Big data and AI need each other
Overview:
To anyone applying AI in any form, the response to the heading above might be “Duh!” That’s an obvious statement to those engrossed at the coalface, but for many others (especially on the client side), they have yet to realize the potential resolution of their data that AI brings.
The IT industry seems to understand AI’s value far more succinctly, and several unicorns have emerged around the globe on the back of AI. While it’s still early days, these companies have brought long yearned for speed or efficiencies to healthcare, transport, robotics, data analytics, and cybersecurity.
It wasn’t so long ago, as any reputable IT company like EC-MSP can confirm, that data was a problem. There was simply too much, and it was standing around like an elephant in the room at many, many corporates. Everyone knew it held a goldmine, but no one seemed to have a tool quick and smart enough to turn it into wearable jewellery.
Put differently, for the longest time it was far easier to accrue data than to sort and monetize it. It’s taken AI to meet data’s volume with the speed and intelligence capable of doing just that. AI is far more than simply sorting through reams of old mailing lists or other client data, of course.
As it evolves, so it disrupts – but it’s cleaning up a lot in its wake.
How AI and Big Data met and fell in love
It’s a simple and obvious truth, but when we understand that the more and better data we feed AI, the better AI gets, it doesn’t take much imagination to see two things become apparent.
One, those stagnant data swamps floating in the cellars of so many companies are soon going to vanish, turned nicely into the value always promised but never extracted by human systems.
Two, we can have no idea where AI will go. To that end, it really is an evolving intelligence. Its DNA is the data we give it, but how exactly it will extrapolate that data into working capital or other valuable resources is still excitingly unknown. Rather, while we can anticipate outcomes, how exactly AI’s appetite for our data will shape our future world is truly unknown.
The intersection at which Big Data meets AI is where unicorns are born. It’s also the crucible of future business intelligence, where analytics will become even more comprehensive and smarter, because of the convergence and symbiosis of data and AI.
Why should you care about their relationship?
The companies that proactively introduce their data to AI will be handsomely rewarded with predictive intelligence, something likely to become a baseline for future business. Without it, you won’t be in business anymore, because it provides a competitive edge that can be merciless on the opposition. This we already know.
By rights, unicorns should never emerge, they shouldn’t manifest, they shouldn’t exist. You would think, since existing business has the market share and all the funds needed to be first in line with future trends, that after the first heady days of mainstream computing decades ago, legacy business would have dominated to the extent that unicorns would have been an unborn fatality of its hegemony.
The very fact that unicorns can emerge, and have emerged lately on the back of AI, points to the tinderbox potential at the interface of AI and big data. Again, it’s also emblematic of just how unknown AI’s potential is. A unicorn must be talking billions in a short space of time.
How is it possible that such a gaping hole in the market can be so meteorically filled by unicorns?
It’s possible, in part, because AI itself is opening new dimensions to old problems, eliminating them in short order and rolling right on to bigger things. It’s not so much that AI is the saviour, resolving persistent issues for legacy business (although it is!), it’s more that AI is able to redefine what business is. Its potential is that great.
To be that comet, to be that world shaker, AI needs lots of data – the more, the merrier.
For many companies, such futuristic ponderings are vague－that they are now able to not only sort and meaningfully store their data but are finally being able to derive the value they deserve from their data – is enough.
While the convergence of AI with Big Data might result in the need for different data preparation, management, and governance protocols, it seems far more likely that their marriage will vastly reduce or eliminate the need for such architecture.
What AI’s appetite for data means for your business
To restate the obvious once more－data is voluminous! Even a medium sized concern is typically swimming in it. Techniques like data visualization, machine learning, and predictive analytics are finally able to drain those data swamps to get at the gold.
Such aspects of AI allow for vastly enhanced decision making, both in terms of the speed and the accuracy of decisions that lead to successful outcomes.
It’s no overstatement to say that such enhanced business intelligence at play is already a marketplace differentiation between competitors, and－you read it here first!－very, very likely to become the largest dividing line between businesses that fade into oblivion, and those that seize the future. It’s a dividing line that will open into an abyss－take heed.
Forecasting can become clinically accurate, and not based on human (usually one) interpretation and “gut feel” anymore, no matter that gut feel will likely still play a big role for some mavericks. Likewise, predicting the behaviors of consumers, industries, and even nation states will experience a far higher accuracy in future, with AI in play.
To date, machine learning specifically has shown its remarkable accuracy in analyzing something as ephemeral as sentiment, and those companies who most accurately know the minds of their customers have an obvious advantage. A huge one, in fact.
Business Intelligence is getting an immense leg up, reporting too is now able to aim for a level of accuracy companies could only dream of in the past, and a more efficient, far less wasteful commercial experience awaits the world now that AI is rolling.
