Machine learning (ML) has moved beyond the hype to become a meaningful
driver of value for many organizations. Over two-thirds of businesses that
have fully embraced artificial intelligence (AI) say the technology has created
a better customer experience, and more than half say it has improved
decision-making, increased productivity, and allowed for innovation while
achieving cost savings.
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While it's clear that ML is an essential part of business transformation, many
organizations struggle to understand where to apply ML for the most impact.
Selecting the right ML use case requires you to consider a number of factors.
First, you need to find a balance between optimal business value and speed.
A proof of concept built by a siloed data scientist is not likely to generate
much enthusiasm for ML in an organization. What is more apt to attract the
needed commitment and funding is showing how ML can address the practical
issues your organization currently faces. Furthermore, you'll want to find
something that can be accomplished in 6–8 months so that you won't lose
momentum. This is especially true if this is your first foray into ML.
Second, you'll want to find a use case that is rich in data that you already have.
A good business use case with no data will lead to frustrated data scientists.
Lastly, you'll want to evaluate whether your business problem actually
requires ML for success and whether ML will result in better outcomes
than your traditional approach. These outcomes might be realized as cost
reduction, increased employee productivity, or an improved experience for
your customers.
The best way to satisfy all these criteria is to ensure that technical experts
and domain experts are working hand in hand on your ML project. Technical
experts can conduct feasibility assessments, and domain experts will ensure
the solution is solving a real business problem and will have a real impact.
INTRODUCTION
Solve your most common
business challenges with
machine learning
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"Artificial Intelligence (AI) and Analytics," PwC Tech Effect Blog, 2022
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