AI Deployment Essentials: 5 Key Factors to Consider

2024 is the year AI at work gets real…

…according to Microsoft and LinkedIn's recent 2024 Work Trend Index Annual Report. I couldn’t agree more as I’ve been getting a lot of questions from TA leaders on how to deploy AI in the workplace.

We’ve heard time and time again over the past year that AI is no longer a futuristic concept, it’s now a practical technology that’s driving efficiency. For hiring teams looking to stay competitive and not fall behind, implementing AI has become essential. 

For those that are still investigating and considering applying AI, knowing where to start can be daunting.

Believe it or not, I have 10+ years of experience working with AI. I know you’re all thinking, “AI hasn’t been around that long!”. But it sure has - all the way back to my days at IBM and working with the Watson team. So, in this month’s blog, I wanted to offer some practical advice on the 5 key things you should be thinking about and the questions you should be asking as you begin to deploy AI tools across your organization.

1.) Assess Your Needs & Objectives

I can’t emphasize this one enough, and that’s why it's #1. You don’t just “want AI”. You want to solve problems, and AI might be able to solve them better than before. Those problems might be as simple as wanting AI to give you more time in the day and speed up some tasks for you or it might be a more complex problem you’re working through. It’s critical to understand the specific needs and objectives of your talent organization first. Ask yourself…

  • What problems are we trying to solve? 
  • Which processes can be optimized or automated? 
  • Can AI help you solve that problem in a better way?
  • How do we implement AI in the right way?

I’ve seen a lot of talent teams state that they simply want to use AI, but you have to know the problems you’re trying to solve for first.

2.) Choose the Right AI Tools

Evaluating the technical proficiency of any tech vendor is essential. This helps determine how well their AI performs its intended function compared to human benchmarks. Questions to ask…

  • What steps do you take to ensure the AI system’s predictions or outputs are reliable and consistent? 
  • Can you explain the methodology behind your AI’s decision-making process? 
  • Can you provide examples of real-world scenarios where your AI outperforms other solutions or human experts? 
  • How do you define and identify biases in your AI’s outputs? 
  • What steps have you taken to ensure that users can quickly learn how to use your platform? 

If the vendor you’re evaluating can’t confidently answer these questions, then I’d be cautious as to whether they have the right processes developed into their systems to provide you with an accurate view on risk.

3.) Pilot & Iterate

Before rolling out any application of AI, I’d recommend starting with a pilot project that relates to one of the major problems you’re looking to solve. Are you looking to fix inefficiencies within your interview process? Or maybe looking to automate the many repetitive tasks in recruitment like resume screening or scheduling interviews?

Having a pilot plan with a smaller sample group allows you to test AI applications in a controlled environment, gather feedback, measure performance, and identify and address any issues or limitations. This way you can use insights from the pilot to refine your approach before broader implementation.

4.) Foster A Culture of AI Adoption

For AI to have a positive effect on the workplace, employees must embrace its potential. To foster a culture of AI adoption, you should…

  • Communicate the objectives and benefits of assessing whether AI can help you progress yourself or your projects 
  • Provide training and resources to build AI literacy 
  • Encourage open dialogue to address concerns or misconceptions 
  • Highlight early success to build momentum and buy-in 

When employees understand and embrace AI, they can better leverage its capabilities, leading to enhanced productivity and efficiency across the company.

5.) Monitor, Evaluate, & Optimize

Seems like a no brainer, right? But you’ll be surprised how many organizations forget that AI deployment is an ongoing process. If you’re not continuously evaluating how AI applications are impacting the business, you won’t be able to maintain the relevance and effectiveness of the solutions over time. You can do this by…

  • Identifying success metrics 
  • Tracking data quality 
  • Regularly conducting performance audits 
  • Collecting feedback from end-users 
  • Reporting findings 
  • Refining the process to improve performance

Monitoring, evaluating, and optimizing AI systems are vital to ensure they remain accurate, fair, secure, compliant and continuously improve to meet user and business needs. 


A few weeks ago, we had Matt Alder, host of The Recruiting Future Podcast, join us for a webinar. He mentioned how noisy the AI tech space is right now. He also reiterated the importance of cutting through all of the noise and ensuring the AI tools you select are actually doing something. This warning couldn’t be more accurate.

Hopefully the above provides some advice on how to think about leveraging AI. Remember that AI is not just a technology, but a strategic enabler. With thoughtful planning and execution, you can harness its power to help solve the biggest problems you’re facing now and to help you perform more efficiently in your day-to-day. If I can be of any help to you as you navigate this process, please feel free to shoot me a DM here.

Until next month,

Mark Simpson
CEO & Founder 

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