In an effort to wrap our heads around a rapidly emerging technology that will change the face of global business and the workforce (and other small feats), Rebel recently attended the Global Artificial Intelligence Conference in Boston, MA. Approaching artificial intelligence (AI) strategically will make a difference between making a profit and wasting time and resources.

Fundamentals

Merriam-Webster defines artificial intelligence as the following: “A branch of computer science dealing with the simulation of intelligent behavior in computers…” We interpret this as follows: AI takes a set of outside inputs and provides predictive modeling to forecast and determine the outputs — constantly refining as it learns.

As speaker Vinay Seth Mohta, director of Manifold asked: “What are you trying to model and what are you trying to determine at the end-state? What opportunities are worth tackling? What are you going to do differently with results in hand?”

AI Shaping Business and Society

AI can be used as an organizer of data and analysis. And when properly applied and deployed, AI is a game changer. These systems provide speed to gather and digest significant amounts of information and analyze it in ways that aren’t humanly possible without it. (Speed of learning drives innovation and competitive advantage.) However, AI needs context for better decisions to be made. As an example, stated by conference speaker, Joe Barkai, “AI will change radiologists, but it won’t replace radiologists.” So, AI will allow us to make better decisions versus taking time to gather and analyze data that machine learning can do more efficiently and effectively.

Press play to watch Rebel’s VP of Marketing Strategy, Craig Wilson, speak about how businesses must embrace big data to gain a competitive advantage.

AI must be used thoughtfully and responsibly. There is a danger of profiling, for example, based on statistics that skew ethnic populations and zip codes that can have higher crime rates, which can affect insurance rates and loan application status, as examples. So, context is important because bias can flaw decisions.

Another area of focus must be data quality. Ask yourself the following questions:

  • Are you following the 80/20 Rule? 80% of the process needs to be focused on data cleansing while the other 20% needs to be focused on data modeling.
  • Who owns the data and who governs it?
  • Is there bias in the data ownership and governance?

Business Implications for Marketing

Ok, that was a lot to digest and you may be searching for a place to begin. For starters we recommend some questions to consider. Do you have:

  • Clients/prospects who have a complex problem, challenge or opportunity to solve?
  • The sheer volume of data to analyze for the situation overwhelming without computing?
  • Partnerships with AI firms that can provide support for your efforts with clients?
  • A vetting process to determine that AI companies are best suited for marketing and sales applications?
  • The resources within your agency and commitment from its leadership to follow through on AI approaches?

This is an exciting — albeit dizzying — time to be in marketing. How we navigate for the future will determine who will best position themselves in this dynamic marketplace.

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