Mastering AI for Staffing Agencies - Beyond ChatGPT
Generative AI continues to be the buzzword of the year, but AI hangovers are starting to show up as organizations of all sizes grapple with where the technology can actually be effective in their workflows and start feeling pressure on IT budgets.
When people think of generative AI, they often focus on ChatGPT and similar general-purpose search tools. While these are undoubtedly valuable for assistive tasks like researching unknown topics, planning out travel itineraries, or writing the first draft of creative content, the ways generative AI is and will influence business processes in the staffing industry are much more nuanced.
In 2023, we highlighted ways AI will impact staffing agencies, and our predictions have all come true! Many staffing agencies we’ve spoken with use AI to automate the recruiting process, increase candidate engagement, improve job management, and provide business insights.
Now that we have data from generative AI pilots over the last few years, we have also learned about the dangers of AI, including:
- Non-deterministic outputs. Because generative AI models are trained on massive amounts of language and generate responses by predicting the next word (or token) in a sequence based on a probability distribution, the AI can produce different outputs even when given the same input multiple times. This unpredictability in its results can also make it hard to streamline repetitive processes that require 100% accuracy or that might be damaged in the event of a hallucination.
- Loss of a “human touch”. AI can process massive amounts of data and automate repetitive tasks but lacks emotional intelligence (EQ). While AI recruiting modules can speed up the hiring process by automatically screening candidates, they may miss out on individuals with unique skill sets or potential that isn’t easily quantifiable. Similarly, AI customer service or chatbots cannot build lasting relationships with your end customer.
- Ethical biases. AI systems can inadvertently perpetuate biases in the training data, leading to unfair hiring practices. Without human oversight, these biases can go unchecked, resulting in potential legal and ethical issues for your agency.
- Data privacy. Unless you enter a Zero Data Retention policy with your large language model provider (e.g., OpenAI) or software vendor, they may be free to use your business data to improve their models for other clients. Additionally, sensitive data such as healthcare or payroll data can leak in this model training process, unintentionally showing up for unauthorized users of that data.
We have three key recommendations for preparing your staffing agency for the AI era.
Foster a culture of innovation
Encourage a culture of innovation within your agency. Stay updated on AI trends and technologies, and be open to experimenting with new tools and approaches. Innovation drives growth and keeps your agency competitive.
Focus on data quality
You can only leverage AI effectively if your data is clean and organized. If you feed garbage data into your AI products, you should expect to receive garbage out. And if you think that general AI models will work for your custom business processes, you will be upset. Please invest your time in data cleaning and management to ensure the accuracy and reliability of your datasets. One of the beauties of generative AI is that now you can feed your AI models with unstructured text or images, such as resumes. However, if you feed your AI with lots of noisy data, whether structured or unstructured, the output will have a similar level of noisiness and unpredictability.
Develop a business case for AI tools and monitor their performance
Before you invest in AI products, have a clear idea of the use cases you are interested in deploying and the value they will generate for your business or customers. Regularly monitor and evaluate the performance of your AI tools, and make sure the outcomes AI products drive are beating your initial expectations.
Building business cases around various use cases can also help you identify the low-hanging fruit AI applications and where you can get the biggest bang for your buck.
Are you interested in AI but need help with all the steps needed to implement it effectively in your organization?
We have compiled a simple 10-point checklist to help you effectively implement AI in your organization.
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