It seems as if everywhere you turn, someone’s referencing AI. “Artificial intelligence is essential for business,” states a news article. “AI is the only way forward,” insists a colleague. And the scariest of all: “If you don’t implement AI quickly, you’ll be left in your competitors’ dust.” The constant refrain of AI, AI, AI can leave you feeling like your organization has lost the race before it has even entered it.
The truth is, AI is changing the world at a remarkable pace. And, eventually, nearly every industry and business will benefit from it. “Whether you work in retail, banking, transport or the public sector, AI will be an integral part of the way you do business in the future as it has huge potential to improve decision-making, increase efficiency and power new ways of working,” states the article How to Get Your Business AI-Ready.
But that doesn’t mean AI is the best solution for your organization right now. Implementing AI takes a massive commitment in the form of time, resources, and money. It requires a critical mass of data and properly trained staff. By prematurely jumping into a high-profile AI program, you risk ignoring the valuable tools already available and stalling other strategic projects underway. Instead, a more practical approach—one that uses software scaled to your operations—will move the most important metrics now, while developing an analytics culture that will make AI more feasible down the road.
AI has become a buzzword. What exactly does it mean?
In its prolific use, the meaning of artificial intelligence has become skewed. Some have come to view it as a magical solution capable of instantly transforming business all on its own. Others equate it with automation. Neither of these is true, however. AI requires much preparation and strategy (more on that later), and where automation follows pre-programmed rules, AI involves machine learning. AI is designed to mimic human thinking by making predictions and adjusting its processes based on new data insights. In this way, AI is quite different from many previous technological revolutions, during which technology took over specific, static roles within processes.