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Creating an artificial intelligence (AI) application can range from simple algorithms, like decision trees or linear regression, to more complex systems like neural networks. Below is a straightforward example of a decision tree implemented in C++, which could be considered a rudimentary AI for classification purposes.

This decision tree will be very simple and will only work with categorical data. It will be hardcoded to classify whether a person is likely to go for a walk based on the weather and the temperature.

#include <iostream>
#include <string>
// Decision node struct
struct DecisionNode {
   std::string question;
   DecisionNode* yes;
   DecisionNode* no;
   DecisionNode(std::string q) : question(q), yes(nullptr), no(nullptr) {}
};
// Decision tree class
class DecisionTree {
private:
   DecisionNode* root;
public:
   DecisionTree() {
       // Construct the decision tree
       root = new DecisionNode("Is the weather nice?");
       root->yes = new DecisionNode("Is it warm?");
       root->no = new DecisionNode("false"); // false means will not go for a walk
       root->yes->yes = new DecisionNode("true"); // true means will go for a walk
       root->yes->no = new DecisionNode("false");
   }
   ~DecisionTree() {
       // Recursive delete
       deleteTree(root);
   }
   void deleteTree(DecisionNode* node) {
       if (node) {
           deleteTree(node->yes);
           deleteTree(node->no);
           delete node;
       }
   }
   // Classify method
   std::string classify(const std::string& weather, const std::string& temperature) {
       DecisionNode* node = root;
       while (true) {
           if (node->question == "true") return "Will go for a walk.";
           if (node->question == "false") return "Will not go for a walk.";
           if (node->question == "Is the weather nice?") {
               node = (weather == "nice") ? node->yes : node->no;
           } else if (node->question == "Is it warm?") {
               node = (temperature == "warm") ? node->yes : node->no;
           }
       }
   }
};
int main() {
   DecisionTree tree;
   std::string weather, temperature;
   // Get user input
   std::cout << "Is the weather nice? (nice/bad): ";
   std::cin >> weather;
   std::cout << "Is it warm? (warm/cold): ";
   std::cin >> temperature;
   // Classify and print the result
   std::cout << tree.classify(weather, temperature) << std::endl;
   return 0;
}

To compile this code, you need to save it to a file (say, decision_tree.cpp) and then use a C++ compiler:

g++ -o decision_tree decision_tree.cpp
./decision_tree

When you run the program, it will ask for the weather and temperature, and based on your answers, it will predict whether the person will go for a walk. This is a deterministic model and doesn't involve learning from data, but it is a starting point for building more complex AI systems that include learning capabilities.