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Seedlink Blog

5 Myths of AI in HR

Seedlink Nov 21, 2019 1:44:22 AM | 7 min read time

5 myths of AI in HR

Photo by Alexander Sinn on Unsplash

The human resources industry has changed rapidly over the past decade, transitioning from administrative tasks to focusing more on strategic decisions. The application of artificial intelligence tools have been playing a large part in this transformation. 

Discussions about AI has produced many myths and misconceptions. Some think that AI will eventually take over the world, while others think that it’s just a new tech buzzword. The truth is somewhere in-between. Regardless, it is important to fully understand how AI can create value for businesses and where it cannot. Here are some AI myths and misconceptions in the realm of HR. 

 

1. AI is just for techies

As AI in HR is still a relatively new concept, it may seem complicated and hard to use for those who aren’t familiar with it, especially for HR practitioners who aren’t usually trained in technology. While HR might not typically be known for being data confident, it does not mean that they cannot engage in the AI tech conversation.

These sophisticated AI-based HR solutions are usually meant to solve key pain-points and be user friendly. Training will still be needed to know how to properly operate and utilise the solution but it will not require AI expertise. In fact, getting started with AI usually involves making sure that your HR team is already tracking commonly used HR metrics, such as:

1. Time-to-hire
2. % of regretted losses
3. Staff retention rates
4. New-hire retention rates
5. Probation pass rates
6. Job candidate drop-off rates
7. Job seeker satisfaction
8. Promotion rates
9. Average cost to recruit new candidates
10. Key performance indicators for existing staff and new-hires

With these metrics, AI can help with defining areas of HR that you want to optimise and even bring new insights such as engagement rates and the correlation of certain competencies to success. Familiarity with AI begins with things you already know.

A key insight from IBM’s research report, “The Business Case for AI in HR” mentions that “you do not need AI expertise but rather an analytical approach, the desire to understand how technology works and how to use it effectively.”  

 

2. AI eliminates the need for HR.

The future of HR is both digital and human. AI will continue playing an increasingly important role in HR. However, it is meant to transform HR departments, not to make them redundant.  

Many HR tasks can be automated, replacing more operational and process-oriented functions. This means that HR is free to do more strategic work, such as focusing on enhancing employee experience, coaching and development, creating more personalized onboarding experiences, etc.

These are important things that require a human touch – which is something that AI may not be able to handle in the near future.

 

“The blend of key soft skills, such as human empathy and judgement, together with the powerful analytical and predictive capabilities of AI, is a recipe for success in HR, driving more insightful, human-centric work now and in the future.”-  Clare Barclay, CEO of Microsoft UK

 

This is a powerful summary of HR in the Future of Work. Humans & machines will work together to augment each other’s capabilities for superior decision making and efficiency.

Computers can find patterns in highly unstructured data and can process large amounts of information quickly. Humans on the other hand are very good at drawing conclusions from vague premises. We can use data to solve problems, and we’re able to find nuance where machines can’t.

Together, people and machines will pave the way for smarter, faster recruiting in the future of work for example.

HR is not the only function that is impacted by the advancements in AI as other departments are undergoing their own digital transformation.

As the people responsible for recruiting and training the workforce of tomorrow, HR professionals play an important role in ensuring the success of their organization's digital transformation journey. 

 

3. AI is too expensive. It just increases business costs without tangible benefits.

At face value, HR AI tech does seem expensive to adopt, especially since most of its benefits could only be seen through long term investment. But it is still important to keep in mind that that AI solutions can actually be more cost-effective compared to existing solutions and at times, help to boost revenue.

Talent Acquisition is an area where HR AI tech is often used, from reducing human bias in the screening process, to increasing candidate assessment efficiency. Along with numerous man-hours, countless company dollars are being spent on old-fashion recruitment.

A 2016 Society of Human Resource Management survey found that "the average cost-per-hire is $4,129". For companies with large intakes, they would be spending a hefty sum on recruitment costs alone in a single year.

There, adopting an AI recruitment solution can be more cost-effective by reducing cost-per-hire and freeing up HR to deal with other matters. AI talent management programs can also help companies measure the ROI on talent as well, tracking their progress throughout their career journey.

Certain kinds of predictive AI have the ability to boost revenue if used to assess for roles that specifically help in revenue generation. This is one way to transform HR from a cost center, to a profit center.

4. AI can automatically solve all of HR’s pain points. 

AI may seem omnipotent, but it is only capable of performing incredible things within specific boundaries. Some forms of AI may seem like they have human intelligence, but it would be unrealistic to think that the current AI is equivalent to the human mind.

For example, image recognition technology may be more accurate than most humans, but it is useless when it comes to maths problems. AI in its current form can be exceedingly good at one task, but once the parameters change, it will most likely fail. 

This applies to most HR AI tech as well. Benefits of AI in HR are plenty – ranging from enhancing candidate experience for a more efficient and effective recruitment, to helping with development and retention of existing employees.

However, most HR AI tech will solve for a certain pain point that it is programmed for, but not all of it. For business leaders and HR professionals, it is an important point for consideration when choosing your AI strategy.

It is good to understand what is the exact pain points to be solved, and then choose the AI solution to fit into your strategy.

 

5. AI as a solution has yet to mature. There’s no rush to adopt AI immediately.

Research has shown that early adopters of AI with strong digital capabilities appear to have higher profit gains. The performance gap between them and laggards are expected to widen as well, with early-movers using their profits from AI adoption to invest in additional AI applications.

So, what other benefits are there to adopting AI as soon as possible? There are two key arguments, both of which point to the fact that laggards will never be able to catch up.

Simply put, integrating AI takes time. AI is not a ready-made product. For it to reach its maximum potential, time is needed to customize and configure the solution to suit specific business needs.

When adopting AI, it is common to start with small pilot projects. From there, it has to be integrated into existing systems. While rewarding, the transition from project to full integration takes effort and can be time-consuming. There are also human challenges involved as employees will need to learn how to interact with these technologies.

Secondly, because AI has the ability to learn and evolve, the continued accumulation of data over-time creates a barrier for slow adopters to catch up.

If you have been using your AI solution for 5 years, your AI machines will have 5 years’ worth of hiring data. This means that your organization can potentially predict for leadership potential and long-term retention rates as you are able to track employees throughout their career journey in the company.

Your competitors who are late adopters will not be able to do so, simply because their AI machines will lack the required historical data.

Early adopters have access to this data that laggards do not, creating an even bigger divide between those who adopt early and adopt late. 

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Topics: Industry 4.0, Future of Work, HR Tech, Artificial Intelligence