How to Build a Better Business Strategy with AI/ML

9 September 22

By 2030, artificial intelligence is slated to reshape the landscape for global business. According to PwC, AI is going to revolutionize productivity to drive unparalleled GDP growth. The combination of increased personalization, product variety, and affordability will fuel consumer-side demand.

In less than a decade, every industry will embrace a new wave of AI-powered digital transformation, using machine learning (ML) algorithms to achieve never-before-seen levels of productivity that redefine what is possible.

To see how we get there, let’s take a closer look at the technology behind this change.

What is AI/ML and Why Is it Important?

The technology world loves acronyms. The two that are important here are ‘AI’ and ‘ML.’ These letters are often found together. Here’s what they mean–

Artificial Intelligence (AI) refers to a broad category of computer-derived intelligence. Intelligence is the ability of a system, biological or technological, to interpret information from its environment and carry out actions based on that stimuli.

Machine Learning (ML) refers to a specific application of artificial intelligence where a specific data set is fed into a model to produce a desired calculation or outcome.

Here are a few actionable steps that your business can take to build a better business strategy today.

Redefine Your Marketing Strategy with AI/ML

You’re probably already invested in collecting data about your target audiences and consumer behaviors to sell your products. And you’re probably also aware that a lot of the data that is collected is never used. With AI/ML technology enablement, you can focus on finding the right data and making the most use of that data.

Building the right technology stacks using Amazon Web Services (AWS), it’s simple to build and train machine learning algorithms capable of predicting the outcome of your marketing campaigns. This technology is able to mine high-quality data from a variety of business and call center analytics, verify intent and determine sentiment in milliseconds, making it possible to get an accurate feel for how consumers really feel about your products or services.

Invest in Data-Driven Culture

Jumping on the data-driven business bandwagon might feel like hype, but there’s something more than allure there. Yes, everyone seems to be doing it. And yes, some plans are better than others–resulting in mixed results. Keep in mind that the internet wasn’t a fad. Digital marketing as a whole has transformed businesses. And in the same ways that companies took big chances on these trends in the early 2000s and 2010s, now is the time to invest in the data-driven business culture.

Since 2017, Amazon’s SageMaker has made ML widely accessible to businesses of all sizes. This tool includes pre-trained ML algorithms with a simple, point-and-click interface that streamlines the process of creating, training, and implementing AI/ML features. With accessibility nailed down, businesses should be looking at laying a foundation that supports further AI/ML integration by embracing a data-driven culture that prioritizes data quality from day one.

Rethink Fraud Detection Efforts

Fraud is a big deal. From internal corruption, like a payroll full of false names to consumer theft, businesses lose about 5% of their annual revenue to fraudulent transactions. This is one area that AI/ML excels–offering superior pattern recognition without the resource-intensive inputs of traditional auditing measures.

Amazon Web Services offers a suite of tools that can detect and flag suspicious payments, identify fraudulent accounts, validate emails, and finally put a stop to loyalty program abuse. Amazon Fraud Detector automates the machine learning model to continuously adapt to new patterns, staying on top of fraud as it’s perpetrated.

Leverage Personalization to Drive Loyalty

Your business works hard for the customers that it has earned. Keep them loyal with a new wave of technology enablement that empowers a new level of personalization. The ML suite available through AWS can help you identify ‘red zone’ customers on the brink of walking away, as well as all the interactions that led them to that zone so that you can pinpoint issues and offer effective resolutions.

Simplify the process of creating complex ML algorithms with effective, pre-built AWS models that process your data to show you what you need to see. Forage through unstructured data streams like social media posts and reviews to determine sentiment. Put that information side by side with structured data like real sales numbers to see the complete picture. And then, follow through with tools like Amazon Rekognition can turn images and video into searchable content, transforming the digital customer experience.

Final Thoughts on Building a Better Business Strategy with AI/ML

A variety of tools available from Amazon Web Services has made AI/ML technologies accessible on every scale. All you need to do is partner with the right data sciences team to connect your data to tools available to power a digital-first business strategy that will keep your dot on the map through 2030 and beyond.