diff --git a/Project.toml b/Project.toml
index 2a992247..63ac73c4 100644
--- a/Project.toml
+++ b/Project.toml
@@ -34,7 +34,7 @@ oneAPI_Support_jll = "b049733a-a71d-5ed3-8eba-7d323ac00b36"
 
 [compat]
 AbstractFFTs = "1.5.0"
-AcceleratedKernels = "0.3.1, 0.4"
+AcceleratedKernels = "0.5"
 Adapt = "4"
 CEnum = "0.4, 0.5"
 ExprTools = "0.1"
diff --git a/src/accumulate.jl b/src/accumulate.jl
index d3647faa..193a0cb0 100644
--- a/src/accumulate.jl
+++ b/src/accumulate.jl
@@ -3,19 +3,23 @@ import oneAPI: oneArray, oneAPIBackend
 import AcceleratedKernels as AK
 
 # Use a smaller block size on Intel GPUs to work around a scan correctness issue
-# with the Blelloch parallel prefix sum at larger block sizes (>=128).
+# with the parallel prefix sum at larger block sizes (>=128).
 const _ACCUMULATE_BLOCK_SIZE = 64
 
+# The scan algorithm for the given `dims`: whole-array scans and scans along a dimension
+# use different algorithms, so pick the one AcceleratedKernels' `Auto()` would, with our
+# block size.
+_scan_alg(dims) = dims === nothing ? AK.ScanPrefixes(block_size = _ACCUMULATE_BLOCK_SIZE) :
+    AK.SliceScan(block_size = _ACCUMULATE_BLOCK_SIZE)
+
 # Accumulate operations using AcceleratedKernels
-Base.accumulate!(op, B::oneArray, A::oneArray; init = zero(eltype(A)),
-                 block_size = _ACCUMULATE_BLOCK_SIZE, kwargs...) =
-    AK.accumulate!(op, B, A, oneAPIBackend(); init, block_size, kwargs...)
+Base.accumulate!(op, B::oneArray, A::oneArray; dims = nothing, alg = _scan_alg(dims), kwargs...) =
+    AK.accumulate!(op, B, A; dims, alg, kwargs...)
 
-Base.accumulate(op, A::oneArray; init = zero(eltype(A)),
-                block_size = _ACCUMULATE_BLOCK_SIZE, kwargs...) =
-    AK.accumulate(op, A, oneAPIBackend(); init, block_size, kwargs...)
+Base.accumulate(op, A::oneArray; dims = nothing, alg = _scan_alg(dims), kwargs...) =
+    AK.accumulate(op, A; dims, alg, kwargs...)
 
-Base.cumsum(src::oneArray; block_size = _ACCUMULATE_BLOCK_SIZE, kwargs...) =
-    AK.cumsum(src, oneAPIBackend(); block_size, kwargs...)
-Base.cumprod(src::oneArray; block_size = _ACCUMULATE_BLOCK_SIZE, kwargs...) =
-    AK.cumprod(src, oneAPIBackend(); block_size, kwargs...)
+Base.cumsum(src::oneArray; dims = nothing, alg = _scan_alg(dims), kwargs...) =
+    AK.cumsum(src; dims, alg, kwargs...)
+Base.cumprod(src::oneArray; dims = nothing, alg = _scan_alg(dims), kwargs...) =
+    AK.cumprod(src; dims, alg, kwargs...)