I’m thrilled to sit down with Marco Gaietti, a veteran in the field of business management with decades of experience in management consulting. Marco’s expertise spans strategic management, operations, and customer relations, making him the perfect person to dive into the evolving role of AI in HR and the broader workplace trends shaping 2025. In this conversation, we explore how AI is being integrated into HR processes, the shifting perceptions of what AI means in organizations, the financial hurdles to adoption, and the growing strategic importance of HR in the eyes of top executives. Let’s get started.
How are HR departments currently leveraging AI, and in which specific areas are you seeing the most significant adoption?
AI is making its way into HR in some really practical ways. Right now, we’re seeing the most traction in areas like talent acquisition, particularly with resume screening and candidate matching, where AI can quickly sift through huge volumes of data. It’s also being used in employee engagement through chatbots that handle routine queries about benefits or policies, freeing up HR staff for more complex tasks. Another big area is learning and development—AI tools are personalizing training programs based on individual needs. These applications are gaining ground because they deliver clear efficiency gains, which is a big driver for adoption.
Why do you think there’s such a wide gap between HR professionals using AI tools personally and organizations formally investing in them?
I think it comes down to a mix of experimentation and budget constraints. Many HR professionals are exploring AI on their own—think free or low-cost tools to draft emails or analyze data—because it’s accessible and helps them get work done faster. But when it comes to formal investment, organizations are cautious. There’s a hesitancy to commit to pricey subscriptions or enterprise-wide solutions without a rock-solid case for return on investment. Plus, there’s often a disconnect between individual use and aligning those tools with broader company processes or security standards.
How is the personal use of AI by HR staff influencing the push for broader, formal implementation within companies?
Personal use is acting as a kind of grassroots movement. When HR professionals see firsthand how AI can streamline their workload, they become advocates for wider adoption. They’re showing their teams and leadership tangible benefits—like faster data analysis or better candidate sourcing—which builds a case from the ground up. However, it’s not always a straight path to formal implementation. Sometimes, this personal experimentation highlights risks, like data privacy concerns, that slow down the process until proper governance is in place.
Can you break down what generative or agentic AI capabilities look like in an HR setting, and how they differ from older definitions of AI?
Generative and agentic AI are a step beyond traditional machine learning or predictive analytics. In HR, generative AI might mean creating tailored job descriptions or personalized employee feedback based on minimal input, essentially producing new content rather than just analyzing data. Agentic AI goes further—it acts autonomously, like a virtual HR assistant that not only answers employee questions but also anticipates needs, schedules meetings, or flags potential turnover risks without being prompted. This is different from older AI, which mainly focused on patterns and predictions, like forecasting hiring needs based on past trends.
What’s behind the trend of organizational teams, rather than vendors, redefining what AI means in the workplace?
Organizational teams are driving this shift because they’re on the front lines of implementation and see what actually works in their specific context. Vendors often push a one-size-fits-all narrative about AI, but internal teams—HR, IT, and operations—know their pain points and are redefining AI to match their real needs, like focusing on tools that can create or act independently. They’re less impressed by buzzwords and more focused on practical outcomes, which is why they’re taking the lead in setting the bar for what counts as true AI.
How has this evolving perception of AI changed the way HR evaluates and selects tools or solutions?
This shift has made HR much pickier. They’re no longer just looking for tools that crunch numbers or predict outcomes; they want solutions that can create, adapt, and act with minimal human input. For example, they’re evaluating whether a tool can generate unique training content or proactively solve employee issues. This means vendors have to demonstrate more advanced capabilities, and HR is asking tougher questions about integration, scalability, and whether the tool truly aligns with their strategic goals rather than just being a shiny add-on.
For larger companies, cost has become a major barrier to AI adoption. What specific expenses are they grappling with most?
Larger organizations, especially those with over 5,000 employees, are wrestling with a few key costs. First, there’s the upfront investment in software licenses or subscriptions, which can be steep for enterprise-grade AI tools. Then, there’s the cost of integration—tying these tools into existing HR systems often requires custom work or IT support, which adds up. Training staff to use the technology effectively is another big expense, as is ensuring compliance with data privacy laws, which sometimes means hiring consultants or legal experts. These combined costs can make AI feel like a risky bet, even for big players.
With so many organizations resistant to paying extra for AI features, what strategies could vendors use to make these tools more appealing or affordable to HR departments?
Vendors need to rethink their approach. One way is to offer tiered pricing models—start with a basic, low-cost version that delivers clear value, then let companies scale up as they see results. Another strategy is bundling AI features into existing HR software at no extra charge, at least initially, to lower the barrier to entry. Vendors could also focus on proving ROI upfront through pilot programs or case studies tailored to HR challenges, showing exactly how the tool saves time or money. Building trust through transparency about costs and benefits would go a long way.
What kind of return on investment would it take to convince more organizations to invest in AI capabilities for HR?
Organizations need to see hard numbers that justify the spend. For HR, that often means measurable efficiency gains—like cutting recruitment time by a significant percentage or reducing administrative workload by, say, 20 hours a week per staff member. Cost savings in areas like benefits administration or compliance could also be a big draw. Beyond dollars and cents, they’d want proof of improved outcomes, such as higher employee satisfaction scores or better retention rates. If AI can demonstrably move the needle on these metrics within a short timeframe, say six months to a year, more companies would be willing to open their wallets.
There’s been a notable increase in how CEOs and board members view HR’s strategic importance. What do you think has fueled this change over the past year?
I believe this shift comes from a growing recognition of HR’s role in navigating uncertainty, especially after recent global challenges. CEOs and boards have seen HR manage unpredictable resources—whether it’s talent shortages, remote work transitions, or employee well-being concerns—with a level of expertise that other departments, like IT, are just starting to appreciate. HR’s ability to adapt and keep the workforce aligned with business goals during turbulent times has elevated its status. Plus, as data-driven decisions become critical, HR’s insights into people analytics are proving invaluable at the executive level.
Looking ahead, what is your forecast for the role of AI in HR over the next few years?
I think we’re on the cusp of a major transformation. Over the next few years, AI in HR will move beyond efficiency tools to become a core strategic partner. We’ll see more advanced generative and agentic capabilities—think AI that not only automates tasks but also offers insights and solutions proactively, like predicting cultural fit for hires or designing wellness programs based on real-time employee feedback. The challenge will be balancing adoption with ethical considerations, like bias and privacy. If companies can get that right, AI could redefine HR as a driver of innovation, not just a support function. I’m optimistic, but it’ll require careful navigation.
