Machine Learning (ML) is a subset of the wider field of artificial intelligence. It is the area of technology where computers are fed large amounts of data and by applying algorithms, computers find patterns and make accurate predictions based on that data without any human intervention.
Present Scenario for AI and Machine Learning in Small Business
SaaS (Software-as-a-service) providers offer AI-ready solutions at low or no cost, making state-of-the-art tools available, even on a budget. WorkFusion, for instance, helps businesses plug AI tools into existing workflows using their RPA Express. It is a free downloadable tool that offers enterprise-scale automation and requires no coding. Literally, in just minutes, you can see improved efficiency and reduced workflow. By using clustering and segmentation algorithm we can find hidden patterns within customer base. Using these patterns, businesses can sell more to the same number of customers.
Two factors that are making machine learning accessible to small businesses are : the commodification of machine learning algorithms and the democratization of pre-trained ML models. These two shifts allows several small businesses to build custom ML solutions that could not be dreamt even a few years back.
Making product recommendations is another great way to use machine learning to grow business is to utilize machine learning recommended systems. Businesses can also use machine learning to up-sell the right product, to the right customer at the right time. Nowadays all big online retailers display more suitable products to each customers and increase sales. With the help of machine learning, the credit card company would be able to automate this decision-making process using a ML model.
Fraud Protection and Data Filtering is yet another example of ‘Classification’ in machine learning. At the time of purchase, machine learning is applied to reduce the risk of credit fraud in small businesses. Machines learn from historical datasets that contain fraudulent transactions. With this, they can identify patterns that represent a typical fraudulent transaction.
Drawbacks of Machine Learning in Small Business
AI and ML is currently a “dark art” in the sense that it requires highly specialized talent. The glitch as of now is that many small businesses do not have a clear business objective, or budget to allocate high-paying data science positions, or automated software. It will instead need to rely on easier-to-use tools for existing staff in marketing, IT and management. The longer we use machine learning in small business, the more accurate any application of it will become. Tools like IBM Watson aim to improve the accessibility of machine learning solutions, but most of them still require a bespoke setup period and unique skill set.
Machine Learning in Small Business Holds Huge Potential
Despite all the drawbacks and pitfalls, cloud-based big data, machine learning-based solutions will grow three times as of now. The uses of it are almost infinite and the benefits of having an automatically improving model are too good to ignore. As AI and ML becomes more accessible (cheaper, with better defined business uses, and with less requisite computer science knowledge), we can expect to see ML make its way into small businesses.
