For many businesses, machine learning seems like a distant yet game-changing technology. What might surprise you is just how close you could be to be deploying it in your company in 2022.

Critics couldn’t be more wrong when they label machine learning and artificial intelligence (AI) as mere buzzwords. They’re more than mere terms used by firms who feel they should be getting involved with the ‘next big thing’.

We see the tangible benefits in action every day, and McKinsey estimates that these technologies could deliver up to $1 trillion of extra value for the banking industry alone each year.

On a wider scale, projections show that AI could provide a $13 trillion boost to the world economy by 2030.

Whatever your views, it’s impossible to argue that those figures aren’t exciting. So, how can businesses secure these benefits for themselves? Find out here along with what machine learning is, where you’re already using it, and how it can help your company.

What is Machine Learning?

To understand machine learning, it’s necessary to first look at AI. In simple terms, artificial intelligence is a branch of computer science that focuses on equipping machines to perform tasks that would usually require human intelligence.

It takes applied statistics and scales it by automating data collection and calculations to gain insight and make decisions. This allows machines to exhibit the capabilities of certain aspects of the human mind, such as adjusting, problem-solving, and decision-making.

Machine learning then, by extension, is the application of AI that allows machines to automatically learn and improve with experience.

In other words, it does away with the need for constant human input and programming to make advances. Computers observe patterns in data, make decisions, and learn from the outcomes so they can do better the next time.

To prove that this is more than a distant and futuristic technology, you need only to look at its many everyday applications:

• Google’s predictive search bar.
• Filtering spam mail from your inbox.
• Selecting the nearest Lyft to minimize wait time.
• Online loan approvals, check deposits and fraud alerts.
• The ever-present social media ‘algorithms’ controlling what we see and how often.
• Chatbots that can create customized website templates and hold a conversation for hours on end.
• The smart assistants that pervade our phones, homes, even doorbells.

And in industrial settings, these same algorithms can be used to predict asset failures.

The Business Case for AI

For consumers, some of these applications might seem like novelties. For businesses, though, they can be truly transformative. Used in the right way, it can smooth out business processes while improving customer and user experiences.

Robotic Process Automation (RPA) is a great foundation for transformation, and for starting your machine learning journey. It’s an entry point in streamlining operations and cutting costs by automating everyday business tasks with data collection, compiling, and decision-making.

At a basic level, RPA interacts with a user interface to capture data and edit applications in the same way that humans do.

RPA offers a way to ease the burden of repetitive yet business-critical tasks — freeing up the time of humans to focus on other, more important things. Best of all, it is relatively quick to deploy, and there are many out-of-the-box solutions.

Examples include front-end online customer support, financial reporting, and even employee onboarding. These are all tasks that can be eliminated from human employees’ tasks, yet ones that machines can perform at pace and with greater accuracy 24 hours a day, 365 days a year.

It’s not difficult to see why RPA is gaining such traction in the business world. As Adrian Garcia, our VP of Transformation & Strategy, puts it:

“the returns come in quarters, not years”.

Bridging the Innovation Gap

Using these technologies can save you money and time while putting you ahead of the curve. So why don’t you have it yet? Well, for most businesses the difficulty is knowing where to start.

Contrary to popular belief, AI and machine learning are not catch-all solutions and they can’t change the way that you do business with the flick of a switch.

The businesses successfully deploying these technologies haven’t gone from analog to digital in one fell swoop. Instead, they’ve invested in mobile technology, and have a robust IT strategy in place to ensure that innovations like RPA can slot into the model and start to add value from day one.

The reality is that you can’t go from A to Z with one new technology. Unless you already have devices, infrastructure, and the internet built into your business, you don’t yet have the data needed to make a real difference in your operations and your bottom line.

Getting Ahead

Part of the problem is that businesses have been slow to invest in technologies and processes that bring all innovation investments into a unified strategy that can serve as the foundation for machine learning & AI.

Just like blockchain, many corporate leaders are happy to use these terms as innovation buzzwords. Yet they’re more reluctant to invest good money in building unified digital strategies and allowing these technologies to drive future growth.

For those firms that do invest, there is a real opportunity to get ahead of the game and to break away from your competitors.

Modernized solutions like AI are becoming easier and cheaper to apply with off-the-shelf solutions available without the need for any significant in-house development.

Innovation is picking up too, and in the future, we can expect to see businesses upgrading more with automation in their essential operations. With continued growth in the 22 billion-device-strong internet of things (IoT), 2022 is likely to see a greater reliance on digital innovations.

Rather than sending data out and waiting for a decision back from cloud-based AI, leaders will be looking to leverage IoT and invest in having more intelligence at the edge. In practice, this will hopefully mean faster decision-making and devices that can adjust their output to optimize lifespan and productivity.

Gaining the ‘First Mover’ Advantage

While many companies risk falling behind if they fail to invest in AI, getting involved needn’t be hard. The most difficult thing is just knowing where to begin. Every day we help businesses to chart out what it is they want to achieve and select the right AI and machine learning to get them there.

By giving businesses a roadmap for digital transformation, we can break down their investment and make smaller incremental gains that can be scaled over time.

The challenge then is in balancing art and science to create a user interface that brings value to a business. For that, it takes an expert design firm like us to construct great customer experiences.