diff --git a/src/plugins/intel_gpu/src/graph/graph_optimizer/prepare_quantization.cpp b/src/plugins/intel_gpu/src/graph/graph_optimizer/prepare_quantization.cpp
index 13e21ab4c21..893d3539507 100644
--- a/src/plugins/intel_gpu/src/graph/graph_optimizer/prepare_quantization.cpp
+++ b/src/plugins/intel_gpu/src/graph/graph_optimizer/prepare_quantization.cpp
@@ -530,6 +530,10 @@ void prepare_quantization::prepare_asymmetric_quantization(program &p, convoluti
         in1.get_output_layout().data_type != data_types::i8)
         return;
 
+    const size_t feature_idx = 1;
+    if (asymmetric_data && in0.get_output_layout().get_partial_shape()[feature_idx].is_dynamic())
+        return;
+
     auto old_conv_prim = convolution_node.get_primitive();
 
     primitive_id input = old_conv_prim->input[0].pid;
@@ -546,7 +550,7 @@ void prepare_quantization::prepare_asymmetric_quantization(program &p, convoluti
         wl = wl.convert_to_weights_layout(convolution_node.typed_desc()->grouped_weights_shape);
     }
     int ofm = wl.group() * wl.ofm();
-    int ifm = in0.get_output_layout().feature();
+    int ifm = in0.get_output_layout().get_partial_shape()[feature_idx].get_length();
     int ofm_aligned = align_to(ofm, 32);
     int ifm_aligned = align_to(ifm, 32);
 
diff --git a/src/plugins/intel_gpu/tests/unit/passes/prepare_quantization.cpp b/src/plugins/intel_gpu/tests/unit/passes/prepare_quantization.cpp
index bbd918fde11..408ea0c611b 100644
--- a/src/plugins/intel_gpu/tests/unit/passes/prepare_quantization.cpp
+++ b/src/plugins/intel_gpu/tests/unit/passes/prepare_quantization.cpp
@@ -44,4 +44,30 @@ TEST(prepare_quantization, program_replace_check_num_of_nodes) {
     program_wrapper::apply_opt_pass<prepare_quantization>(*prog);
 
     ASSERT_TRUE(prog->get_node("quantize").get_dependencies().size() == 9);
-}
\ No newline at end of file
+}
+
+TEST(prepare_quantization, dynamic_conv_asymmetric_data_weight_no_failure) {
+    auto& engine = get_test_engine();
+
+    ov::Shape in_shape = { 1, 15, 4, 5 };
+    auto in_layout = layout{ ov::PartialShape::dynamic(in_shape.size()), data_types::u8, format::bfyx };
+    auto input_ptr = engine.allocate_memory({ data_types::u8, format::bfyx, { 1, 15, 4, 5 } });
+    auto w_mem_ptr = engine.allocate_memory({ ov::PartialShape{ 30, 15, 3, 3 }, data_types::i8, format::bfyx });
+    auto zp_mem_ptr = engine.allocate_memory({ in_shape, data_types::u8, format::bfyx });
+
+    topology topology;
+
+    topology.add(input_layout("input", in_layout));
+    topology.add(data("weights", w_mem_ptr));
+    topology.add(data("a_zp", zp_mem_ptr));
+    topology.add(eltwise("a_sub", { input_info("input"), input_info("a_zp") }, eltwise_mode::sub, data_types::f32));
+    topology.add(convolution("conv_prim", input_info("a_sub"), "weights", "", 1, {1, 1}, {1, 1}, {0, 0}, {0, 0}, false));
+
+    ExecutionConfig config = get_test_default_config(engine);
+    config.set_property(ov::intel_gpu::allow_new_shape_infer(true));
+    config.set_property(ov::intel_gpu::optimize_data(true));
+    network network(engine, topology, config);
+    network.set_input_data("input", input_ptr);
+
+    EXPECT_NO_THROW(network.execute());
+}