Maximize ROI with Managed Artificial Intelligence for Small Medium Businesses

As a business leader, are you considering using Artificial Intelligence (AI) and Machine Learning (ML) to enhance your business outcomes? Businesses of all sizes are automating processes with technology for a variety of reasons—whether it’s more efficiency, lower costs, or another distinct benefit.

If you have a limited technical background, you may be skeptical of investing in AI and ML due to the potential costs and the time taken to build the solutions, as well as the uncertainty to realize a return on investment (ROI). You might also wonder if you even need to hire the right talent to manage such an undertaking.

We recognize small and medium businesses (SMBs) face a number of challenges today as they try to meet business KPIs on increasing revenue and customer base, while dealing with talent shortages. As e-commerce, social platforms, and online services become the predominant way of doing business, SMBs have to innovate rapidly to acquire new customers, reduce fraud, predict demand, improve the customer experience, and go to market quickly. AI can help your SMB close those gaps so you can focus on other parts of your business.

Simple definitions of AI and ML for SMBs

At Amazon Web Services, SMB customers are increasingly looking at AI and ML solutions to solve the business challenges previously mentioned. If you’re new to this topic, let us clarify the differences between AI and ML and how they might be practically used in your operations.

AI focuses on emulating repetitive actions and tasks in real time without human intervention. For example, this might include a customized follow-up message after an online purchase or a chatbot that answers customers’ frequently asked questions. Our customers with small post-sale support teams find this especially helpful in scaling interactions without necessarily hiring more talent.

ML refers to technology and algorithms that look at AI solutions (such as the ones above) and layer in historical data to provide predictions. For example, if your business has a significant amount of sales data but a limited number of analysts, ML can help you understand and forecast trends. Predictions help you better manage internal operations and make investments where truly needed—all in the name of scaling effectively.

Interest in AI and ML is evident, but certain challenges exist

While the ability to automate manual processes and predict trends is promising, it does take a certain amount of effort to implement. However, the outlook is promising and other SMBs such as yours see the benefits. In fact, according to an IDC report specifically focused on SMBs, an analyst mentioned the following: “SMBs see clear advantages of combining ML and AI with cloud services.” So, what are some of the challenges that impede companies from adopting these solutions?

1. Building and maintaining AI and ML infrastructure: AI and ML solutions built from scratch need a large capital investment (capex) as they run on large servers with heavy compute and storage needs. This puts significant pressure on SMBs to take advantage of these innovative cloud solutions. Per IDC, “…inadequate or lack of purpose-built infrastructure capabilities are often the cause of AI projects failing.”
2. Integrating and maintaining applications: When SMBs build a solution, connecting it with existing applications requires custom coding, long lifecycles, testing, and expertise. This burns a lot of the existing teammates’ time rather than focusing on innovating and modernizing solutions.
3. Lacking data science talent: A study shows that SMBs adopting AI and ML solutions find it difficult to hire data science engineers due to market demand. SMBs cannot justify additional headcount without seeing business outcomes first. As organizations plan to re-skill their workforce, the lack of skill impedes overall innovation and timeline.
4. Not enough historical data to build solutions: To build machine learning solutions, large, historical datasets are required. Most SMBs do not own enough data specific to their industry and often struggle to build such solutions. This can lead to inaccurate or incomplete predictions

New to digitization or looking to add more cloud capabilities to your SMB? Explore solutions by industry, benefit, use case, and more on AWS Smart Business

What are managed AI services and how can they help SMBs?

There are a few solutions to the challenges above in the form of managed AI services. These services are powered by machine learning models and provide strong intelligence for your business. SMBs can quickly build out and/or deploy these services scale whether or not they have engineering talent in-house.

AWS AI Services are critical for SMBs looking to gain a competitive edge and many are considered low- or no-code solutions. This means AWS can help you guide this journey. Figure 1 depicts how you can derive successful results with less overhead expenses so you can refocus your efforts on sales.

Figure 1: Four pillars of managed AI solutions: cost savings, no ML experience required, no customization required, no infrastructure to maintain

Let’s dive deeper into four specific use cases on how SMBs can use managed AI solutions to become smart businesses.

Helping detect fraud and reduce loss

SMBs face increasing pressure from fraudulent transactions and costs that aren’t easy to absorb. Industries such as financial services, travel and hospitality, healthcare, and retail, lose money on transactions, fake accounts, bot users, and paying out rewards as a result of fraud. AI Services can learn fraudulent patterns from historical data and provide insights into potential fraud happening in real time. However, businesses that haven’t adopted such solutions rely on manual intervention, which results in huge operational expenses prevents SMBs from scaling.

Personalizing recommendations to help improve customer experience

SMBs are progressively looking to drive sales and provide value to their customers with custom recommendations. This helps SMBs operate in an agile way to improve customer experience, retention, and grow the business. To build such enhanced features in the software, SMBs have to spend long development cycles and time to market. Fortunately, AI Services can help shorten development cycles by learning from past customer behavior patterns. This can help create recommendation features to enhance purchasing

Image and video recognition to identify inappropriate content for end-user safety

SMBs—especially in media and entertainment—are building applications that support large scale, user-generated videos and images. This enables them to emulate large social media platforms’ ability to engage and retain visitors and turn them into returning customers. However, this could lead to users uploading inappropriate content. You have likely seen news stories over the past few years about how unmoderated content can lead to brand reputation damage and legal issues. Identifying inappropriate content in near real time is a complex task requiring a lot of resources. AI Services can be embedded quickly with existing applications to provide fast content moderation and help you reduce business risk.

Serving customers targeted marketing to help increase sales

SMB companies hoping to scale their customer acquisition efforts are adopting AI-powered marketing tactics such as programmatic ads, chatbots, and surveys. According to Forbes, AI will drive future marketing. Even though traditional ways of marketing may work, they may not be enough to thrive in the competitive market today. Today, with AI Services, SMBs can segment customers into demographics groups such as gender, age, income levels, interests, and many more attributes to target their services. Without much investment, SMBs can implement and validate business outcomes in a short time.

Next Steps

Harnessing modern AI and ML in business process can be transformational. However, low- or no-code AI services can make SMBs successful in adopting these solutions with a quick turn around on their ROI with a “pay-as-you-use” on the underlying ML lifecycle and processes.

As a next step, SMBs can begin accelerating their AI/ML adoption today by leveraging AWS Managed AI services.