AI is now playing a crucial role in the digital transformation of the HR function. We examine what’s driving this trend, key challenges, and the future roadmap for AI deployment.

2019 has been an exciting year for artificial intelligence (AI). From witnessing large-scale adoption across the enterprise to its potential for business transformation coming of maturity – AI, machine learning (ML) and deep learning are already impacting organizations in a big way.

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In a recent roundtable survey, recruiting technology provider, Montage, found that business transformation is the primary reason leading organizations to adopt AI in their HR function. This does not come as a surprise given how prevalent the need for digital transformation is, but it is clear that talent acquisition (TA) leaders are still working out the kinks in their AI strategy. According to the survey, only nine percent of TA leaders say their organization has “an aligned definition of AI, its strategy and approach.”

As HR leaders look to AI to accelerate digital transformation, it is an opportune time to start thinking strategically about AI in the HR. The question driving AI adoption is shifting from how and where to why. What organizational goals do we want to achieve through AI? Why is AI best positioned to help us make better talent decisions?

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As organizations across industries embrace the promise of data-driven decision-making, AI deployment at scale will likely be a high stakes game for survival. But what is keeping TA leaders from exploring the real possibilities of AI in the TA function?

Key Challenges to AI Deployment in HR

For most TA leaders, harnessing AI’s full potential begins tentatively with explorations of select TA opportunities and a few potential use cases. Kurt Heikkinen, President and CEO at Montage believes organizations are comfortable with AI informing their hiring decisions but aren’t comfortable with AI making those decisions. He says, “AI is being evaluated at every stage of the talent acquisition (TA) process, but TA leaders are pursuing with cautious optimism. Our own research has found that organizations are more comfortable deploying AI to inform hiring decisions, not make them. In order to feel comfortable deploying AI, organizations need to have confidence in the data and science behind the algorithms and assurance that candidates will accept it. Our research has found that candidates don’t regard AI favorably in every aspect of hiring. For instance, recent Montage research found that 94 percent of candidates do not feel comfortable being evaluated with AI-enabled facial recognition technology during the hiring process.”

However, as AI becomes commonplace across candidates’ own consumer lives (think Siri, Alexa, and Google Home), they’ve come to expect the same level of personalization from their workplace as well. “With the new realities of the talent market, talent acquisition leaders are under pressure to provide digital, consumer-like hiring interactions for all candidates. But consumer AI has developed faster than AI hiring applications – meaning that though candidates do prefer some digital interactions in hiring, they’re still not comfortable with machines making hiring decisions, posing a challenge to hiring teams looking to leverage AI during the recruiting process,” says Kurt.

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One of the other major concerns around AI in recruitment has been its tendency to amplify human bias when fed with historical data sets. Without the right checks and balances in place, AI could end up doing more harm than good in the HR function. “When done right, AI can help provide more opportunity to reach and recruit more diverse groups of candidates. However, many problems occur when putting AI technology into place to help hiring teams overcome unconscious bias. If machines are not trained properly to overcome bias and discrimination, or the underlying data they are trained on represents bias, AI and hiring algorithms will further reinforce the very issues they are hoping to address in the hiring process. As a result, when leveraged incorrectly, this technology can be detrimental to an organization’s hiring practices, diversity and inclusion efforts, and employer brand,” says Kurt.

“Because of this, we have a long road ahead of us until unconscious bias and discrimination are completely eliminated. Companies should take a cautious approach to implementing AI and ensure that the technology is proven and validated before putting it into practice. Not all AI recruiting technologies have evolved to the same point, so talent acquisition leaders need to take a critical look at the track record for specific AI technologies before making them part of their hiring processes. To help overcome bias, talent acquisition teams can implement tactics like consistent questions via text-based interviews and software that forces hiring managers to assess candidates solely on the content of their responses,” he adds.

Performing regular audits of the training datasets can help AI vendors and TA leaders identify and eliminate biased predictions/outputs. Isolating factors that can cause an adverse impact in the predictions of an AI-model is key to successful AI deployment in the HR function.

Accelerating Digital Transformation with AI in HR

When starting your AI deployment journey, it is crucial that you clearly map out your pain points in talent acquisition and the expected business outcomes. AI in HR is yet to reach maturity, however, AI technologies available in the market today are suited well to take on high-volume, repetitive tasks and create value for organizations taking a strategic approach to AI deployment. The possibility of leapfrogging our productivity fuels AI adoption across organizations. And as of now, that should certainly be the core objective of any AI strategy within the HR function.

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“My best advice for organizations looking to create an AI deployment strategy within their talent acquisition functions is to take a cautious approach to adoption. AI in talent acquisition hasn’t reached marketplace acceptance yet. To access the benefits of recruiting technologies and improve their candidate experience, talent acquisition leaders should choose a solution that’s specific to the issues they’re trying to solve in their hiring processes and inform candidates ahead of time that they will be interacting with AI technology during the recruiting process.

“Lastly, know what matters most to candidates. First, map your entire hiring experience and determine which interactions matter most to candidates. Next, determine how much expertise, time and effort is required to perform each task. Focus your recruiters on the intelligent, valued interactions and implement AI to administer the time-consuming administrative steps. You will drive greater recruiter productivity, hiring manager satisfaction and the better candidate experience.

“Hiring is a high-stakes decision for both candidates and employers. By taking a careful approach to AI, talent acquisition leaders can find the right balance of technology and the human touch in hiring,” says Kurt.


AI’s role in HR is growing as intelligent tools and strategies are standardized. While it is true that in the coming years, AI will not only augment human performance but also automate some operational and business processes entirely, we’re still a long way from there. Now it is time for HR and TA leaders to fundamentally rethink the way humans and smart machines interact within the world of work, and what they can achieve together in the AI-driven organization of the future.