diff --git a/connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala b/connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala
index 139c45adb442..877c3f89e88c 100644
--- a/connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala
+++ b/connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala
@@ -141,6 +141,12 @@ private[sql] class AvroDeserializer(
       case (INT, IntegerType) => (updater, ordinal, value) =>
         updater.setInt(ordinal, value.asInstanceOf[Int])
 
+      case (INT, LongType) => (updater, ordinal, value) =>
+        updater.setLong(ordinal, value.asInstanceOf[Int])
+
+      case (INT, DoubleType) => (updater, ordinal, value) =>
+        updater.setDouble(ordinal, value.asInstanceOf[Int])
+
       case (INT, dt: DatetimeType)
         if preventReadingIncorrectType && realDataType.isInstanceOf[YearMonthIntervalType] =>
         throw QueryCompilationErrors.avroIncompatibleReadError(toFieldStr(avroPath),
@@ -194,6 +200,9 @@ private[sql] class AvroDeserializer(
       case (FLOAT, FloatType) => (updater, ordinal, value) =>
         updater.setFloat(ordinal, value.asInstanceOf[Float])
 
+      case (FLOAT, DoubleType) => (updater, ordinal, value) =>
+        updater.setDouble(ordinal, value.asInstanceOf[Float])
+
       case (DOUBLE, DoubleType) => (updater, ordinal, value) =>
         updater.setDouble(ordinal, value.asInstanceOf[Double])
 
diff --git a/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala b/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
index ce38ada7c9e4..1f00392420be 100644
--- a/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
+++ b/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
@@ -921,6 +921,39 @@ abstract class AvroSuite
     }
   }
 
+  test("SPARK-49082: Widening type promotions in AvroDeserializer") {
+    withTempPath { tempPath =>
+      // Int -> Long
+      val intPath = s"$tempPath/int_data"
+      val intDf = Seq(1, Int.MinValue, Int.MaxValue).toDF("col")
+      intDf.write.format("avro").save(intPath)
+      checkAnswer(
+        spark.read.schema("col Long").format("avro").load(intPath),
+        Seq(Row(1L), Row(-2147483648L), Row(2147483647L))
+      )
+
+      // Int -> Double
+      checkAnswer(
+        spark.read.schema("col Double").format("avro").load(intPath),
+        Seq(Row(1D), Row(-2147483648D), Row(2147483647D))
+      )
+
+      // Float -> Double
+      val floatPath = s"$tempPath/float_data"
+      val floatDf = Seq(1F,
+        Float.MinValue, Float.MinPositiveValue, Float.MaxValue,
+        Float.NaN, Float.NegativeInfinity, Float.PositiveInfinity
+      ).toDF("col")
+      floatDf.write.format("avro").save(floatPath)
+      checkAnswer(
+        spark.read.schema("col Double").format("avro").load(floatPath),
+        Seq(Row(1D),
+          Row(-3.4028234663852886E38D), Row(1.401298464324817E-45D), Row(3.4028234663852886E38D),
+          Row(Double.NaN), Row(Double.NegativeInfinity), Row(Double.PositiveInfinity))
+      )
+    }
+  }
+
   test("SPARK-43380: Fix Avro data type conversion" +
     " of DayTimeIntervalType to avoid producing incorrect results") {
     withTempPath { path =>