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AI in HR:  CRF’s Seven Key Principles

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 ju

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