diff --git a/doc/source/whatsnew/v1.3.1.rst b/doc/source/whatsnew/v1.3.1.rst
index 2ce146660f98c..2e3c15eca972f 100644
--- a/doc/source/whatsnew/v1.3.1.rst
+++ b/doc/source/whatsnew/v1.3.1.rst
@@ -24,6 +24,7 @@ Fixed regressions
 - Fixed regression in indexing with a ``list`` subclass incorrectly raising ``TypeError`` (:issue:`42433`, :issue:`42461`)
 - Fixed regression in :meth:`DataFrame.isin` and :meth:`Series.isin` raising ``TypeError`` with nullable data containing at least one missing value (:issue:`42405`)
 - Regression in :func:`concat` between objects with bool dtype and integer dtype casting to object instead of to integer (:issue:`42092`)
+- Bug in :class:`Series` constructor not accepting a ``dask.Array`` (:issue:`38645`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/core/construction.py b/pandas/core/construction.py
index 7e7205d1351b3..68d7f6c6f8a22 100644
--- a/pandas/core/construction.py
+++ b/pandas/core/construction.py
@@ -560,8 +560,11 @@ def sanitize_array(
             raise TypeError(f"'{type(data).__name__}' type is unordered")
 
         # materialize e.g. generators, convert e.g. tuples, abc.ValueView
-        # TODO: non-standard array-likes we can convert to ndarray more efficiently?
-        data = list(data)
+        if hasattr(data, "__array__"):
+            # e.g. dask array GH#38645
+            data = np.asarray(data)
+        else:
+            data = list(data)
 
         if dtype is not None or len(data) == 0:
             subarr = _try_cast(data, dtype, copy, raise_cast_failure)