diff --git a/doc/source/whatsnew/v0.21.0.txt b/doc/source/whatsnew/v0.21.0.txt
index 50f11c38bae23..4a90e3b9073c1 100644
--- a/doc/source/whatsnew/v0.21.0.txt
+++ b/doc/source/whatsnew/v0.21.0.txt
@@ -633,6 +633,7 @@ Sparse
 - Bug in :func:`SparseDataFrame.fillna` not filling all NaNs when frame was instantiated from SciPy sparse matrix (:issue:`16112`)
 - Bug in :func:`SparseSeries.unstack` and :func:`SparseDataFrame.stack` (:issue:`16614`, :issue:`15045`)
 - Bug in :func:`make_sparse` treating two numeric/boolean data, which have same bits, as same when array ``dtype`` is ``object`` (:issue:`17574`)
+- :func:`SparseArray.all` and :func:`SparseArray.any` are now implemented to handle ``SparseArray``, these were used but not implemented (:issue:`17570`)
 
 Reshaping
 ^^^^^^^^^
diff --git a/pandas/compat/numpy/function.py b/pandas/compat/numpy/function.py
index ccbd3d9704e0c..d42be56963569 100644
--- a/pandas/compat/numpy/function.py
+++ b/pandas/compat/numpy/function.py
@@ -184,6 +184,14 @@ def validate_cum_func_with_skipna(skipna, args, kwargs, name):
     return skipna
 
 
+ALLANY_DEFAULTS = OrderedDict()
+ALLANY_DEFAULTS['dtype'] = None
+ALLANY_DEFAULTS['out'] = None
+validate_all = CompatValidator(ALLANY_DEFAULTS, fname='all',
+                               method='both', max_fname_arg_count=1)
+validate_any = CompatValidator(ALLANY_DEFAULTS, fname='any',
+                               method='both', max_fname_arg_count=1)
+
 LOGICAL_FUNC_DEFAULTS = dict(out=None)
 validate_logical_func = CompatValidator(LOGICAL_FUNC_DEFAULTS, method='kwargs')
 
diff --git a/pandas/core/sparse/array.py b/pandas/core/sparse/array.py
index 3b45a013734c9..0424ac8703e25 100644
--- a/pandas/core/sparse/array.py
+++ b/pandas/core/sparse/array.py
@@ -615,6 +615,48 @@ def fillna(self, value, downcast=None):
         return self._simple_new(new_values, self.sp_index,
                                 fill_value=fill_value)
 
+    def all(self, axis=0, *args, **kwargs):
+        """
+        Tests whether all elements evaluate True
+
+        Returns
+        -------
+        all : bool
+
+        See Also
+        --------
+        numpy.all
+        """
+        nv.validate_all(args, kwargs)
+
+        values = self.sp_values
+
+        if len(values) != len(self) and not np.all(self.fill_value):
+            return False
+
+        return values.all()
+
+    def any(self, axis=0, *args, **kwargs):
+        """
+        Tests whether at least one of elements evaluate True
+
+        Returns
+        -------
+        any : bool
+
+        See Also
+        --------
+        numpy.any
+        """
+        nv.validate_any(args, kwargs)
+
+        values = self.sp_values
+
+        if len(values) != len(self) and np.any(self.fill_value):
+            return True
+
+        return values.any()
+
     def sum(self, axis=0, *args, **kwargs):
         """
         Sum of non-NA/null values
diff --git a/pandas/tests/sparse/test_array.py b/pandas/tests/sparse/test_array.py
index f653ee50982ad..8de93ff320961 100644
--- a/pandas/tests/sparse/test_array.py
+++ b/pandas/tests/sparse/test_array.py
@@ -664,6 +664,94 @@ def test_fillna_overlap(self):
 
 class TestSparseArrayAnalytics(object):
 
+    @pytest.mark.parametrize('data,pos,neg', [
+        ([True, True, True], True, False),
+        ([1, 2, 1], 1, 0),
+        ([1.0, 2.0, 1.0], 1.0, 0.0)
+    ])
+    def test_all(self, data, pos, neg):
+        # GH 17570
+        out = SparseArray(data).all()
+        assert out
+
+        out = SparseArray(data, fill_value=pos).all()
+        assert out
+
+        data[1] = neg
+        out = SparseArray(data).all()
+        assert not out
+
+        out = SparseArray(data, fill_value=pos).all()
+        assert not out
+
+    @pytest.mark.parametrize('data,pos,neg', [
+        ([True, True, True], True, False),
+        ([1, 2, 1], 1, 0),
+        ([1.0, 2.0, 1.0], 1.0, 0.0)
+    ])
+    def test_numpy_all(self, data, pos, neg):
+        # GH 17570
+        out = np.all(SparseArray(data))
+        assert out
+
+        out = np.all(SparseArray(data, fill_value=pos))
+        assert out
+
+        data[1] = neg
+        out = np.all(SparseArray(data))
+        assert not out
+
+        out = np.all(SparseArray(data, fill_value=pos))
+        assert not out
+
+        msg = "the 'out' parameter is not supported"
+        tm.assert_raises_regex(ValueError, msg, np.all,
+                               SparseArray(data), out=out)
+
+    @pytest.mark.parametrize('data,pos,neg', [
+        ([False, True, False], True, False),
+        ([0, 2, 0], 2, 0),
+        ([0.0, 2.0, 0.0], 2.0, 0.0)
+    ])
+    def test_any(self, data, pos, neg):
+        # GH 17570
+        out = SparseArray(data).any()
+        assert out
+
+        out = SparseArray(data, fill_value=pos).any()
+        assert out
+
+        data[1] = neg
+        out = SparseArray(data).any()
+        assert not out
+
+        out = SparseArray(data, fill_value=pos).any()
+        assert not out
+
+    @pytest.mark.parametrize('data,pos,neg', [
+        ([False, True, False], True, False),
+        ([0, 2, 0], 2, 0),
+        ([0.0, 2.0, 0.0], 2.0, 0.0)
+    ])
+    def test_numpy_any(self, data, pos, neg):
+        # GH 17570
+        out = np.any(SparseArray(data))
+        assert out
+
+        out = np.any(SparseArray(data, fill_value=pos))
+        assert out
+
+        data[1] = neg
+        out = np.any(SparseArray(data))
+        assert not out
+
+        out = np.any(SparseArray(data, fill_value=pos))
+        assert not out
+
+        msg = "the 'out' parameter is not supported"
+        tm.assert_raises_regex(ValueError, msg, np.any,
+                               SparseArray(data), out=out)
+
     def test_sum(self):
         data = np.arange(10).astype(float)
         out = SparseArray(data).sum()