Denis asks, “Are there new skillsets that marketing leadership should be hiring based on the impact of AI will have?”
The answer to this question is contingent on the types of AI solutions your company will be deploying. Broadly speaking, you’ll be needing to identify efficiencies for AI to automate, increasing complex human work like true innovation, leadership, domain expertise, and creativity, and inspecting and tuning the outcomes of AI.
The skillsets required would include strong data analysis capabilities, machine learning expertise, and the soft skills around innovation, leadership, domain expertise, and creativity. The latter will be the hardest, because it requires experienced recruiters and HR staff, as well as hiring managers, to be able to understand innovation and creativity.
What you won’t be hiring for are repetitive tasks and repetitive work. If it’s repetitive, AI will do it, so those roles will be smaller in number.
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
- Got a question for You Ask, I’ll Answer? Submit it here!
- Subscribe to my weekly newsletter for more useful marketing tips.
- Find older episodes of You Ask, I Answer on my YouTube channel.
- Need help with your company’s data and analytics? Let me know!
- Join my free Slack group for marketers interested in analytics!
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today’s episode, Dennis asks, Are there new skill sets that marketing leadership shouldn’t be hiring for, based on the impact that AI will have? Yes, the answer to this question is contingent on the types of AI that your company will be deploying. For example, if you’re just going to do something very limited, like, I don’t know, put up a chat bot, then you might want somebody who has a natural language processing experience. For example, if you’re going to be building your own chatbot, from scratch, but broadly speaking, you’re going to need to identify the efficiencies for AI to automate. So that’s going to be one type of person you’re going to want to be able to hire. Those are people who are good at process management, project management, Product Manager, management, Business Process automation, and about whole soup of acronyms that goes with that total quality management, Six Sigma, you name it, that’s, that’s going to be one bucket of people, people who can help you decide what problems you want to solve with artificial intelligence. The second group of people you’re going to need are people who can help you increase the quality and the quantity of complex human work. So that will be things like interpersonal relationship management, true innovation, people who can actually innovate, there are, there are a lot of people who use the word innovative, very few people who actually are very few people who can create something new, that didn’t exist before. Another area where you will need more people rather than less is going to be around leadership. Again, there are a lot of people who claim the word leader, there are not a very many people who actually are leaders. And of course, creativity. This is an area where you will need more people who are truly an actually creative. Again, a lot of people use the word, not a lot of people can do it. The third group of people you’re going to need are people who can inspect and tune the outcomes of AI, it will be sometime before AI can be just given a pile of data and and come up with good answers that require relatively little to no cleaning up front, or improving on the backend iterating improving on the backend. In fact, there’s an entire branch of AI right now called active learning, which has a human in the loop sooner. So for example, if you’re trying to classify customer service inquiries, and the machine knows it can do I was a positive inquiry that was a negative or unhappy inquiry. And then there’s probabilities between those those two ranges. Active Learning allows the machine to raise his hand soon and say, Hey, I don’t know what to do with this one. This might be sarcasm, it might be might be someone who’s happy and unhappy at the same time, what do I do? And so active learning involves people with subject matter expertise to help to and the machine. That is probably the last area I would say in one that encompasses or stretches across all these, which is domain expertise. There is going to be a tremendous call for people with greater and greater domain expertise in their industries. What do you know about your industry where the tips, the tricks, the hidden things, if you’ve got, you know, a little more gray hair rather than less? What have you learned that can be used to help tune and codify the results that people are getting? That is so powerful, and so absent? And a lot of machine learning work? A lot of the problems that we see happening with AI and machine learning right now is you have statisticians who can build a theoretical model, you have coders who can turn into code. But in a lot of cases, there isn’t someone of domain expertise to Satan. That’s not how that works. A real simple example would be, you could have somebody say in food science. And the coders, the statisticians are saying, well, these foods clustered together most of these.
And the coders codify that and no one’s saying, folks, you got to put, you always got to put salt on tomatoes. Because the food science person, the food expert knows that tomatoes contain a natural form of glue tannic acid, which when you add salt to it forms a, a natural, MSG is right tomatoes always tastes better with salt. But a coder and a statistician would not know that only a domain expert would know that. So that’s an example where you need people who have domain expertise, whatever it is, your company does, to provide those little tweaks that make things so much better. Now, in terms of skill sets, you’re hiring for strong data analysis capabilities across the board, that is going to be required for pretty much everyone, as time goes on being able to look at a data file that goes into a machine or look at the machines output and say, yes, that’s good, or no, that’s not good. Machine learning expertise, you’ll be hiring for some of that people who can tune the machines built them. Not everyone has to do that. But you do need a few people who can really get under the hood and make this the systems and software work. And then again, you’re going to be hiring for innovation, for leadership, for creativity, and for domain expertise. This last category, those soft skills, for the most part, and domain expertise is more of a hard skill. It’s going to be so hard. That’s the part where you will make or break your company your outcomes. Because as someone who used to be a recruiter, having someone used to be a hiring manager, identifying skills like innovation, and leadership and creativity are extremely difficult. Everyone says they are. How do you test for that? How do you discern that how to even test for whether a person is going to be a good fit into your company. One, one hiring trick I remember from the old days was to ask somebody describe their accomplishments of their last company. And if if they use words that were almost exclusively about that, well, I did this and I did this and I had a team, but I did this, that person’s probably not a good team player. Right? As opposed to, I did this and I work with the team. And here’s how I supported the team. Or here’s how the team supported me, or in this result is this was a group effort. And here is my role in this. This Africa, here’s what I did to help this effort come to fruition, but understanding that there was a lot more to what that effort was than just what the just what the one person the individual contributor did. Now, the one thing you won’t be hiring for repetitive tasks, and roles that are largely repetitive, if it is repetitive a machine is going to do it. And what you’ll see happen is those tasks will go away first. And then as those tasks go away, you will see the number of people needed in that role to get smaller and smaller. So for example, I used to work in the public relations industry. And there was one type of role that was largest copying and pasting all day long, that’s going away, right, that role is not needed in any capacity. Because the machine can do that you don’t even need to do that. You can just use regular programming to take that work and make it better and faster and cheaper with machinery. So look at the roles in your organization, if is 7585 95% repetitive work, that the tasks that role will do will will go to machines. And then the role will simply consolidate and diminish and eventually for some roles absolutely will go away. If someone’s job, for example, is literally nothing more than getting coffee for somebody else. That role is probably going to go away because as companies get more productive and get better at measuring productivity, they’ll see that that’s not generating business impact. So lots to unpack here about the skill sets that marketing leadership should be looking for, but it really boils down to data capabilities, soft skills, and domain expertise. If you have any follow on comments, please leave them in the comments box below. And of course, please subscribe to the YouTube channel and the newsletter. I’ll talk to you soon. want help solving your company’s data analytics and digital marketing problems. This is trust insights.ai today and let us know how we can help you
You might also enjoy:
- How To Start Your Public Speaking Career
- Retiring Old Email Marketing Strategies
- Is Social Listening Useful?
- What Content Marketing Analytics Really Measures
- What Is The Difference Between Analysis and Insight?
Want to read more like this from Christopher Penn? Get updates here:
Get your copy of AI For Marketers