diff --git a/docs/snippets/cpu/Bfloat16Inference.py b/docs/snippets/cpu/Bfloat16Inference.py
index 7d6516ea7d4..69479e8c3fb 100644
--- a/docs/snippets/cpu/Bfloat16Inference.py
+++ b/docs/snippets/cpu/Bfloat16Inference.py
@@ -12,16 +12,16 @@ model = get_model()
 
 #! [part0]
 core = ov.Core()
-cpu_optimization_capabilities = core.get_property("CPU", device.capabilities())
+cpu_optimization_capabilities = core.get_property("CPU", device.capabilities)
 #! [part0]
 
 #! [part1]
 core = ov.Core()
 compiled_model = core.compile_model(model, "CPU")
-inference_precision = core.get_property("CPU", hints.inference_precision())
+inference_precision = core.get_property("CPU", hints.inference_precision)
 #! [part1]
 
 #! [part2]
 core = ov.Core()
-core.set_property("CPU", {hints.inference_precision(): ov.Type.f32})
+core.set_property("CPU", {hints.inference_precision: ov.Type.f32})
 #! [part2]
diff --git a/docs/snippets/cpu/ov_execution_mode.py b/docs/snippets/cpu/ov_execution_mode.py
index 5476426e77a..511e2a28dd6 100644
--- a/docs/snippets/cpu/ov_execution_mode.py
+++ b/docs/snippets/cpu/ov_execution_mode.py
@@ -9,11 +9,11 @@ core = ov.Core()
 # in case of Accuracy
 core.set_property(
     "CPU",
-    {hints.execution_mode(): hints.ExecutionMode.ACCURACY},
+    {hints.execution_mode: hints.ExecutionMode.ACCURACY},
 )
 # in case of Performance
 core.set_property(
     "CPU",
-    {hints.execution_mode(): hints.ExecutionMode.PERFORMANCE},
+    {hints.execution_mode: hints.ExecutionMode.PERFORMANCE},
 )
 #! [ov:execution_mode:part0]
diff --git a/docs/snippets/gpu/compile_model.py b/docs/snippets/gpu/compile_model.py
index 152de661c1f..733f162dbc1 100644
--- a/docs/snippets/gpu/compile_model.py
+++ b/docs/snippets/gpu/compile_model.py
@@ -46,7 +46,7 @@ def main():
         model,
         "GPU",
         {
-            hints.performance_mode(): hints.PerformanceMode.THROUGHPUT,
+            hints.performance_mode: hints.PerformanceMode.THROUGHPUT,
         },
     )
     #! [compile_model_auto_batch]
diff --git a/docs/snippets/ov_auto.py b/docs/snippets/ov_auto.py
index 35454e0527b..a665b509713 100644
--- a/docs/snippets/ov_auto.py
+++ b/docs/snippets/ov_auto.py
@@ -31,13 +31,13 @@ def part0():
     compiled_model = core.compile_model(
         model=model,
         device_name="AUTO",
-        config={device.priorities(): "GPU,CPU"},
+        config={device.priorities: "GPU,CPU"},
     )
 
     # Optional
     # the AUTO plugin is pre-configured (globally) with the explicit option:
     core.set_property(
-        device_name="AUTO", properties={device.priorities(): "GPU,CPU"}
+        device_name="AUTO", properties={device.priorities: "GPU,CPU"}
     )
     #! [part0]
 
@@ -60,13 +60,13 @@ def part1():
     exec_net = ie.load_network(
         network=net,
         device_name="AUTO",
-        config={device.priorities(): "GPU,CPU"},
+        config={"MULTI_DEVICE_PRIORITIES": "GPU,CPU"},
     )
 
     # Optional
     # the AUTO plugin is pre-configured (globally) with the explicit option:
     ie.set_config(
-        config={device.priorities(): "GPU,CPU"}, device_name="AUTO"
+        config={"MULTI_DEVICE_PRIORITIES": "GPU,CPU"}, device_name="AUTO"
     )
     #! [part1]
 
