Gartner Research

3 Machine Learning Myths for Forecasters

Published: 14 February 2019

ID: G00431509

Analyst(s): Finance Research Team


Few FP&A organizations use ML in financial forecasting, despite its significant potential. We help financial planning and analysis leaders take a focused exploration of ML-enabled forecasting by dispelling three myths about its forecast accuracy, capabilities required and level of automation.

Table Of Contents

Myth 1: ML Can Improve the Accuracy of Any Forecast

A Defined, Beatable Benchmark to Exceed

Data With Integrity

Ambiguous Causality

Myth 2: Starting ML Requires a Data Scientist or Lots of Money

Myth 3: ML Models Require Minimal Human Intervention


About This Research


©2021 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates. This publication may not be reproduced or distributed in any form without Gartner’s prior written permission. It consists of the opinions of Gartner’s research organization, which should not be construed as statements of fact. While the information contained in this publication has been obtained from sources believed to be reliable, Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartner research may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such. Your access and use of this publication are governed by Gartner’s Usage Policy. Gartner prides itself on its reputation for independence and objectivity. Its research is produced independently by its research organization without input or influence from any third party. For further information, see Guiding Principles on Independence and Objectivity.

Already have a Gartner Account?

Become a client

Learn how to access this content as a Gartner client.