You Just Got Told ‘We are Going to do AI,’ Now What?
We are 11 days into 2024, and I think it’s fair to say that the AI tech race in the HR technology and analytics space is heating up. I hear more and more conversations in HR around “We are going to do AI,” “We need to start on AI,” etc. Here’s the thing: modern civilization is pretty much embedded in AI at this stage (read: there isn’t a person sitting behind all the traffic data and re-route options inside your phone’s navigation tool of choice). We are experiencing AI's commercialization and consumerization—the tech isn’t new.
So, if you are a business or HR leader and reading this, please understand that the words “let’s do AI” in my HR Tech brain sound a whole lot like “let’s do green.” Most of the time, the response is going to be, “ok…and what exactly do you want to do with it?” (Occasionally done with a look of confusion as if you just sprouted antlers if I am not managing my poker face well that day)
Now, if you are currently working in the HR tech or analytics space and have recently been on the receiving end of the “let’s do AI,” don’t panic because I think I have figured out a process that will take you from that statement to evaluating solutions to possibly implementing something. Here we go:
Step 1: Breathe. Don’t Overanalyze.
I don’t know why, but it appears to me that sometimes the corporate human brain is wired to receive new ideas, panic about how complex it may be to assess and evaluate the viability of new ideas, get overwhelmed in under three seconds by the imaginary workload, and default to rejection. Don’t do that—especially if you have been asked to look at possible AI solutions or applications.
Realistically speaking, AI isn’t going away anytime soon (and probably not ever). The sooner you can find an opportunity to brush up on the applicability of AI in your everyday work, the easier it is for you to adapt to future processes and tech changes down the road. Not to mention, it’s also a great skill to have from an employability perspective.
Now, the hardest part is over; move on to Step 2. Yes, I am serious; this will probably be the hardest step for most organizations on their AI journey.
Step 2: Figure Out Your High-Ticket Challenges for 2024
Step 2 kicks off the easy part of this process because you probably had to do this anyway when you put in your budget request for the upcoming fiscal year. This step is no different than how you would have evaluated where to invest your resources in 2024. The critical question here is: what will be the one thing that will take 20% of the budget but solve 80% of the business’ challenges (conceptually, actual numbers will vary)?
I typically categorize my challenges into People, Process, and Technology buckets. From an AI adoption perspective, the challenges predominantly caused by process-related issues are my favorite candidates to evaluate for possible AI solutions. Because let’s face it, nobody likes to change how they do things daily unless it is to eliminate the activity. Tech-related issues are my second choice. Depending on the challenge, sometimes they can be good candidates for AI tools. But suppose the challenges touch too many peripheral technologies or integrations or have confidential/secure data associated with them. In that case, getting approvals for an AI solution and having a clear path for implementation can get a bit too complicated.
Step 3: Determine How Much You Are Willing to Spend to Solve the Challenge
You’re not buying a 4-wheel drive vehicle on a bicycle budget. Let’s get that one out of the way before we proceed further. Tech configurations are expensive, training the data models behind the AI-enabled tools is costly, and someone has to pay for all of that.
You don’t necessarily need a specific amount for this step, but at least get a sense from your organization on a ballpark number they feel comfortable spending to try and resolve the challenge. I’ve been part of conversations where the tech solution would cost $200K+, but the scale of the organization can only afford a ~$75K solution. It would have been more economical to hire someone to solve the problem instead of implementing tech.
This scenario happens more often than you think. Depending on the circumstances of your organization, AI tech might not be the right solution for you in the short term. There are other things you can do in the meantime to prepare your organization for the future adoption of AI; see #5 here
Step 4: Evaluate the Organizational Sentiment Toward AI
Adopting and implementing HR tech depends on the HR team and the organization’s sentiment and trust towards the technology. Sidebar: I firmly believe in active and passive ONA, but I also think the technology is underutilized/avoided in organizations because without truly understanding it, it could feel like someone is always watching over all worker activities.
While AI is all over mainstream media lately, it is still very much a divisive topic in certain rooms and organizations, depending on the demographic composition of your leadership team and the experiences of your stakeholders with AI and new technology in general. Understanding your organization’s sentiment towards AI will significantly help you assess the time and effort it may take you to socialize the technology, undergo IT security reviews, and have the contract vetted for signature.
Step 5: Create a Proof of Concept or Pilot Plan
You should test the solution before you commit and roll it out more broadly. Like any HR tech implementations, you will plan and test for 120% of the scenarios only to find at go-live that you missed 5% somewhere somehow. Especially with AI being a newer concept in the world of workplace technology, it will very likely take more time to understand, tweak, and adapt the solution for your organization.
Step 6 (BONUS): Find Your Bestie in IT
No matter how experienced you may be in HR tech or AI for HR, it is unlikely that HR will be able to embark on the AI journey alone. So, find your best friend/sponsor in your IT organization and move forward as one front. You’ll probably find socializing concepts and getting buy-in a lot easier.