@@ -81,7 +81,7 @@ def part3():
         model=model,
         device_name="AUTO",
         config={
-            hints.performance_mode(): hints.PerformanceMode.THROUGHPUT
+            hints.performance_mode: hints.PerformanceMode.THROUGHPUT
         },
     )
     # To use the “LATENCY” mode:
@@ -89,7 +89,7 @@ def part3():
         model=model,
         device_name="AUTO",
         config={
-            hints.performance_mode(): hints.PerformanceMode.LATENCY
+            hints.performance_mode: hints.PerformanceMode.LATENCY
         },
     )
     # To use the “CUMULATIVE_THROUGHPUT” mode:
@@ -97,7 +97,7 @@ def part3():
         model=model,
         device_name="AUTO",
         config={
-            hints.performance_mode(): hints.PerformanceMode.CUMULATIVE_THROUGHPUT
+            hints.performance_mode: hints.PerformanceMode.CUMULATIVE_THROUGHPUT
         },
     )
     #! [part3]
@@ -111,19 +111,19 @@ def part4():
     compiled_model0 = core.compile_model(
         model=model,
         device_name="AUTO",
-        config={hints.model_priority(): hints.Priority.HIGH},
+        config={hints.model_priority: hints.Priority.HIGH},
     )
     compiled_model1 = core.compile_model(
         model=model,
         device_name="AUTO",
         config={
-            hints.model_priority(): hints.Priority.MEDIUM
+            hints.model_priority: hints.Priority.MEDIUM
         },
     )
     compiled_model2 = core.compile_model(
         model=model,
         device_name="AUTO",
-        config={hints.model_priority(): hints.Priority.LOW},
+        config={hints.model_priority: hints.Priority.LOW},
     )
     # Assume that all the devices (CPU and GPUs) can support all the networks.
     # Result: compiled_model0 will use GPU.1, compiled_model1 will use GPU.0, compiled_model2 will use CPU.
@@ -132,19 +132,19 @@ def part4():
     compiled_model3 = core.compile_model(
         model=model,
         device_name="AUTO",
-        config={hints.model_priority(): hints.Priority.HIGH},
+        config={hints.model_priority: hints.Priority.HIGH},
     )
     compiled_model4 = core.compile_model(
         model=model,
         device_name="AUTO",
         config={
-            hints.model_priority(): hints.Priority.MEDIUM
+            hints.model_priority: hints.Priority.MEDIUM
         },
     )
     compiled_model5 = core.compile_model(
         model=model,
         device_name="AUTO",
-        config={hints.model_priority(): hints.Priority.LOW},
+        config={hints.model_priority: hints.Priority.LOW},
     )
     # Assume that all the devices (CPU ang GPUs) can support all the networks.
     # Result: compiled_model3 will use GPU.1, compiled_model4 will use GPU.1, compiled_model5 will use GPU.0.
@@ -169,12 +169,12 @@ def part6():
     compiled_model = core.compile_model(
         model=model,
         device_name="AUTO",
-        config={log.level(): log.Level.DEBUG},
+        config={log.level: log.Level.DEBUG},
     )
     # set log level with set_property and compile model
     core.set_property(
         device_name="AUTO",
-        properties={log.level(): log.Level.DEBUG},
+        properties={log.level: log.Level.DEBUG},
     )
     compiled_model = core.compile_model(model=model, device_name="AUTO")
     #! [part6]
@@ -187,7 +187,7 @@ def part7():
     # compile a model on AUTO and set log level to debug
     compiled_model = core.compile_model(model=model, device_name="AUTO")
     # query the runtime target devices on which the inferences are being executed
-    execution_devices = compiled_model.get_property(properties.execution_devices())
+    execution_devices = compiled_model.get_property(properties.execution_devices)
     #! [part7]
 
 
diff --git a/docs/snippets/ov_auto_batching.py b/docs/snippets/ov_auto_batching.py
index 7508c90337c..54a0c8accdd 100644
--- a/docs/snippets/ov_auto_batching.py
+++ b/docs/snippets/ov_auto_batching.py
@@ -18,37 +18,37 @@ def main():
     import openvino.properties as props
     import openvino.properties.hint as hints
 
