The Case for AI
"THE VELOCITY OF NEW DATA FLOWING THROUGH EVERY BUSINESS UNIT PROVIDES ANALYSTS THE CHANCE TO MEASURE THE COMPANY'S PULSE."
And companies that don't take advantage of this, are likely to be left behind by the competition. To put it in perspective, AI can be applied in areas that every business should be concerned with, such as HR and productivity. Technology can help identify collaborators, top performers versus weak, as well as employee motivation, thus leading to decisions on how to improve productivity. In marketing, quick decisions need to be made on campaign spend, and ROIs need to be tracked and achieved. A company might employ various tools to measure these and collate data on. But no one person will be able to handle that on their own, and this is where AI steps in to help.
With technology such as AI available today, there's just no excuse not to find a tool that suits the business. There are several types of data that are suitable for AI transition:
- High velocity data
- Fragmented data sitting in many platforms or systems
- Raw data that needs to be cleaned and analyzed
- Anything real-time
AI has the potential to look at businesses through a different lens and enable a new type of decision capability. Many may ask what does the journey to decision automation look like? It's a breeze actually, once you get started. What's the difference? Unlike humans which may take any out of 6 different paths to decision making, AI takes only one, and quickly goes through the 3-step process of gathering insights, giving recommendations and then decisions. It is able to handle extractions of large amounts of data, then run it through data cleansing, add context, and harmonization, in order to deliver it on a plate for you for decisions to be made. In other words, AI can help you find the best and most comfortable tees, jeans, grey and blue suits for your wardrobe, so all you have to do is just pick one suitable for the occasion.
So what's next? Decisions as a Service?
Maybe. Regardless the path to evolution, it won't be one winner takes all, it will be a network of apps that provide specialist functions working together through an API driven sharing ecosystem. Eventually, we'll see algorithms talking to other algorithms, negotiating between themselves without humans, much like Facebook's AI that created their own language to "talk" to each other. How will this business model work? Most probably through pay-per-decision / performance, with differentiators in the quality, accountability, and speed. The question is also not IF when it happens, but when it happens, where will your business be placed? As a top adopter, or way down the line behind your competitors?
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