops integrated new technology such as AI which improve the customer experience and level of satisfaction [3].  AI emerged as basic applications for broad range of expert demines. the AI based solutions play a crucial role in present, market condition. AI spreading their operation in every corner of business such as production, logistics and digital marketing. The author found that it is feasible to develop AI based marketing insights solutions for speedy customer satisfaction [4]. The rise of advanced technologies has significantly expanded the role of AI in digital marketing. AI tools are now frequently utilized for risk assessment, consumer research, and for integrating business operations with the preferences of targeted customers. At present, it’s still uncertain whether AI-driven digital marketing will guarantee success. Research also shows that when digital marketing strategies are poorly executed, they can lead to harmful outcomes for businesses [5]. The rise of AI in digital marketing allows organizations to automate many marketing functions. This automation not only streamlines operations but also generates valuable data assets that further strengthen and support AI-driven decision-making [6].

The present study adopted clear narrative review of literature on several dimensions on the present topic. The extensive review has been done and found that there is lack of studies on user trust and satisfaction of a customer by AI integration.  AI driven strategies has occupied every corner of business activities. This is very significant to study the several factors in present situation. This is futuristic study and this can focus on what next strategy in business.

Objectives of Study

• To understand customer awareness and perception
• To identify the difference of trust on AI in customer decision management
• To examine the influence of trust on AI on customer decision management

Difference of Trust on AI in Customer Decision Management

• H0: There is no significant difference in user trust of AI on customer decision management
• H1:There is a significant difference in user trust of AI on customer decision management Influence of trust on AI 

 Customer Decision Management

• H0: There is no significant Influence of user trust of AI on customer decision management
• H1: There is a significant Influence of user trust of AI on customer decision management Research 

Methodology

In this research article descriptive research used to describe the phenomena. The survey method has been used to collect the primary data by simple random sampling with well-defined statements along with Likert scale method with a sample size of 88 respondents. The simple statistical analysis has been done such as one sample t-test, regression, ANOVA to prove hypothesis. Variables of the study: in this study Artificial Intelligence belongs to independent variable user trust, AI recommendation and AI satisfaction these are mediating variable and  customer decision management and  purchase decision are dependent variable This table shows that most respondents are female and young, mainly between 18–35 years. A majority are working professionals, with fewer students, homemakers, or business owners. Most participants earn between ₹10,001–₹25,000, indicating    that     the   sample    largely represents lower-middle to middle-income individuals. Overall, the respondents are predominantly young, employed, and moderately earning Table 1.

Table 1: Demographic Profile of Respondents

Source: Primary Data

The obtained Cronbach’s Alpha of 0.854 demonstrates that the 11 items in the scale have strong internal reliability. This suggests that the items are closely related to each other and consistently measure the intended concept, making the scale suitable and trustworthy for analysis Table 2.

Table 2: Reliability Statistics

Sources: Primary Data

The above analysis table shows the one sample test used to identify the differences between sample mean and population mean. The result shows there is a significant difference with p-value 0.000 which is less than 0.05.   Therefore, reject the null hypothesis and accept the alternative hypothesis Table 3.

Table 3: One-Sample Test

Sources: Primary Data

The represents the T –Test for various variables showing significant deviations from zero. For age the t- value is 19.189 with mean differences of 1.93182 (CI- 1.7317-2.1319). Gender T value 30,911 with mean differences of 1,61364(CI – 1.5099-1.7174) Occupation of respondents  T value  is 19.070  with mean difference of 2.20455 (CI-1.9748-2.4343)Monthly income level of respondents T value 25.899 with Mean differences of 2,51136 (2,3186-2,7041), user trust represents the T value 36.822 with mean differences of 2.14394 (CI- 2.0282-2.2597), purchase decision T value 41.867 with mean differences of 2.21212 (2,1071-2,3171), artificial  intelligence  recommendation T value 37.831 with mean differences of 2.30682(2.1856-2,4280), artificial intelligence satisfaction T value is 23,763 with mean difference of 2,09091 (1.9160-2.2658).  Therefore, Reject the null hypothesis and accept the alternative hypothesis Table 4.

Table 4: One-Sample Test

Sources: Primary Data

The above analysis described that the influence of user trust on customer purchase decision. The r square shows 0.204 and beta value 0.452 which means there is 45% of user trust influence on purchase decision with f value 22.084 which is greater than F table value 3.95.This is evidenced that p-value 0.00. Therefore, reject the null hypothesis and accept the alternative hypothesis. Hence, significant influence of User trusts AI on Consumer purchase decision Table 5-6.

Table 5: Model Summary

Table 6: ANOVAa

Sources: Primary Data

The above analysis explained that influence of AI recommendations on customer purchase decision. The r square 0.351 and beta 0.592 which means there is 59% of AI recommendations influence on customer purchase decisions. With F value 46.438 which is greater than F critical value 3.95 and p value less than 0.05. Therefore, reject the null hypothesis and accept the alternative hypothesis Table 7-9.

Table 7: Model Summary

Table 8: ANOVAa

Sources: Primary Data

Table 9: Suggestion for AI Application and Customers

• The study found that customers have differences of opinion regarding AI usage in day to day activit Some customers don’t recognise the usage of AI in some purchasing activities due to lack of knowledge regarding AI application
• Now a day’s its very crucial to believe technology in every corner of human life due to fear of digital arre But in case of purchasing activities more number of usage belongs to online with the help of AI due to trust. It’s challenging for everyone to find proper AI applications for the activities. This study found that majority of customers influenced by trust on AI in purchasing activities
• Present day customer is volatile in nature due to several avenues and platforms available for purchasing activities. The customer decisions based on several influential factors such as advertisements, publicity, price and mouth to mouth recommendations. The integration of technology in purchasing activities influenced by recommendations and review systems in AI
• The key terminology used in AI is highly recommended which create more interest on the specific produc If the product doesn’t have any words in the blog as recommended, then the customers never use to read that product. Rating strategy also more eye catching strategy to attract the customers and change the customer purchase decision. Sometime the price of the product depends on the demand the AI application rapidly change the price accordingly the customers also change the purchase decisions

The study concludes that Artificial Intelligence plays a decisive role in customer decision management through behavioural factors such as user trust, AI recommendations, and satisfaction. The findings reveal that transparent, ethical, and customer-oriented AI systems are essential for building consumer confidence and enhancing the quality of decision-making. Consistent with behavioural decision theories, the results show that customers are more inclined to depend on AI when it lowers uncertainty and strengthens perceived control. Trust emerges as a crucial mediator between AI adoption and purchase decisions, highlighting the need for ethical and transparent AI practices. The study ultimately concludes that sustainable AI-based decision management depends on effectively integrating technological efficiency with behavioural and ethical considerations.

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