How AI Will Affect HR

Todd Downing

The future is now. Generative AI (Artificial Intelligence), which can create new content and perform many job functions, continues evolving in every industry. We’re fortunate that a smart group of horticulture professionals is helping educate people on utilizing AI in production, marketing, sales, IT, accounting and even customer service.

What about AI’s possibilities to enhance Human Resource departments? This is a complex question, as the bridging of AI with human interaction can be concerning. Human Resources is about people and where’s the tipping point between using a computer to manage human interaction before we dehumanize the process?
 

The current and near-future application of AI in Human Resources borrows from similar efficiencies AI is supporting in other departments. Most notably in creating and generating communication, such as: 

• Job descriptions that translate industry language and create job postings to have a wider impact
• Marketing content that better portrays the positives of your company culture and why you’re an employer of choice
• Interview questions based on specific job descriptions, which will save interviewers time and increase the relevance of the question

AI also can improve data analysis and analytics by:

• Identifying trends in employee retention
• Determining ROI for specific investments in headcount, HR Information Systems or other HR initiatives or software expenditures
• Forecasting HR budget

 It can increase efficiency and productivity of HR professionals via:

• Applicant tracking
• Overall task automation of repeated transactional HR responsibilities
• Project management, including employee training and the onboarding process
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AI applications unique to Human Resources are where the balance between human interaction and AI remains conflicting. Of note, increasing the accuracy and speed in identifying and hiring candidates. In theory, we use a job description and skill set keywords. AI is regenerative. Thus, the process of “teaching” the AI software what the right keywords are for a specific job will get better and more accurate. However, this becomes dependent on the resumes or social media bios to include these. Having read thousands of resumes, it’s impossible to note all the meaningful responsibilities, expertise or achievements on paper. Thus, how many candidates are still not found? An experienced horticulture industry professional, whether HR or hiring manager, will have the intuition to read enough in a resume to set up a conversation where the missing elements can be assessed in communication.

Several global companies utilize specific AI bots to conduct the first interview with candidates. While time saving is apparent in doing so, this is an application of AI that’s polarizing. AI will help with employee professional development with its ability to answer what career path a professional’s current skills and experiences may lead to. It can identify what additional training or education will help that professional progress forward.
Human Resource professionals in other industries are lauding the positive impact on the performance review and engagement process. Please note AI is NOT being used to determine a person’s performance assessment. This will always require human judgment, empathy and the right interpersonal communication. While better suited again for larger organizations, AI will compile performance data faster so that the manager can make human decisions more accurately and quickly.
 

Passive candidates are professionals who aren’t looking at a career change. Here’s why AI isn’t cutting it:

• Relationships STILL matter: Passive candidates respond to people they trust within their network or contacts that exhibits that the person reaching out knows what they do, their industry and has common connections. These professionals will only respond to a genuine conversation, not an AI-generated message.
• No emotional connection: AI cannot provide empathy or have a real conversation about someone’s goals and concern. That’s where recruiters shine—listening, understanding and building trust.
• Personalized communication and tone: AI is great for sending out mass, generic or more transactional communication. Passive candidates, though, will only respond when the message meets them where they are. The tone of communication matters. Be “real” and write in your own words. Many smart people have shared they can quickly identify AI-generated communication versus what was individually written by a person.
   

1. Use AI for research, not outreach. Let AI help you gather insights, but keep outreach personal.
2. Build long-term relationships. Communication that’s authentic in getting to know their career goals is critical. Follow up with them, share industry-related information that relates to what they do and acknowledge their achievements.
3. Be discreet. Make confidentiality a priority and be clear about it.
4. Keep it “real.” Be available to answer questions and offer guidance. Show you care about their career long term.
5. It’s about them—not you. Customize your communication to match their skills and goals. Make it about them, not just the job.
    

What are the risks associated with utilizing AI in the hiring process and managing individuals? A recent LinkedIn survey provides insight into how candidates and employees view the use of AI.

Overall, 19% of respondents reported that they “Mostly trust” AI-driven decisions and 7% indicated that they “Completely trust” these decisions. A significant proportion, 43%, remained neutral on the subject. Meanwhile, 23% expressed that they “Trust a little” and 8% reported that they “Do not trust at all” the accuracy of AI-driven decision-making in hiring.

