3 Ways to Implement Machine Learning and AI into Small Businesses

Earlier this month, John Giannandrea, Apple’s head of artificial intelligence (AI), gave insight into how Apple is leveraging machine learning (ML) within their iOS and the future of machine learning at Apple. Anything from language translation to only sorting photos on your phone into pre-made galleries is made possible with machine learning. These various types of machine learning applications are becoming more and more common and essential.


However, a common misperception of AI and machine learning is that these advanced and sophisticated technologies are only for big brands with budgets that allow for experimentation and implementation.

A small business owner reading a report like Gartner’s 2019 survey of CIO’s would find that although 37% of organizations have installed some form of AI or machine learning, most of the CIO’s interviewed were from large brands. This type of survey may further intimidate small and medium-sized business owners into thinking the growing age of AI and machine learning isn’t ready for their company yet. But, you’d be surprised by how easily small companies can adopt cutting-edge technology without having to rely on an extensive budget.



For small businesses, ML software as a service can be a great tool to utilize, especially in consumer and B2B marketing spaces. In fact, 40% of marketers prioritize AI and machine learning more than any other department and consider them critical to their success. 


One familiar and accessible ML tool marketers at small businesses can leverage is a chatbot tool for their website. Chatbots now utilize natural-language processing (NLP) that can interact conversationally with website visitors and collect information like preferences visitors have as they browse a website.


Chatbot tools like Botsify also allow for integration with several services and offer an easy interface to help customize your company’s brand into their templates.


In terms of ML digital marketing tools, a chatbot is just one of the many corners that can be explored. Also, consider implementing machine learning marketing applications for email marketing, ad targeting, voice search, or predictive analysis to help create your campaigns reach new, multiple touchpoints.



Like marketing, cybersecurity is witnessing a fast-growing trend with investments into machine learning tools to help protect their own company and customers. ABI Research estimates ML, AI, and big data spending will increase to $96 billion by 2021.


Machine learning technology can track users’ patterns and make assessments of these patterns, such as the iPhone creating galleries from related pictures, as previously mentioned. This technology can be applied for security responsibilities by implementing security algorithms into something like your mobile application.


If your business relies on the consumer making financial transactions, it’s the company’s responsibility to keep any entered information secure.

Biocatch, for example, utilizes behavioral biometrics, a machine learning technology that tracks user behavior within an application as another form of security. Behavioral biometrics can identify when a different person uses an application by the way they move around the app or the way they type.  

Sometimes even just adding a single line of code can improve your mobile application’s security and add another form of authentication working in the background.



Another aspect of any business that requires managing a ton of data, repetitiveness, and predictably is the accounting department, which means machine learning for accounting tasks is a relationship that makes too much sense to not explore.


The future of accounting is heavily entangled with AI and ML, and back in 2018, a report suggested tasks like taxes and payroll would eventually become fully automated. In 2020 machine learning is now applied to generating and processing invoices, even including specific requirements with each task.


Xero, a New Zealand-based accounting software company, provides a cloud accounting software that creates and processes invoices for small businesses. The machine learning aspect in the software enables the creation of invoices based on past behaviors for customers.


Whether you leverage machine learning through marketing, security, or accounting, the decision ultimately depends on where you possibly see the value and ROI of any machine learning tool. For a small-to-medium-sized business, where that value is found can vary.


More and more companies are tapping into or at least exploring how machine learning can impact their business as the machine learning market is expected to grow at 42% CAGR by 2024. While adoption of AI and ML may be daunting, machine learning models are proving to show increasing value to any business size.


Interested in implementing ML or AI in your business process? Contact us at info@quantilus.com for a consultation and learn more about what Quantilus has to offer here.



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