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT}
     compiled_model = core.compile_model(model, "GPU", config)
     # [compile_model]
 
     # [compile_model_no_auto_batching]
     # disabling the automatic batching
     # leaving intact other configurations options that the device selects for the 'throughput' hint 
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT,
-            hints.allow_auto_batching(): False}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT,
+              hints.allow_auto_batching: False}
     compiled_model = core.compile_model(model, "GPU", config)
     # [compile_model_no_auto_batching]
 
     # [query_optimal_num_requests]
     # when the batch size is automatically selected by the implementation
     # it is important to query/create and run the sufficient requests
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT}
     compiled_model = core.compile_model(model, "GPU", config)
-    num_requests = compiled_model.get_property(props.optimal_number_of_infer_requests())
+    num_requests = compiled_model.get_property(props.optimal_number_of_infer_requests)
     # [query_optimal_num_requests]
 
     # [hint_num_requests]
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT,
-            hints.num_requests(): "4"}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT,
+              hints.num_requests: "4"}
     # limiting the available parallel slack for the 'throughput'
     # so that certain parameters (like selected batch size) are automatically accommodated accordingly 
     compiled_model = core.compile_model(model, "GPU", config)
     # [hint_num_requests]
 
     # [hint_plus_low_level]
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT,
-            props.inference_num_threads(): "4"}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT,
+              props.inference_num_threads: "4"}
     # limiting the available parallel slack for the 'throughput'
     # so that certain parameters (like selected batch size) are automatically accommodated accordingly
     compiled_model = core.compile_model(model, "CPU", config)
diff --git a/docs/snippets/ov_caching.py b/docs/snippets/ov_caching.py
index a30ec968e7d..b6b4c6e3f8e 100644
--- a/docs/snippets/ov_caching.py
+++ b/docs/snippets/ov_caching.py
@@ -12,7 +12,7 @@ model_path = get_path_to_model()
 path_to_cache_dir = get_temp_dir()
 # ! [ov:caching:part0]
 core = ov.Core()
-core.set_property({props.cache_dir(): path_to_cache_dir})
+core.set_property({props.cache_dir: path_to_cache_dir})
 model = core.read_model(model=model_path)
 compiled_model = core.compile_model(model=model, device_name=device_name)
 # ! [ov:caching:part0]
@@ -28,7 +28,7 @@ assert compiled_model
 
 # ! [ov:caching:part2]
 core = ov.Core()
-core.set_property({props.cache_dir(): path_to_cache_dir})
+core.set_property({props.cache_dir: path_to_cache_dir})
 compiled_model = core.compile_model(model=model_path, device_name=device_name)
 # ! [ov:caching:part2]
 
@@ -38,5 +38,5 @@ assert compiled_model
 import openvino.properties.device as device
 
 # Find 'EXPORT_IMPORT' capability in supported capabilities
-caching_supported = 'EXPORT_IMPORT' in core.get_property(device_name, device.capabilities())
+caching_supported = 'EXPORT_IMPORT' in core.get_property(device_name, device.capabilities)
 # ! [ov:caching:part3]
diff --git a/docs/snippets/ov_hetero.py b/docs/snippets/ov_hetero.py
index aa0eac7784f..7f338081f69 100644
--- a/docs/snippets/ov_hetero.py
+++ b/docs/snippets/ov_hetero.py
@@ -41,15 +41,15 @@ def main():
     compiled_model = core.compile_model(model, device_name="HETERO:GPU,CPU")
     # device priorities via configuration property
     compiled_model = core.compile_model(
-        model, device_name="HETERO", config={device.priorities(): "GPU,CPU"}
+        model, device_name="HETERO", config={device.priorities: "GPU,CPU"}
     )
     #! [compile_model]
 
