diff --git a/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp b/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp
index e8d537f..4b43052 100644
--- a/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp
+++ b/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp
@@ -59,20 +59,24 @@
     auto unsignedAxis = armnnUtils::GetUnsignedAxis(numDims, m_Data.m_Parameters.m_Axis);
     int aclAxis = boost::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis));
 
+    auto layer = std::make_unique<arm_compute::NEArgMinMaxLayer>();
+
     if (m_Data.m_Parameters.m_Function == ArgMinMaxFunction::Max)
     {
-        m_ArgMinMaxLayer.configure(&input, aclAxis, &output, arm_compute::ReductionOperation::ARG_IDX_MAX);
+        layer->configure(&input, aclAxis, &output, arm_compute::ReductionOperation::ARG_IDX_MAX);
     }
     else
     {
-        m_ArgMinMaxLayer.configure(&input, aclAxis, &output, arm_compute::ReductionOperation::ARG_IDX_MIN);
+        layer->configure(&input, aclAxis, &output, arm_compute::ReductionOperation::ARG_IDX_MIN);
     }
+
+    m_ArgMinMaxLayer.reset(layer.release());
 }
 
 void NeonArgMinMaxWorkload::Execute() const
 {
     ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonArgMinMaxWorkload_Execute");
-    m_ArgMinMaxLayer.run();
+    m_ArgMinMaxLayer->run();
 }
 
 } //namespace armnn
diff --git a/src/backends/neon/workloads/NeonArgMinMaxWorkload.hpp b/src/backends/neon/workloads/NeonArgMinMaxWorkload.hpp
index 6301b13..6e1cc46 100644
--- a/src/backends/neon/workloads/NeonArgMinMaxWorkload.hpp
+++ b/src/backends/neon/workloads/NeonArgMinMaxWorkload.hpp
@@ -8,7 +8,8 @@
 #include <backendsCommon/Workload.hpp>
 
 #include <arm_compute/core/Error.h>
-#include <arm_compute/runtime/NEON/functions/NEArgMinMaxLayer.h>
+#include <arm_compute/runtime/IFunction.h>
+
 namespace armnn
 {
 
@@ -23,7 +24,7 @@
     virtual void Execute() const override;
 
 private:
-    mutable arm_compute::NEArgMinMaxLayer m_ArgMinMaxLayer;
+    std::unique_ptr<arm_compute::IFunction> m_ArgMinMaxLayer;
 };
 
 } //namespace armnn
diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp
index 18085ed..2093613 100644
--- a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp
+++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp
@@ -120,19 +120,19 @@
 
     // Check for optimisation opportunities
     arm_compute::Status optimizationStatus =
-        arm_compute::NEDepthwiseConvolutionLayerOptimized::validate(inputInfo,
-                                                                    kernelInfo,
-                                                                    biasInfo,
-                                                                    outputInfo,
-                                                                    padStrideInfo,
-                                                                    depthMultiplier,
-                                                                    arm_compute::ActivationLayerInfo(),
-                                                                    aclDilationInfo);
+        arm_compute::NEDepthwiseConvolutionLayer::validate(inputInfo,
+                                                           kernelInfo,
+                                                           biasInfo,
+                                                           outputInfo,
+                                                           padStrideInfo,
+                                                           depthMultiplier,
+                                                           arm_compute::ActivationLayerInfo(),
+                                                           aclDilationInfo);
 
     if (optimizationStatus.error_code() == arm_compute::ErrorCode::OK)
     {
-        m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayerOptimized>();
-        static_cast<arm_compute::NEDepthwiseConvolutionLayerOptimized*>(
+        m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer>();
+        static_cast<arm_compute::NEDepthwiseConvolutionLayer*>(
             m_pDepthwiseConvolutionLayer.get())->configure(&input,
                                                            m_KernelTensor.get(),
                                                            m_BiasTensor.get(),