diff --git a/src/plugins/intel_cpu/src/transformations/transformation_pipeline.cpp b/src/plugins/intel_cpu/src/transformations/transformation_pipeline.cpp
index 54a038c9492db6..4f9e103fd8254c 100644
--- a/src/plugins/intel_cpu/src/transformations/transformation_pipeline.cpp
+++ b/src/plugins/intel_cpu/src/transformations/transformation_pipeline.cpp
@@ -963,9 +963,13 @@ void Transformations::MainSnippets(void) {
         // The current solution with ExtractExplicitMatMulTranspose pass is slower for non-f32 cases than using of brgemm_copy_b kernel
         if (matmul->get_transpose_a() || matmul->get_transpose_b())
             return false;
-        if (in_type0 == ov::element::i8)
+        if (in_type0 == ov::element::i8) {
+            // [150531] AVX2_VNNI_2 is not fully supported yet
+            if (dnnl::impl::cpu::x64::mayiuse(dnnl::impl::cpu::x64::avx2_vnni_2))
+                return false;
             return dnnl::impl::cpu::x64::mayiuse(dnnl::impl::cpu::x64::avx512_core_vnni) ||
                    dnnl::impl::cpu::x64::mayiuse(dnnl::impl::cpu::x64::avx2_vnni);
+        }
         if ((in_type0 == ov::element::bf16 && in_type1 == ov::element::bf16) ||
             ((in_type0 == element::f32 && in_type1 == ov::element::f32 && inferencePrecision == ov::element::bf16))) {
             // Implementation calls AMX BF16 brgemm only for tensors with K and N aligned on 2, otherwise fallbacks on vector impl