Introduction

The agricultural tourism being one of the most important segments of tourism is gaining attention in modern times. This tourism can provide economic opportunities and contribute to the environmental conservation and sustainable development of the rural communities. Owing to the importance of this matter, researchers and experts in tourism have started investigating ways to improve the relevance and sustainability of this industry. In this respect, the application of new technologies, namely artificial intelligence, can come into play and present a viable solution.
 

Methodology

The current research is basic concerning purpose and descriptive regarding nature and methods in the qualitative section and survey-based in the quantitative section. For the qualitative part, semi-structured interviews were conducted with selected samples. Then, in the quantitative analysis, the paired scale technique was adopted using AHP to rank the factors. The population under study consisted of experts in the domain of information technology, entrepreneurship, and tourism. A purposive sampling method, and the sample selection was done on a snowball basis until theoretical saturation was reached, with 12 people being selected for the samples. For the analysis of data in the qualitative phase, the method of Strauss and Corbin (open, axial, and selective coding) was employed. The member-checking and the intra-rater agreement methods were used to ascertain the validity and reliability of the questions.
 

Results

This research aimed at modeling the agricultural tourism development into sustainable ones hinged on artificial intelligence (case study: Paveh city); hence, mixed methods were followed in this study. Altogether, extraction was finally made of 168 open codes, 25 central codes, and 6 selective codes and categorized into 6 main categories after common codes were identified and analyzed (figure no. 1). Fewer than 24 main categories can, therefore, be focused on at the same time owing to the magnanimous nature of categories. Thus, by adopting the ranking of such categories, necessary actions for sustainability set for agricultural tourist development become much easier to make. In the ranking part of the study, an AHP technique was used for the pair scale (binary), and the ranking follows in order of priority: financial restrictions by (0.881) on the first place; environmental pressures with (0.830) in second; and third by situation expert manpower (0.683); fourth by assessment of required services (0.369); benefiting from information technology capacities with (0.350) in fifth; establishing supportive and facilitating laws with (0.349) in a sixth rank; followed by dynamic technological environment with (0.316) into the seventh; provision of sufficient facilities by the government and institutions is on the eighth rank with (0.314); creativity and innovation in services is ninth with (0.281); tenth comes reducing the risk of lack of economic justification of agricultural activities with (0.276); following by changing the nature of tourists with (0.250) ranked eleventh; and appropriate marketing and information system is ranked 12th with (0.230); thirteenth is holding training courses and persuasion with (0.220); the fourteenth place is given to effective participation of universities and educational centers with (0.185); legal and policy infrastructure rank of 15th at (0.150); access to technological infrastructure by the host community is given the sixteenth rank at (0.146); Environmental determinism is followed for the acceptance of intelligence artificial with (0.142) in the 17th rank; reduction of migration to the city is therefore found with (0.996) in the 18th ranking; for diversifying the local economy and income sources, it is found at the 19thrank with (0.994); creating a platform for the support of private sector was thus ranked with (0.889) in the 20th position; introducing agricultural tourism destinations ranks 21st with (0.753); cultural and attitudinal constraints were ranked on the 22nd with (0.560); content production with educational and promotion themes got (0.444) in the 23rd rank; infrastructures Governing services and facilities were ranked 24th with (0.405).
 

Discussion

Nowadays, artificial intelligence is one of the significant instruments in tourism. Within agricultural tourism, artificial intelligence can facilitate the entire process of sustainable development for this sub-sector. Its application in the use of AI algorithms in predicting tourism demand and optimizing tourist destinations' capacity can be an aid to more precise planning and more effective management of tourists. In addition, the smart systems will enable personalized services for tourists that will boost their satisfaction and loyalty. Analyzation of big data and machine learning techniques allow a more comprehensive and accurate assessment of sustainability in agricultural tourism, while smart sensors and continuous monitoring of sustainability indicators assist in identifying and managing environmental risks. However, implementation of these artificial intelligence-sourced solutions will further depend not only on the technology acceptance by stakeholders but also on the ethical issues of privacy.
 

Conclusion

Artificial intelligence can be applied to agricultural tourism planning, management, data analysis and optimization of processes, but beyond that, it can also provide an individualized travel experience for tourists. Further, artificial intelligence can be effectively put into use such as environmental monitoring regarding the sustainability of data analysis through which steps can be taken to promote sustainable development in agricultural tourism. By targeting such audience through proper and smart use of artificial intelligence, good marketing strategies can be enhanced for the development of agritourism. Data and behavior analysis of the tourist audience could yield more effective advertising and communications and reach target groups. There is a pretty good capability for artificial intelligence to promote sustainability in agricultural tourism. Using that technology can improve the management of that flow, satisfaction, and sustainability definition. However, it depends on the operational and ethical issues that follow. Generally, they have termed artificial intelligence as an appropriate application for the sustainable development of agricultural tourism.
 
Acknowledgments
I sincerely appreciate everyone who contributed to the preparation of this article.