diff --git a/src/core/include/openvino/op/log.hpp b/src/core/include/openvino/op/log.hpp
index ae0ca7080a7..33a0fe6aa44 100644
--- a/src/core/include/openvino/op/log.hpp
+++ b/src/core/include/openvino/op/log.hpp
@@ -21,11 +21,8 @@ public:
     /// \param arg Node that produces the input tensor.
     Log(const Output<Node>& arg);
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
     bool has_evaluate() const override;
 };
 }  // namespace v0
diff --git a/src/core/reference/include/openvino/reference/log.hpp b/src/core/reference/include/openvino/reference/log.hpp
index fec6c959e29..d8b7fdeab3b 100644
--- a/src/core/reference/include/openvino/reference/log.hpp
+++ b/src/core/reference/include/openvino/reference/log.hpp
@@ -4,6 +4,7 @@
 
 #pragma once
 
+#include <algorithm>
 #include <cmath>
 #include <cstddef>
 
@@ -11,9 +12,9 @@ namespace ov {
 namespace reference {
 template <typename T>
 void log(const T* arg, T* out, size_t count) {
-    for (size_t i = 0; i < count; i++) {
-        out[i] = static_cast<T>(std::log(arg[i]));
-    }
+    std::transform(arg, arg + count, out, [](const T v) {
+        return static_cast<T>(std::log(v));
+    });
 }
 }  // namespace reference
 }  // namespace ov
diff --git a/src/core/src/op/log.cpp b/src/core/src/op/log.cpp
index a854ceb06f5..dacde7087e9 100644
--- a/src/core/src/op/log.cpp
+++ b/src/core/src/op/log.cpp
@@ -2,78 +2,66 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include "ngraph/op/log.hpp"
+#include "openvino/op/log.hpp"
 
+#include "element_visitor.hpp"
 #include "itt.hpp"
-#include "ngraph/op/divide.hpp"
-#include "ngraph/runtime/host_tensor.hpp"
 #include "openvino/reference/log.hpp"
 
-using namespace std;
-using namespace ngraph;
+namespace ov {
+namespace op {
+namespace log {
+struct Evaluate : element::NoAction<bool> {
+    using element::NoAction<bool>::visit;
 
-op::Log::Log(const Output<Node>& arg) : UnaryElementwiseArithmetic(arg) {
+    template <element::Type_t ET, class T = fundamental_type_for<ET>>
+    static result_type visit(const Tensor& in, Tensor& out, const size_t count) {
+        reference::log(in.data<const T>(), out.data<T>(), count);
+        return true;
+    }
+};
+}  // namespace log
+
+namespace v0 {
+Log::Log(const Output<Node>& arg) : UnaryElementwiseArithmetic(arg) {
     constructor_validate_and_infer_types();
 }
 
-bool ngraph::op::v0::Log::visit_attributes(AttributeVisitor& visitor) {
-    OV_OP_SCOPE(v0_Log_visit_attributes);
-    return true;
-}
-
-shared_ptr<Node> op::Log::clone_with_new_inputs(const OutputVector& new_args) const {
+std::shared_ptr<Node> Log::clone_with_new_inputs(const OutputVector& new_args) const {
     OV_OP_SCOPE(v0_Log_clone_with_new_inputs);
     check_new_args_count(this, new_args);
-    return make_shared<Log>(new_args.at(0));
+    return std::make_shared<Log>(new_args.at(0));
 }
 
-OPENVINO_SUPPRESS_DEPRECATED_START
-namespace logop {
-namespace {
-template <element::Type_t ET>
-inline bool evaluate(const HostTensorPtr& arg0, const HostTensorPtr& out, const size_t count) {
-    using T = typename element_type_traits<ET>::value_type;
-    ov::reference::log<T>(arg0->get_data_ptr<ET>(), out->get_data_ptr<ET>(), count);
-    return true;
-}
-
-bool evaluate_log(const HostTensorPtr& arg0, const HostTensorPtr& out, const size_t count) {
-    bool rc = true;
-    out->set_unary(arg0);
-
-    switch (arg0->get_element_type()) {
-        OPENVINO_TYPE_CASE(evaluate_log, i32, arg0, out, count);
-        OPENVINO_TYPE_CASE(evaluate_log, i64, arg0, out, count);
-        OPENVINO_TYPE_CASE(evaluate_log, u32, arg0, out, count);
-        OPENVINO_TYPE_CASE(evaluate_log, u64, arg0, out, count);
-        OPENVINO_TYPE_CASE(evaluate_log, f16, arg0, out, count);
-        OPENVINO_TYPE_CASE(evaluate_log, f32, arg0, out, count);
-    default:
-        rc = false;
-        break;
-    }
-    return rc;
-}
-}  // namespace
-}  // namespace logop
-
-bool op::Log::evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const {
+bool Log::evaluate(TensorVector& outputs, const TensorVector& inputs) const {
     OV_OP_SCOPE(v0_Log_evaluate);
-    return logop::evaluate_log(inputs[0], outputs[0], shape_size(inputs[0]->get_shape()));
+    OPENVINO_ASSERT(outputs.size() == 1);
+    OPENVINO_ASSERT(inputs.size() == 1);
+
+    const auto& input_shape = inputs[0].get_shape();
+    const auto count = shape_size(input_shape);
+    outputs[0].set_shape(input_shape);
+    using namespace ov::element;
+    return IfTypeOf<f16, f32, i32, i64, u32, u64>::apply<log::Evaluate>(inputs[0].get_element_type(),
+                                                                        inputs[0],
+                                                                        outputs[0],
+                                                                        count);
 }
 
-bool op::Log::has_evaluate() const {
+bool Log::has_evaluate() const {
     OV_OP_SCOPE(v0_Log_has_evaluate);
     switch (get_input_element_type(0)) {
-    case ngraph::element::i32:
-    case ngraph::element::i64:
-    case ngraph::element::u32:
-    case ngraph::element::u64:
-    case ngraph::element::f16:
-    case ngraph::element::f32:
+    case element::f16:
+    case element::f32:
+    case element::i32:
+    case element::i64:
+    case element::u32:
+    case element::u64:
         return true;
     default:
-        break;
+        return false;
     }
-    return false;
 }
+}  // namespace v0
+}  // namespace op
+}  // namespace ov