     #! [configure_fallback_devices]
     import openvino.hint as hints
 
-    core.set_property("HETERO", {device.priorities(): "GPU,CPU"})
-    core.set_property("GPU", {properties.enable_profiling(): True})
-    core.set_property("CPU", {hints.inference_precision(): ov.Type.f32})
+    core.set_property("HETERO", {device.priorities: "GPU,CPU"})
+    core.set_property("GPU", {properties.enable_profiling: True})
+    core.set_property("CPU", {hints.inference_precision: ov.Type.f32})
     compiled_model = core.compile_model(model=model, device_name="HETERO")
     #! [configure_fallback_devices]
diff --git a/docs/snippets/ov_multi.py b/docs/snippets/ov_multi.py
index bae82aa3d47..1f852faea94 100644
--- a/docs/snippets/ov_multi.py
+++ b/docs/snippets/ov_multi.py
@@ -17,7 +17,7 @@ def MULTI_0():
     # Pre-configure MULTI globally with explicitly defined devices,
     # and compile the model on MULTI using the newly specified default device list.
     core.set_property(
-        device_name="MULTI", properties={device.priorities(): "GPU,CPU"}
+        device_name="MULTI", properties={device.priorities: "GPU,CPU"}
     )
     compiled_model = core.compile_model(model=model, device_name="MULTI")
 
@@ -28,7 +28,7 @@ def MULTI_0():
     compiled_model = core.compile_model(
         model=model,
         device_name="MULTI",
-        config={device.priorities(): "GPU,CPU"},
+        config={device.priorities: "GPU,CPU"},
     )
     #! [MULTI_0]
 
@@ -38,22 +38,22 @@ def MULTI_1():
     core = ov.Core()
 
     core.set_property(
-        device_name="MULTI", properties={device.priorities(): "CPU,GPU"}
+        device_name="MULTI", properties={device.priorities: "CPU,GPU"}
     )
     # Once the priority list is set, you can alter it on the fly:
     # reverse the order of priorities
     core.set_property(
-        device_name="MULTI", properties={device.priorities(): "GPU,CPU"}
+        device_name="MULTI", properties={device.priorities: "GPU,CPU"}
     )
 
     # exclude some devices (in this case, CPU)
     core.set_property(
-        device_name="MULTI", properties={device.priorities(): "GPU"}
+        device_name="MULTI", properties={device.priorities: "GPU"}
     )
 
     # bring back the excluded devices
     core.set_property(
-        device_name="MULTI", properties={device.priorities(): "GPU,CPU"}
+        device_name="MULTI", properties={device.priorities: "GPU,CPU"}
     )
 
     # You cannot add new devices on the fly!
@@ -109,7 +109,7 @@ def MULTI_4():
 
     # Optionally, query the optimal number of requests:
     nireq = compiled_model.get_property(
-        properties.optimal_number_of_infer_requests()
+        properties.optimal_number_of_infer_requests
     )
     #! [MULTI_4]
 
diff --git a/docs/snippets/ov_properties_api.py b/docs/snippets/ov_properties_api.py
index 369e88ad572..2c07ca67741 100644
--- a/docs/snippets/ov_properties_api.py
+++ b/docs/snippets/ov_properties_api.py
@@ -17,48 +17,48 @@ def main():
     # [get_available_devices]
 
     # [hetero_priorities]
-    device_priorites = core.get_property("HETERO", device.priorities())
+    device_priorites = core.get_property("HETERO", device.priorities)
     # [hetero_priorities]
 
     # [cpu_device_name]
-    cpu_device_name = core.get_property("CPU", device.full_name())
+    cpu_device_name = core.get_property("CPU", device.full_name)
     # [cpu_device_name]
 
     model = get_model()
     # [compile_model_with_property]
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT,
-            hints.inference_precision(): ov.Type.f32}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT,
+            hints.inference_precision: ov.Type.f32}
     compiled_model = core.compile_model(model, "CPU", config)
     # [compile_model_with_property]
 
