Talent management has evolved from static annual reviews to continuous feedback loops and check-ins, and AI has become a huge part of that.
While AI is transforming the skills employees and leaders need to succeed and deliver, it’s also changing how talent is measured.
“AI completely changes the way employees are measured and evaluated,” says Lauren Livak Gilbert, executive director of the Digital Shelf Institute (DSI). “If every employee has the same access to generalized knowledge, then what are you measuring performance on?”
Here’s how AI is changing talent management and how companies can adapt and effectively manage talent in an AI-first environment.
AI Makes Talent Management More Dynamic
Traditionally, performance reviews have taken place at the end of the year. But more organizations are shifting to quarterly reviews, real-time, in-the-moment feedback, and continuous engagement with employees around their goals and career development.
These shifts mean HR teams and managers are wrangling more performance data, and they need a streamlined way to tackle it all.
This is where AI-driven automation is becoming an asset for organizations. It allows them to surface the most meaningful insights faster, have more productive performance conversations, and better align performance metrics with specific business outcomes.
Nearly 40% of organizations are already using AI in performance management, with 44% of this group using it for goal setting and 37% for performance reviews, according to research from Willis Towers Watson (WTW).
AI makes companies less reactive when managing talent. They can use AI-driven predictive analytics to identify skill and learning gaps early on that impact both employee performance and broader company goals.
Talent is a core strategic advantage for companies. Those who want to build or maintain this advantage in today’s business environment have to incorporate AI into performance management to stay competitive.
AI Upskilling Is Now Non-Negotiable
We’re now seeing everyone from government organizations to quick-service restaurants and leading consumer-packaged goods (CPG) companies embed AI into their workflows and business processes.
As we encounter more examples of human-AI collaboration in the workplace, employees will need to increase their AI fluency.
What it means to be AI fluent will vary by organization, but at a baseline, employees will need to understand how to use generative AI (GenAI) tools to enable their work — whether it’s analyzing data, summarizing information, or creating product content.
They’ll need to know how to write effective prompts and how to structure their queries to get the right answers. They’ll also have to learn to use these tools responsibly and assess the quality and truthfulness of their outputs, as hallucinations and false information are two of the biggest risks with AI.
Leadership Should Approach AI Talent Management With Caution
HR teams and leaders will need to develop AI upskilling strategies that factor in the varying levels of digital literacy within their organization, what AI skills are most critical based on role, and how to gauge progress beyond typical metrics like improved productivity.
They’ll also need to craft an AI governance policy anchored around responsible AI principles, such as fairness, transparency, eliminating bias, and human oversight.
AI can’t just be a bolted-on capability. Modern talent management requires companies to be thoughtful about how they incorporate it and harness it as an essential part of how employees work today.
Livak Gilbert cautions organizations to take a balanced approach to integrating AI into talent management.
“As AI takes over for more entry-level tasks, it's important for HR teams to understand how they’ll train the future leaders of their organizations," she says.
AI-First Leadership Is Vital
An AI-enabled workforce also demands AI-first leadership. In today’s workplaces, leaders not only have to spearhead AI implementation but also create an AI-enabled culture that empowers employees to do their best work.
Leaders must develop an AI enablement strategy that marries employee learning, development, and growth with strategic priorities such as profitability, revenue growth, and larger market share.
Mid-level managers, rather than those in the C-suite, likely will play the most critical role in this effort because their positions often thread the needle between tactical and strategic execution.
AI is also changing the nature of their work, with more organizations gradually implementing AI-powered coaching to enable managers to have more effective performance conversations.
Managers and leaders will also need to become AI fluent, modeling for rank-and-file employees how AI skills can advance their careers and help them meaningfully contribute to their organizations.
Effective change management, creating a safe environment for AI experimentation, and being open about AI successes and failures will make or break how successful leaders are in developing an AI-driven culture.
Tips for Integrating AI Into Talent Management
As organizations ramp up their use of AI in talent management, they should redefine performance measurements, increase AI fluency, prioritize governance, and empower their teams.
Redefine How Performance Is Measured
“AI requires HR teams to take a step back and evaluate what performance metrics will drive the behavior they want inside their organizations,” Livak Gilbert says.
Consider incorporating more nuanced data points into business and employee performance metrics, such as:
- Customer service improvements;
- Net promoter scores (NPS);
- Internal mobility and promotion rates; and
- Revenue contribution per employee before and after AI implementation.
Make AI Fluency a Core Competency
Integrate AI training into onboarding, learning and development, and review process.
Create avenues for employees to test and grow their AI skills, whether it’s on-demand webinars, hack-a-thons, or by infusing AI competency into employee rewards and recognition programs.
Prioritize Governance
It’s not enough to teach employees how to use AI; they also need to know when and where to use it.
Leaders must lead the charge in creating a responsible AI policy, one that focuses on transparency and explainability around how AI will and won’t be used in certain work processes, how it will inform performance decisions, how often they’ll audit AI tools, and when a human must be in the loop to make a final decision.
For example, a responsible AI policy for a CPG brand might involve mandating a final human review for quality and accuracy after a team member uses AI to create an Amazon product listing.
Empower Your Team
To develop AI-first leaders, organizations must invest in them.
Frontline employees, especially managers, can serve as AI champions, evangelizing the benefits of AI tools while educating their colleagues about how to use them safely and effectively.
Organizations must first show frontline leadership how AI can improve and streamline their own work, whether it’s helping managers provide better real-time performance feedback using an AI-powered coaching tool or reducing the time they spend on manual processes, like pulling and analyzing data from Amazon, Walmart, and Target, or internal dashboards for the company’s owned channels.
AI’s Role in Modern Talent Management
Data is now integral for goal-setting, performance tracking, and developing effective learning pathways, and AI has become a key enabler of modern talent management.
Once managers understand — and truly feel — the value of AI in their everyday work, they’ll be better positioned to get other employees onboard with the technology, too.
.svg)
