The rise of artificial intelligence (AI) and Machine Learning (ML) has been rapid and industry disruptive. More people have access to these technologies than ever, right down to the phones in our pockets. Like self-driving cars, the Internet of Things, and smart home security systems have become more prolific, the potential for both AI and ML continues to grow. SMEs are proving slow to take advantage of these technologies, and that’s largely due to a lack of understanding. AI and ML have become increasingly common in workplaces of every industry. That means it’s more important than ever that brand owners and business managers know a little more about the potential gains available through artificial intelligence and machine learning.
The End of Experimentation
Over the last few years, industries have been largely experimenting with AI/ML to find out how best to use it. As the technologies become more accessible, experimentation is gradually coming to an end. Healthcare, transportation, finance, and manufacturing brands alone are already moving past the experimentation stage and have adopted mass-scale adoption in a variety of different ways. SME brands in all sectors should be watching those bigger business models and taking note. The potential for ML and AI to level the playing field is just as impactful as social media was for marketing. That means that despite the inherent challenges, even the smallest of enterprises will be able to compete with the big names through the right applications of AI and ML.
Finding Team Members
One of the problems for business owners is that hiring tech specialists can be very challenging. That’s always down to a lack of understanding of what skills to look out for and the kinds of training applicants should have to perform AI/ML-related functions. That’s where research is going to come in. Tech buzzwords on a resume can look impressive, but without understanding what those terms mean, they can quickly lead to hiring mistakes that hold a company back from growth. While you should look for potential new employees with practical experience in AI and ML, formalized qualifications can be a lot more advantageous to watch for. Look for those applicants with Azure Machine Learning Studio training and who have used that training practically. The more you know what AI and ML can do for you, the easier it will be to fine-tune the relevant skills, training, and experience that you should be looking for.
Metadata – The New Gold
Big data has been called the ‘new oil’ for the last few years in almost every tech-related opinion piece and trend-spotting article. While the value of big data is indisputable, it’s metadata that will be joining the dots between big data and machine learning output. Labeling metadata is becoming the norm and is going to result in SMEs being better able to streamline those everyday business tasks and processes. One of the key challenges of big data is gleaning actionable insights from it. ML and AI are set to make big data more accessible, easier to read, and easier to action via labeled metadata that can transform any SME’s future.
Artificial intelligence and Machine Learning are not sci-fi concepts any longer. They are accessible technologies that even the smallest business models can leverage into high-value tools. As a result, they will only become more visible in workplaces around the world.
