The development of artificial intelligence (AI) and machine learning is no longer an abstract, futuristic concept or technology. Even today, AI is reinventing the way we do business, especially for smaller companies.
Tighter budgets and less experienced staff often mean small and medium businesses (SMB) lag behind larger companies when it comes to areas such as Big Data analytics. However, merging AI capabilities into analytical software avoids many of the restraints holding back SMB, and provides actionable solutions to compete with much larger competitors.
How AI helps SMBs
For example, take IBM’s Watson Analytics. Big Blue’s program relies on the prowess of Watson, a cognitive computing system that comes with natural language processing, hypothesis generation and evaluation, dynamic learning and the ability to defeat two of the greatest Jeopardy champions of all time. How can all these features help SMBs? For one, Watson allows its users to ask questions in plain English, which the system can then translate into data language for querying. Also, because it’s a cloud service, there’s no need for SMBs to worry about investing in expensive infrastructure.
Most smaller companies don’t have experienced IT technicians and data scientists familiar with the language required for proper data analysis. Having an AI feature allows employees to voice questions as they would normally talk, and even allows for simple-to-understand responses, as opposed to overly technical insights. The ability to understand a program is key to its functionality, and AI shortens the learning curve allowing organizations to get to work faster.
AI works for sales and marketing
Watson represents a change in the way we do business, and opens the doors to an evolving B2B environment. AI is ushering in an era of personalized, automated engagement, which has numerous advantages for many business functions, such as sales and marketing.
Engaging, nurturing and following-up with leads is a tiresome, time-consuming effort. What’s worse, so much time is wasted on slow responders and less-interested prospects when it could be devoted to more important customers. This is where an AI-based application and automatic engagement serve a real purpose.
AI systems could manage the endless phone calls and email tagging for slower leads, or those showing small incentives to purchase. With a system handling these situations, it frees up time to focus efforts on more responsive, higher quality customer service. Instead of going out and having to increase staff in order to chase more leads and improve availability, companies could use these automated systems at a fraction of the price.
AI improves supply chain
Supply chain management tools are beginning to be infused with AI capabilities, which will help programs react quicker, make better choices, and learn from their mistakes. For the moment, supply chain tools are good at analyzing familiar data, but can’t handle unknowns or new variables. However, AI technology is dynamic, adaptable and reactive. It can be built to work with databases not only belonging to the company, but others around the world. Now, without constant human oversight, these programs can recognize changes in important variables, like transportation costs or commodity prices, and make changes in order to remain productive and profitable.
Unfortunately, too many decisions are made too late. We see something happen, and then we act. This era of Big Data and predictive analytics allows our machines to anticipate an action, and make changes early to minimize risks and damage. AI can analyze business conditions with historical ones and forecast what’s most likely to happen. However, if a mistake is made, the system will learn from it and incorporate it into any future analyses.
What’s the future of AI?
Any attempt to predict how AI will evolve over the coming years is a fool’s errand, because every new discovery leads to countless possibilities. What we do know is that AI won’t remain restricted to just improving sales and organizational supply chain.
Already we see its availability to everyday users with announcements like Microsoft combining AI with Windows. Experts are also exploring other possibilities, like using AI to improve network security, law enforcement and robotics. The important takeaway is that the combination of Big Data and AI will allow for rapid decisions that don’t require constant human oversight, improving both efficiency and productivity.
Flickr photo via Creative Commons
