Considering that generative AI was heavily popularised by the release of ChatGPT less than two years ago, this high level of uptake is encouraging. 

With that said, HR departments are currently using this technology predominantly for non-strategic tasks. With the speed of its development, AI is poised to become a key driver in HR’s strategic decision-making, helping to predict trends, improve workforce planning and enhance the employee experience.

Now that many HR practitioners have a good understanding of AI tools and how to use them, it’s time to connect this ‘red’ skill to HR’s ‘blue’ skills. For example, we know that CEOs have ambitious growth agendas for 2025 and many will see AI as a key driver of that. 

However, it’s important to note that while AI will likely contribute to portions of that growth agenda, it cannot be done without people. As HRM recently covered, it’s important for your workforce to feel included in your AI-fuelled growth plans, which is an approach that HR leaders can champion.

Current approach: AI is primarily used for automating repetitive tasks such as scheduling interviews, screening resumes or tracking attendance. Its value is in streamlining low-value processes.

Purple approach: AI will support HR in strategic areas, such as predicting employee turnover, personalising learning and development plans and using AI-driven insights to improve talent management. 

2. Integrating data across functions 

Emerging technologies are giving HR access to more data than ever before, creating the conditions for more dynamic and strategic talent management. 

With that said, according to Philip Gibbs, Founding Partner of Agile HR Analytics, reaping these gains requires a thoughtful and well-rounded approach.

“Partners are getting very excited about these great technology solutions out there. But what I would [ask] is, when you bring that in, what are you going to feed it? How are you collecting HR information? Where is that data stored and captured? [And] how are you enhancing and curating that information?” said Gibbs during a session at AHRI’s National Convention and Exhibition in August.

Employee data should feed into every facet of business strategy, he explains, meaning that HR’s role is to democratise this information rather than keeping it locked in an HRIS.

Even more important is the need to collect and analyse data in collaboration with other business functions, such as tech and finance, to create a nuanced understanding of organisational health.

When communicating with other functions or leaders about employee data, HR practitioners will need to leverage their communication skills and business acumen to get cut-through.

“Data needs to be extracted from your transactional systems where it’s being entered, and then it needs to be reshaped [and] recoded to make it manageable and easier to understand,” he says.

“It’s about understanding who your key stakeholders are within the businesses. What do they care about? What are their priorities? That’s [what] we should be emphasising [with our data].”

Current approach: HR data is often used for basic tracking of performance reviews or payroll processes. There is often little communication between HR and other departments regarding data collection or usage.

Purple approach: HR professionals will use data from multiple sources – such as employee feedback and external labour market trends – and will correlate their data with other departments to create a comprehensive view of the workforce. 

Data integration should also support collaboration between HR, IT and finance in particular, ensuring that all key business decisions are made with full visibility into both human and operational metrics.

3. Moving from descriptive to predictive analytics

The rise of AI has expanded the potential of people analytics as a driver of strategic decision-making. Its capabilities have evolved from basic reporting to predictive insights that help businesses anticipate future trends. 

However, Gibbs notes that many organisations have yet to embrace this potential. 

“[Currently], less than 15 per cent of organisations are leveraging predictive analytics to look at more strategic [activities],” he says.

“We really struggle to get beyond what’s called descriptive analytics, which is [things like] snapshots of often very historic data – looking at what has happened, versus actually leveraging predictive and descriptive analytics to really help you think about what might be coming up.”

Learn how to incorporate business strategy into your workforce planning and mitigate future risk with AHRI’s Advanced Workforce Planning short course.

The solution to this could lie in  implementing systems that allow for real-time monitoring and insight, enabling HR to anticipate and respond promptly to changes in the business landscape.

To ensure you are getting the most out of your analytics, Gibbs suggests ensuring that people data is considered within the context of business and technical trends, and vice versa.

“When analytics is conducted in isolation with technical research, it often misses the mark….  it’s really important to overlay that context,” he says.

Current approach: Analytics in HR focuses on historical data and simple metrics like recruitment efficiency or employee satisfaction scores. Reports are static and typically reviewed after the fact.

Purple approach: HR will use predictive analytics to forecast future trends, such as which employees are likely to leave or what skill gaps may emerge in the future. Considering a more complex range of data will allow HR to make proactive decisions and improve talent retention, workforce planning and leadership development. 

By integrating data, aligning AI with business goals and adopting predictive analytics, HR practitioners can play an active role in accelerating HR’s shift from a support function into a strategic partner. 

HR’s ability to be the ‘purple people’ who can bridge the divide between business needs and technological solutions will cement its value in the AI-driven future, closely embedding human insight into decision-making for a more well-rounded HR function.