• Hiring bias: Inputting the data of a perfect candidate, especially when replicating a current strong performer, historical job description or a subset of top employees lends itself to hiring the same demographic, same thinking and same background individual. Diversity in skills, thoughts and backgrounds is critical to company growth. Companies could find this counter to their efforts.
• Ability to assess for behaviors: Is an AI bot capable of the proper human interaction to make a decision that considers human soft skills? Picture yourself as a candidate being interviewed by an AI bot— how well do you think you would interview and how would this leave you feeling about that company?
• HR compliance: Human Resources regulations and laws are constantly evolving at the federal, state and municipal levels. How AI is utilized in hiring and helping HR manage employees will have to be considered, and rushing into its use without properly inputting AI data to account for compliance will lead to issues. For example, currently nine states and six major cities have enacted Pay Transparency Laws in the hiring process and internally with employees, with more coming sooner than later. AI is not capable of providing accurate data on Human Resource regulations and laws currently.
• Intellectual property and confidentiality protection: Although AI can generate content closely resembling human output, it is not human. And since intellectual property (IP) in the U.S. focuses explicitly on non-physical creations or assets made by humans, AI presents a major challenge for legal disputes over patents and IP ownership, namely who owns AI-generated content.
   

1. Discrimination laws. Wherever AI is a factor in employment decisions, there’s also exposure to employment discrimination. If there’s a statistically significant disparity in decisions involving AI, the potential for a disparate impact claim under Title VII or other statutes are at risk.
2. Other employment law. AI can be used to test integrity. However, such uses may trigger exposure under the law, which limits using lie detector tests for pre-employment screening or during employment.
3. AI can be used to measure individual employee productivity or activity to determine if an employee is working properly and/or achieving individual KPIs. These systems may send real-time alerts to employers upon detecting that an employee is not “working” and thus tempt employers to use those records to limit pay, which may lead to wage and hour violations. AI state-specific laws. As of the end of 2024, 113 state bills have been enacted into law, covering areas such as high-risk AI uses, digital replicas, deepfakes and government AI applications. More laws are anticipated in 2025. GO HERE to see states with enacted AI legislation.
    

Overcome the fear of AI replacing human jobs by beginning to play with and explore AI being the solution to how it can eliminate mundane HR tasks they don’t want to do to improve efficiency and job satisfaction. HR leaders will continue to play an influential role in how we keep the emphasis on humans in Human Resources. Get out in front of the right HR application of AI and be the steward of your employees’ careers and company culture.
While generative AI will continue its progress in being utilized by Human Resources in the horticulture industry, it’ll never replace the HUMAN in Human Resources. At the end of the day, professionals want to work for an authentic company. Employees will stay and flourish at companies with a positive interpersonal culture, and companies emphasizing human interaction will continue to be the most successful. GT 

Todd Downing (tdowning@bhcagroup.com) is a Managing Partner for BEST Human Capital Advisory Group and leads the Horticulture & Green Industry executive search and advisory services. He has more than 30 years of experience in the industry and a passion for supporting its continued professional growth.
 

Best Practices for HR Teams Using AI

• Geography: Be aware of your state and municipal laws.
• Risk financing: Employers will want contractual protection from their AI vendors. Ideally, indemnity, but at the very least representations that can be reliably enforced. And, if there’s EPLI or other insurance, what’s covered?
• Cost-benefit assessment: There’s a risk in AI from both AI-specific statutes and general employment statutes, but also rewards. For each AI use in HR, there will need to be a considered judgment of whether the rewards are concrete and exceed the risks.
• Diligence: Vet outside vendors to ensure that they’ve adopted certified procedures designed to promote non-discriminatory outputs.
• Customization: Explore whether AI vendors (or your own programmers) can customize AI programs to focus on a limited number of non-discriminatory candidate characteristics that matter most to your organization.
• Anticipation: Anticipate the need for and incorporate processes for accommodating candidates with disabilities or other special needs.
• Vigilance: Running the numbers on a RIF is now the standard operating procedure. The same should be done with AI assessments. Early notice of problems permits correcting small problems before those become immense. Testing also ensures that qualified candidates aren’t unintentionally excluded. Continue to test after implementation.