Over the last few posts, we’ve chatted with Emily He, Senior Vice President of Oracle’s Human Capital Management Cloud Business Group.
In part one, we discussed how artificial intelligence (AI) is humanizing work for Human Resources (HR) professionals and employees, alike. In part two, we looked at how AI is helping to improve the HR space, especially in hiring and recruiting new workers. And today, we’ll look at what to do with all the data your AI systems produce.
Recruiting Daily Advisor (RDA): How do businesses and specifically HR manage and leverage all that data?
Emily He: You are right on the money. Data is going to be hugely important for all organizations and for all HR functions because data is indeed the foundation that powers AI.
AI is going to augment human capabilities by helping us process a huge volume of data and users of the Internet right now generate 2.5 quintillion bytes of data every day on average, according to research cited by Domo. There is no way humans can possibly be able to process this amount of data, but it’s precisely this huge amount of data that makes the machine smarter.
There’s no denying that the AI and machine learning push is dependent on the labeling and synthesis of huge amounts of training data. The more data there is, the smarter the system will become, and the more AI can learn, adapt, and help us with mundane tasks it will recommend actions for us.
In this new era of AI, data is going to be the key to innovation and transformation. You just can’t possibly have enough data. This also means you need to team up with the right business and technology partner to ensure that the data volume can be managed with and that enterprise-ready AI can help you make decisions, and can help you with pattern detection, smarter analysis, and improved decision making.
The other thing is that data doesn’t have to be for enterprise only. The beauty of AI is it can integrate data from different sources. One thing I love about using my iPhone is every morning it tells me when I need to leave to make my first meeting and the way it does that is by taking data from my calendar and from traffic maps and saying, “Hey, the traffic is really bad this morning and you have a meeting at 8:00, so you need to leave 15 minutes earlier because there has been an accident.” Right? That’s super, super useful.
The way the system can do that is by integrating data from different sources. Not only do you need to get really good at managing enterprise data, but you also need to start integrating third-party data to provide more contextual data to help you with decision making. Again, it’s important that you partner with the right technology vendor who is good at managing data as a service.
The other fascinating thing I find with AI, traditionally enterprise software, is that it’s in silos. We have software for HR, we have software for finance, we have software for customer relationship management (CRM)—for our customer experience—but when users start interfacing with a chatbot or conversational for voice user interface (UI) with enterprise systems, they don’t think in a siloed fashion. Right?
In the morning I may wake up and asked my software, “Okay, how many vacation days do I have left because next week my kids are on their spring break and I want to take a few days off?” Then the next question I may have is, “Okay, have my expense reports been approved? Then if I’m a salesperson, the next question may be, “Okay, I’m getting ready to start my day, so what accounts should I be going after today and which customers do I need to call?” These three questions span across three silos: HR systems, finance systems, and CRM systems.
When we start talking about AI, we have to have the ability to pull data from different sources and deliver that seamless experience for the users. This has a new implication on how we manage data and how we can bring all the enterprise data together to deliver the experience our employees want.
The bottom line is that data is hugely important, and companies need to be really, really good at managing data and make data their core competency. Only when they do that, then they have the AI solution that will deliver the business benefits they want.
RDA: Could you share a few use cases or examples of how these emerging technologies are being used in business and HR today?
Emily He: Many of our customers are already experimenting with AI in several areas. One of the first areas that started adopting AI is recruiting. As I mentioned before, the unemployment rate has never been lower, so recruiting remains the top priority for many companies.
They need to attract the right talent, they need to get them on board quickly, and usually, candidate experience is the first exposure people have to your brand, so you want to make sure from the first moment they start looking at job postings, you deliver that experience that reflects your brand.
Quite a few companies are starting to use chatbot technology in their recruiting process. What the chatbot does is it can guide you through the recruiting process in a really personalized way. They’re using chatbots to answer questions the candidates may have, they’re using chatbots to recommend additional opportunities, and they’re also using the chatbot to guide the candidates through the recruiting process, so they know what to expect.
I know our customer, Marriott and Hilton are both using chatbot in their recruiting experience and this is something that I think we’re going to see more often. The other area that HR organizations are utilizing AI technology is in the HR help desk space.
HR help desk is the primary interface between the HR organization and the employees of the company. As employees, we have a lot of questions, whether it’s our benefit packages or maybe it’s the resources we have or management training or maybe I have a sensitive employee situation, so I want to know how to deal with that.
Using chatbots or voice UI allows employees to interact with the help desk in a really human way and provide that human experience. The great thing is with AI, you can integrate demographic data with the HR help desk database. Based on an employee’s age or geographical area, the HR help desk can serve up personalized recommendations on what resources you need to tap into.
HR can provide that truly personalized and engaging experience to the employees. A few areas that our customers are looking into is, for example, personalized learning. That’s a huge opportunity. Continuous performance improvement and continuous learning is a huge topic for many organizations and they want to deliver that personalized set of recommendations to their employees, so they can continuously grow in their current job as well as grow into their next role.
In tomorrow’s post, we’ll wrap up this interview with Emily, and look at what recommendations she has for exploring AI.