Artificial intelligence (AI) can supercharge your digital transformation efforts—if you understand and adopt it in the right way.
The likelihood a digital transformation will fail is high. McKinsey says that less than 30% of digital transformation projects succeed. In some industries, the success rate is as low as 4%.
But it doesn't have to be like this.
A big reason digital transformations fail is because companies don't adequately leverage artificial intelligence.
"The organizations with successful transformations are likelier than others to use more sophisticated technologies, such as artificial intelligence," says McKinsey.
In reality, AI can be one of the best ways to get value out of a digital transformation.
Why?
Because superior customer experience is at the center of successful digital transformations.
Today, superior customer experience means delivering the personalized experience every consumer demands.
The only way to deliver a personalized experience at scale is with AI.
But what is AI? How do you use it for digital transformation? And how can you get started with AI driven digital transformation?
This article has the answers.
Let's cut through the jargon before we dive into artificial intelligence digital transformation.
The term "digital transformation" isn't that descriptive. It skirts the line of becoming a buzzword. But, love it or hate it, it's now a common term.
We prefer a simple definition of digital transformation:
Digital transformation is when you integrate technology so extensively into your business that you fundamentally change how the business operates.
This integration of technology takes place across all of a business' products, operations, sales, marketing, IT, and customer service functions.
Digital transformation is not about buying new software or adopting shiny new technology. It's about changing how your business works from the ground-up to be digital-first.
This change results in two broad outcomes:
Every company's digital transformation roadmap will look different, because every company is different.
But all successful digital transformations have one thing in common:
They revolve around customer experience.
Customer experience is just the grand sum of experiences a customer has with your company from first-touch to long after purchase.
Customer experience isn't just about improving your website or product or customer service. It's also about improving every other internal-facing and customer-facing part of your company to deliver more value to consumers and customers.
In this way, customer experience is the thread that runs through every single aspect of your digital transformation work. By rethinking customer experience, you fundamentally alter how your company delivers value.
And artificial intelligence provides the key to unlock superior customer experience—and successful digital transformation.
AI comprises a group of real, game-changing technologies that are the key to completing a successful digital transformation.
AI is the "science of making machines smart," which means teaching machines to do human-like tasks. We teach machines to see, hear, speak, write, and make predictions, recommendations, and decisions.
Unlike traditional software (think your typical automation, CRM, and operational software), AI has the power to analyze huge sets of data, then make predictions based on that data. AI can then improve its results over time by learning from the data.
This ability to improve is called machine learning, and it's what gives many AI technologies the capacity to learn on their own.
Data is the key to understanding why AI matters to digital transformation.
AI is essential for digital transformation, because digital transformation relies on data.
Data is the lifeblood of every modern business. Every interaction your business has with customers and markets generates data.
This data comes from almost everywhere, including CRM systems, marketing platforms, website analytics, social media, online orders...and hundreds of other sources.
This data contains essential insights that keep your business successful and competitive. Insights like:
These insights help you make better decisions at speed-decisions that massively improve business outcomes.
There's just one problem...
Traditional technology does a poor job of unlocking the value from your data.
The traditional technology you use today is entirely rules-based. It has been explicitly programmed by a human to perform tasks. But it can only do what it's told to do. It never adapts or improves unless human programmers update it.
That means traditional technology can't analyze data. It can't learn from data. And it can't improve how it operates based on new data. That makes traditional technology pretty useless for digital transformation.
Make no mistake, traditional technology is valuable. It has historically been used to automate and/or speed up tasks, leading to cost savings and productivity gains. It also has made activities more trackable.
(For instance, marketing automation software has made marketing easier and more metrics-driven.)
That worked well in the early internet era, when companies still relied on rudimentary online presences and lots of offline activities.
Today, though, this technology looks downright dumb. It can automate activities and track data. But it can't truly analyze or predict anything. It can't change or adapt to new information. Only AI can.
AI's unique capabilities make it a need to have, not a nice to have, for digital transformation.
Without the ability to analyze, predict, and improve based on data, your digital transformation will fail.
It really is that simple.
Today, your traditional technology can provide and visualize data, which is helpful, but now common. But they don't have machine learning that can learn and improve using that data.
AI does. That's why it needs to be front and center in your digital transformation work.
It's also why today many companies are using AI to support digital transformation across most areas of their businesses.
According to data from TDWI Research the top five departments where AI is being used today are:
According to the same research, organizations are mostly using structured data, text data, and time series data in their digital transformation work.
This makes sense. All three are areas where AI can be applied to extract insights and make predictions.
TDWI also says a handful of major use cases dominate AI-powered digital transformations:
When you look at the commonalities between all these departments and use cases, AI's value becomes clear...
AI reduces costs and increases revenue at scale.
AI reduces costs by using your data to automate costly, time-consuming activities like:
AI also unlocks unprecedented revenue opportunities by using your data to get better insights and make better predictions like:
At the end of the day, it's not about buzzwords. It's about data.
Data drives every aspect of digital transformation, no matter what type of company you are.
And the only way today to unlock the value of that data is to turn your digital transformation into an AI transformation.
The good news is that you can get started with AI today...
The bad news is that most companies take the wrong approach to AI implementation, and then see their AI projects fail. But this doesn't have to happen to you.
Here are some of the top strategies we've seen the most successful companies use to start incorporating AI into their digital transformation strategy.
Over time, successful digital transformation will mandate AI be used in every part of the business. But you'll never get there if initial AI projects don't succeed.
To give yourself the highest chance of success, commit to a single narrowly focused AI project to start.
What do we mean by narrowly focused? Your project should aim to use an AI tool to solve a very clear business problem or very specifically improve a business process.
In fact, you should start with the use case first, then determine if/how AI technology can help.
Here are some examples of clear use cases in marketing:
Often, you can find a use case by cataloguing everything your team does in a day. Some of these tasks will jump out as more time-consuming that others. Those tasks are a good place to start.
You don't need to have a computer science background to confidently kick the tires of an AI solution.
Unfortunately, some sales reps selling AI solutions know less about AI than you do. And some companies fall prey to over-hyping or over-promising what their AI application can do.
You'll want to do free trials and demos often. When you do, you'll want to ask important questions like:
In our 2021 State of Marketing AI Report, we polled hundreds of marketing leaders on AI understanding and adoption. As part of that survey, they told us their top barriers to adopting AI. To our surprise, fear wasn't a major factor...
Instead, 70% of those surveyed said lack of education and training was a major barrier. Unsurprisingly, only 14% said their companies provided this training.
Successful AI initiatives mean developing a base level of AI readiness in your company. At a bare minimum, every employee should understand:
From there, you must champion ongoing AI education, so teams learn how to apply AI to your business and confidently buy AI technology. (Our marketing AI conference is a great way to do this.)
You don't just need AI talent for your digital transformation project. Your organization will need serious AI talent across every area of your business to stay competitive moving forward.
This includes actively recruiting talent on the technical side who have backgrounds in data science or big data. It may even include hiring engineers who can build AI models and ML models.
But you'll also want to identify AI-powered talent in non-technical functions. Tomorrow's marketers, salespeople, analysts, managers, and customer success pros will need a foundational understanding of real-world AI for business.
Look for talent with online course experience or certifications in AI tools and topics. Keep an eye out for hungry professionals who work at AI-powered companies. You may even want to look for professionals writing about AI.