     # [optimal_number_of_infer_requests]
     compiled_model = core.compile_model(model, "CPU")
-    nireq = compiled_model.get_property(props.optimal_number_of_infer_requests())
+    nireq = compiled_model.get_property(props.optimal_number_of_infer_requests)
     # [optimal_number_of_infer_requests]
 
 
     # [core_set_property_then_compile]
     # latency hint is a default for CPU
-    core.set_property("CPU", {hints.performance_mode(): hints.PerformanceMode.LATENCY})
+    core.set_property("CPU", {hints.performance_mode: hints.PerformanceMode.LATENCY})
     # compiled with latency configuration hint
     compiled_model_latency = core.compile_model(model, "CPU")
     # compiled with overriden performance hint value
-    config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT}
+    config = {hints.performance_mode: hints.PerformanceMode.THROUGHPUT}
     compiled_model_thrp = core.compile_model(model, "CPU", config)
     # [core_set_property_then_compile]
 
 
     # [inference_num_threads]
     compiled_model = core.compile_model(model, "CPU")
-    nthreads = compiled_model.get_property(props.inference_num_threads())
+    nthreads = compiled_model.get_property(props.inference_num_threads)
     # [inference_num_threads]
 
     if "GPU" not in available_devices:
         return 0
 
     # [multi_device]
-    config = {device.priorities(): "CPU,GPU"}
+    config = {device.priorities: "CPU,GPU"}
     compiled_model = core.compile_model(model, "MULTI", config)
     # change the order of priorities
-    compiled_model.set_property({device.priorities(): "GPU,CPU"})
+    compiled_model.set_property({device.priorities: "GPU,CPU"})
     # [multi_device]
diff --git a/docs/snippets/ov_properties_migration.py b/docs/snippets/ov_properties_migration.py
index 88addb6a72d..8d5ac86b208 100644
--- a/docs/snippets/ov_properties_migration.py
+++ b/docs/snippets/ov_properties_migration.py
@@ -14,7 +14,7 @@ def main():
     core = ov.Core()
 
     # ! [core_set_property]
-    core.set_property(device_name="CPU", properties={props.enable_profiling(): True})
+    core.set_property(device_name="CPU", properties={props.enable_profiling: True})
     # ! [core_set_property]
 
     model = get_model()
@@ -25,31 +25,31 @@ def main():
     # ! [core_compile_model]
     compiled_model = core.compile_model(model=model, device_name="MULTI", config=
         {
-            device.priorities(): "GPU,CPU",
-            hints.performance_mode(): hints.PerformanceMode.THROUGHPUT,
-            hints.inference_precision(): ov.Type.f32
+            device.priorities: "GPU,CPU",
+            hints.performance_mode: hints.PerformanceMode.THROUGHPUT,
+            hints.inference_precision: ov.Type.f32
         })
     # ! [core_compile_model]
 
     # ! [compiled_model_set_property]
     # turn CPU off for multi-device execution
-    compiled_model.set_property(properties={device.priorities(): "GPU"})
+    compiled_model.set_property(properties={device.priorities: "GPU"})
     # ! [compiled_model_set_property]
 
     # ! [core_get_rw_property]
-    num_streams = core.get_property("CPU", streams.num())
+    num_streams = core.get_property("CPU", streams.num)
     # ! [core_get_rw_property]
 
     # ! [core_get_ro_property]
-    full_device_name = core.get_property("CPU", device.full_name())
+    full_device_name = core.get_property("CPU", device.full_name)
     # ! [core_get_ro_property]
 
     # ! [compiled_model_get_rw_property]
-    perf_mode = compiled_model.get_property(hints.performance_mode())
+    perf_mode = compiled_model.get_property(hints.performance_mode)
     # ! [compiled_model_get_rw_property]
 
     # ! [compiled_model_get_ro_property]
-    nireq = compiled_model.get_property(props.optimal_number_of_infer_requests())
+    nireq = compiled_model.get_property(props.optimal_number_of_infer_requests)
     # ! [compiled_model_get_ro_property]
 
     import ngraph as ng