HR’s Slow Adoption of AI: Is Mindset causing Missed Opportunities?
This article explores the reasons behind why the HR function have been slow to adopt AI, and the path forwards in order to leverage it's benefits.
Introduction
Our data from the 2024 Tucker Stone Survey brings forward an interesting, yet surprising, trend: 50% of organisations are not using AI in their HR functions. This figure is identical to last year's survey, signalling that no significant adoption of AI in HR has taken place over the past 12 months. It raises important questions about HR’s readiness, and willingness, to fully embrace AI-driven innovation.
Why Has AI Adoption in HR Stalled?
In many industries, AI is at the forefront of digital transformation, enabling businesses to automate processes, enhance decision-making, and create personalised customer experiences. So why hasn’t HR, a function so crucial to organisational success, followed suit at the same pace? We explored several possible explanations:
Perceived complexity and skills gaps
One of the most significant barriers to AI adoption in HR is the lack of technical expertise. AI technologies, particularly those that involve machine learning, predictive analytics, or natural language processing, can seem daunting for HR professionals who may not have a background in data science or technology. For many organisations, the challenge lies in building the necessary infrastructure and acquiring the right talent to integrate AI solutions effectively. HR leaders may recognise the value of AI but feel ill-equipped to manage its implementation and ongoing use.
Hesitancy over trust and employee experience
HR’s core focus has always been people. There’s often a fear that integrating AI into HR processes will depersonalise the function. This concern is particularly relevant when it comes to highly sensitive areas like performance management, talent acquisition, and employee engagement, where human intuition and empathy is crucial.
HR leaders also worry about trust issues. They fear employees may be uncomfortable with AI-driven decisions, and that these technologies could introduce bias, invade their privacy, or reduce their control over career-related processes.
Privacy concerns and potential bias
AI thrives on data, and the HR function deal with vast amounts of sensitive employee data, from compensation details to performance records. The integration of AI into HR systems involves using this data to inform decision-making processes, which raises data privacy concerns.
There are other major concerns about the fairness of AI algorithms when it comes to potential bias (as mentioned above), and the ethical implications of AI. AI systems learn from historical data and if that data contains biases, such as racial, gender or age biases, there are concerns with using AI in decision-making processes particularly when it comes to hiring, promotions, and performance management. Navigating these concerns requires not only technical solutions but also a robust governance framework that many organisations are still in the process of developing.
Cost vs ROI
For many HR leaders, the adoption of AI requires a substantial initial investment in technology, training, and change management. While larger organisations may have the budget and resources to experiment with AI solutions, smaller companies may see the cost as prohibitive.
Without investment, HR functions will struggle to quantify the direct impact of AI on core HR metrics such as employee engagement, retention, and productivity, this makes the ROI uncertain and with unclear evidence of the tangible benefits, decision-makers may be hesitant to allocate budget toward such technologies.
It might be that HR leaders want to see more widespread success stories or proven outcomes before committing their budget to AI investments, preferring to focus on more traditional, cost-effective solutions that have an immediate and measurable impact.
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Generic and misaligned solutions
Many organisations may have explored AI solutions that don’t directly align with their specific HR needs. AI has the potential to revolutionise areas like talent acquisition, employee engagement, and performance management, but if the chosen AI tools are not designed to solve the unique challenges of an organisation, the adoption will naturally stall.
This misalignment may arise when organisations adopt generic AI tools that are not tailored to the intricacies of HR. For AI to be effectively used in HR, it needs to be purpose-built for the nuances of people management and integrate seamlessly with existing HR technologies such as HRIS or performance management systems. Failure to find the right fit between technology and organisational needs can result in AI solutions that are underutilised, further dampening enthusiasm for broader adoption.
Organisational inertia
The tendency to stick to familiar processes can be a major barrier to AI adoption and this resistance can manifest at multiple levels: HR professionals themselves – may be sceptical about the role of AI in what is a people-centric function; Senior leadership – may be unfamiliar with how AI can enhance HR outcomes, could also hesitate to push for adoption, and; Employees – may fear the implications of AI, worrying that automation will replace jobs or reduce their ability to engage meaningfully with HR processes.
Change management is the key challenge here, as clearly understood from our survey, with 50% of organisations stating that fostering innovation and navigating change are key challenges facing their business right now. Convincing stakeholders across the organisation: HR teams, executives, and employees, of the benefits of AI, requires a significant shift in mindset, that needs to be driven by clear communication, pilot projects, and demonstrable successes.
The Path Forward for AI in HR
Most of us are aware of the potential benefits of AI in HR, in areas such as talent acquisition, performance management, learning and development, as well as employee engagement. Given this knowledge, it’s essential to understand why organisations are not seizing the opportunity to integrate it into HR functions. Today’s conversation needs to focus on how organisations can start to overcome the barriers to AI adoption highlighted above.
We explored key practical solutions that can help to change mindsets:
Education and experimentation
Many HR professionals remain unaware of the full capabilities of AI or how it can be applied in a people-centric way. To overcome this, there is a need for more education and training within HR teams on AI’s potential to augment, rather than replace, human judgment. HR leaders should be encouraged to experiment with smaller AI projects to build confidence in its effectiveness.
Bridging the Skill Gap
Organisations need to invest in upskilling their HR teams in AI literacy. Partnering with IT and data analytics departments or hiring HR tech specialists can also accelerate the learning curve. Additionally, there is an opportunity to implement AI solutions that do not require deep technical expertise, such as no-code platforms, which can empower HR teams to deploy AI with minimal complexity.
Privacy & potential bias concerns
The responsible use of AI in HR requires a solid framework for data governance and ethics. This involves setting up clear policies on data usage, ensuring transparency in AI-driven decisions, and regularly auditing AI systems for biases. By addressing these concerns head-on, organisations can build trust in AI applications while safeguarding employee privacy.
In a world where businesses continue to navigate an ever-evolving workforce, the pressure to transform HR operations will only increase. AI has the potential to transform HR from an operational support function to a strategic powerhouse that drives business outcomes. Those who embrace AI thoughtfully will be better positioned to drive strategic value and create more efficient, data-driven and agile HR functions that can adapt to the future of work.
We want to hear from HR leaders who are actively using AI – how have you overcome the macro and micro challenges in adopting AI?