AI and Technology
AI in HR: CRF’s Seven Key Principles
The AI buzz is loud, exciting and all around us. Everyone, it seems, is AI curious. Huge claims are made. There are astounding examples of what it can do. The urge to try it, to adopt it, to just give it a go is just unstoppable. And understandable.
Yet, at the same time, there is also need for caution – or at least some careful and critical thinking. The adoption of any new technology requires the same caution. Why? Of course, that technology may indeed turn out to be extremely relevant and important for some purposes and in some contexts. But, on the other hand, it may turn out to be irrelevant, unimportant and even unhelpful or a waste of time for other purposes in other contexts.
In other words, the question is not whether or not we should use AI but, rather when, why and how it should be used.
Broadly speaking, AI can be used both to accelerate or automate existing processes and to discover novel activities and processes which are only possible with AI.
But, however we choose to use AI in HR, it is absolutely vital that our work is always focused on helping the business achieve its objectives. In other words, we should use AI only when we have taken steps to ensure it is adding value to the organisation.
How can we make this happen?
CRF has devised seven key principles to help us do exactly this.
Principle 1: Start with value
Align every AI use case with strategic objectives. Identify a specific contribution HR can make to organisational performance and how AI will be used to help drive business performance. AI only has value if it actually adds value to the organisation.
Principle 2: Diagnose before you prescribe
Accurately define the business problem or the business opportunity. Adopt an Evidence-Based HR approach and use relevant and trustworthy evidence from multiple sources to understand both the causes and potential solutions. What matters most is whether we have actually solved the problem and not whether the solution uses AI. Choose the most effective intervention: This may, or may not, involve AI.
Principle 3: Evaluate before you automate
Before making an HR process faster through automation, we must first establish whether that process is itself necessary, effective, and helps drive a valuable business outcome. Speeding up a poor process just produces poorer outcomes more quickly. If the process is low-value remove it or redesign it so it does add value before automating.
Principle 4: Experiment with purpose
Explore but also ensure that every experiment addresses a specific and important question, specifies what success means, has bounded scope, a named owner, and appropriate safeguards. Define what AI will and will not do. Test it with users and share what you learn. Scale what works. Adapt or stop what does not. Be alert for unintended negative consequences.
Principle 5: Use any time saved to do better work
Freeing up time simply does not, in itself, add any value. Identify in advance specifically how released capacity will be used to actually help the business. Use the new extra time to, for example, make more-informed decisions, develop a stronger focus on business objectives or obtain deeper workforce insights. And ensure people are equipped and have the resources to do such higher-value work.
Principle 6: Retain judgement. Develop people.
Use AI to strengthen, not replace, human thinking. Avoid cognitive surrender. Ensure people continue to learn, think critically, question outputs, and retain meaningful oversight and accountability. Apply safeguards proportionate to the potential impact of AI so that it is used fairly, transparently, securely and with respect for privacy. People affected by AI should understand its role and be able to participate in decisions that affect them.
Principle 7: Define success before you start
State clearly what specifically should improve, for whom or in what way, compared with what and by when. Focus on identifying and measuring important business outcomes – not just AI usage or time saved. Establish a baseline, identify future measurement points and what you hope to see at those points. Review both intended benefits and unintended costs.
Following these seven key principles will greatly increase the probability that our use of AI will actually add value and significantly reduce the chances of wasting resources.
We don’t have a choice about whether or not to use AI in HR.
But we do have a choice about whether or not we do so wisely.
Upcoming Webinar:
AI in HR Series: Where does AI really create value?
Thursday 17 September | 12:00–13:00 BST / 13:00–14:00 CEST | Online
Find out more and register
Prof. Rob Briner (Associate Research Director, CRF) and Johannes Sundlo (Founder, Prorio AI, and Course Director, AI in HR, CRF) will explore how HR can move past the hype and make sharper decisions about where AI genuinely creates value – and discuss the Seven Principles in more depth.
Coming Soon: CRF’s AI in HR Series
This webinar is part of the CRF AI in HR Series which is built on a simple premise: the hardest part of AI in HR isn’t the technology, it’s knowing where to use it and how to create value.
HR’s role is not to become the AI expert, but to help the organisation make better decisions about work, people and capability.
Across four parts, the series focuses on creating value with AI, enhancing individual productivity and judgement, enabling line manager effectiveness and redesigning work and capability. It brings together live webinars, on-demand learning, cohort-based programmes, hackathons, practical research and articles to help HR teams move from AI curiosity to AI capability.
