AMS defines three key steps to successfully operationalizing AI

AMS

As organizations continue to navigate the challenges of a tight labor market in a rapidly evolving digital landscape, artificial intelligence (AI) has emerged as a powerful tool for helping to reach candidates faster, improve decision-making and broaden the talent pool from which to hire. However, as AI becomes increasingly integrated into talent solutions, there are persistent myths about operationalizing the technology. The latest “Exploding Digital Myths” chapter from global talent solutions business AMS has revealed the three key steps to successfully integrating AI into existing talent strategies.

  • Step One: Implement a change management program. Bringing new AI into the business isn’t just an operational change. There are a number of stakeholders to bring on the journey to streamline integration and build AI fluency from legal and compliance colleagues to IT departments and DEI practitioners. Successful integration depends on an effective change management program which considers a broad scope of workstreams from regulation and data security to re-skilling and bespoke training.
  • Step Two: Define a clear purpose. AI will deliver a significant increase in data points. To ensure talent partners don’t get lost in a sea of information, it’s critical to identify specific objectives and outcomes that are relevant to business objectives. Knowing which AI integration will work, how the interface will be designed and what impact this will have on resourcing teams is crucial.
  • Step Three: Communicate transparently. The future is a mix of tech and touch but the fear of AI in workforces is largely driven by the unknown. Being transparent around why and how the technology is being utilized and clear about the value it brings to every stakeholder – including employees – drives adoption. This means being open and honest about implementation, addressing concerns and communicating in a clear and accessible way.

Erica Titchener, Global Head of Technology and Analytics at AMS comments: “We’ve been privileged over the last five years to work with clients who have been on the journey of introducing AI into their organizations. It’s not just about learning how to use a new system; it’s also critical to help teams improve their analytical skills so they can use AI and the increased insights it delivers to support decision making.”

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