Perhaps the top buzzword dujour is AI, or Artificial Intelligence. The way people talk about AI’s advances, there is a wonderment about how it will replace humans in the workforce, leading executives to really struggle with preparing for a future where we don’t know if our workforce will be an expense under CapEx or OpEx. Before making the determination and getting too far ahead of ourselves, we need to unpack what is really going on in the development of AI and how we’re seeing a lot of confusion between AI and just better data processing.
To illustrate what we’re talking about, Google recently came out with a revision to their sheets product that allows users to ask a question like, “What is my average sales on Tuesdays?” and then delivers an instant response. Instead of a user being made to manipulate the spreadsheet with formulas and functions, the software crunches the numbers based on what’s been asked and presents it’s findings. Effectively, Google has audible-ized a macro command. Yet, the marketing folks and the media is touting this action as AI. The main point is that the software is not assessing the data by itself to intelligently make recommendations on shifts in distribution, positioning, promos or anything else based on what days might be performing better based on those parameters, it’s just spitting back what a human is asking. In this case, it’s most definitely not AI.
So, as the beauty of the fast evolution of technology points to exciting possibilities, the unknown that those future possibilities present and the inability to clearly define exactly what it means leads to lack of clarity and anxiety about what that exciting future means to a business.
Signs are pointing toward machine learning that would assess and absorb repetition to dynamically build algorithms to extract information and present based on the factors that a human might ask of the data, but there needs to be a huge amount of human training that goes into that. Just thinking about how much training would need to go into one company’s set of parameters and triggers is daunting – and most companies don’t act the same way as their competitors. Certainly, there might be vast similarities and assumptions based on industry or production, but learning still needs to take place. It’s just we don’t know how long that will be.
The installations of BRAND OS – focusing on People, Process and Product, with a good dose of technology and innovation running through all of them, places businesses in a strong position by looking at technology advancements and operations holistically. Brand OS allows for the refinement of the now and strong consideration of a future consisting of incredible change.
Illustrating this approach from another perspective that has more to do with evaluation and higher-level decision making rather than production and distribution, there are forecasts that social marketing managers will be effectively phased out by smarter computers and software that can: evaluate the meaning, sentiment, emotion, content, context within posts; then extrapolate how those posts perform based on day- and week-parts of those postings; and, finally calibrate the best proposal for future content, context and implementation of posts. And, while bots are being created that can do efficient jobs of responding to community socially, both of these systems require a high value of intelligence – human or artificial – to complete the social “transaction” most effectively. Who knows when AI will be able to overtake the human element of this equation. At least in the foreseeable future, AI will help managers of social make sounder decisions in their execution, but they will not necessarily take the place of.
Why are we talking about the interplay of human and artificial in relation to the People, Process and Product? Because it’s important to recognize how much of an interplay will take place between humans and technology – even when there is much more automation in the executive and creative ranks. When planning for what your workforce will look like in the future – whether that’s 1, 3, 5, 10 or 15 years – we can’t make the mistake of assuming AI is going to be something it’s not. And, we can’t underestimate the value that AI will give our human resources as it shortens or streamlines processes that bring higher efficiency and better use of expenditure.
Either way you look at it, this is a long play with heavy dependency on agile management, keen decision making, and evolving strategy as the definition of AI in the workplace sharpens and what such automation can actually deliver is measured against what each individual company is looking to achieve. So, regardless of the headlines that might be flashing across the feed, we’ve got time to figure it out – but not time to wait.