The phrase ‘artificial intelligence’ is an evocative one. Perhaps, for you, it conjures images of automated technology supporting a leisure-filled life for redundant humans, or maybe it represents exciting leaps forward in fields such as space travel or cancer treatment. If you have a particularly overactive imagination, it could trigger visions of killer robots battling it out in some dystopian future; the phrase means different things to different people.
But what about business insight and intelligence? Where does AI fit into this puzzle?
In 2017, we are seeing increasing numbers of businesses experimenting with AI as they seek to develop a better understanding of their own companies and of the markets around them. For some, the experiments have been so successful that AI is being hailed as the future of insight.
Could it be that the age of Big Data is over? Is it possible that AI could be the next step in the progression towards more profound understanding?
AI vs. Big Data
Let’s not get ahead of ourselves. It certainly isn’t time to be throwing away all of our stored data and dismantling any data management structures. However, AI certainly represents a threat to the traditional routes of gaining insight via Big Data analysis and forecasting.
The reason for this is margin for error. Even with the highest quality datasets, the margin for error when it comes to forecasting future market movements and interactions is still rather high. Big Data is incredibly accurate when we set out to understand what is happening or has happened, and obviously this knowledge is vital as we look forward, but it is not so useful in making direct future predictions.
It is this ‘failing’ of Big Data which could leave the door open to an alternative method. I put the word ‘failing’ in quotes because it is not a failing in a traditional sense, but more of a shortcoming – you can’t collect data on an event which has not yet taken place, after all.
Through artificial intelligence, analysts hope to model the specific conditions and factors which will affect the market in the future. This model can then be examined, giving businesses a more accurate picture of what will happen in the coming months, years, or even decades. Of course, such AI is still data-driven, and works to build upon a platform of empirical understanding, but if it can be implemented successfully, AI goes several steps further than our contemporary data analysis techniques ever could.
AI In Action
In 2016, Japanese insurance company, Fukoku Life announced redundancies for 34 of its employees. This is not pleasant news, of course, but neither is it particularly shocking; corporate restructuring, for better or worse, happens all the time.
However, this announcement from Fukoku represents the beginnings of something that people in this country have been dreading for many years; the replacement of human workers by intelligent machines.
The company have instead opted to use an AI system designed by IBM. One of the duties of the system will be to handle the company’s business intelligence endeavors, taking care of analytic duties that would have relied solely upon manual Big Data interpretation up until very recently. Now forecasts will be made via AI modeling and prediction.
Developing the Next Stages of BI
Of course, in effect, AI is not replacing Big Data analysis at all. Without data to feed into the artificially intelligent systems, there is nothing for the system to act upon; there is nothing for it to learn. The system can eventually understand which datasets it needs to make certain calculations, and then actively search for those itself, but there needs to be a base level for it to build from. This base level is provided by existing Big Data structures.
However, it does represent a paradigm shift. Up until now, Business Intelligence has been about developing ways to store, manage and then interpret large data stores and diverse data sources. With the advent of AI, the focus will instead be on designing the most powerful artificially intelligent systems to gain the most accurate forecasting and the most detailed analysis.
It will be in the construction and development of these systems that the most exciting BI innovation occurs.
One industry figure who has already been sold on AI is Zeus Kerravala of ZK Research. For him, the benefits of AI in providing direct business insight are obvious;
“There’s no question that A.I. systems, like IBM’s Watson, can analyze and interpret data faster and more accurately than people,” he said. “We are in the digital era, where the currency of business is speed, and A.I.s can make decisions faster than people with massive amounts of data.”
The idea of ‘massive amounts of data’ is an important one. We are already far beyond the tipping point and find ourselves basically swamped by data. There is simply no way to process or manage this without a degree of artificial intelligence. This means we have to incorporate AI into our business intelligence strategies; there is just no other option.
However, not everyone agrees that AI will usurp traditional Big Data analytics so completely. Writing for the Harvard Business Review, Walter Swap and Dorothy Leonard discussed the IBM Watson supercomputer used by Fukoku Life. They explained how the system was easily able to defeat master quiz competitors and handle mind-boggling calculations with incredible speed, but fell down in other areas.
Swap and Leonard outlined how the cognitive functions associated with a human brain are still far beyond the capabilities of AI. This means that tasks like “weigh[ing] recommendations, recogniz[ing] patterns from past experience, and mak[ing] the final decision” still need to be handled in the traditional way, with computer systems handling the heavy-lifting number-crunching tasks.
So, the jury is out on just where AI is at the moment. What is clear, however, is that this is a developing field, and one which will come on in leaps and bounds in the not-too-distant future. Don’t start accusing your toaster of stealing your job just yet, but it is safe to say that AI is the future of business insight.
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