Diving into the transformative landscape of HR, I’m thrilled to sit down with Marco Gaietti, a veteran in management consulting with deep expertise in strategic management and organizational growth. With decades of experience guiding businesses through complex challenges, Marco offers a unique perspective on how HR is evolving into a pivotal driver of business adaptability. In this conversation, we explore the integration of cutting-edge technology like AI into HR practices, the shift toward dynamic feedback cultures, strategic talent density, the balance of global and local cultural frameworks, and the reimagining of HR from mere programs to customer-centric products. Let’s uncover the moves every leader must make as we head into 2026.
How have you observed the rise of AI in HR transforming workplace practices, especially with 43% of organizations now leveraging it compared to just 26% in 2024? Can you share a specific instance or pilot where AI was applied to solve a business challenge, including the outcomes and any hurdles you encountered?
Well, the rapid adoption of AI in HR—jumping from 26% to 43% in such a short time—really shows how quickly organizations are recognizing its potential, even if the high-ROI use cases aren’t fully crystalized yet. I’ve seen this play out in a project where we tackled inefficiencies in talent acquisition for a global tech firm. The business problem was clear: their hiring process was sluggish, taking weeks to sift through thousands of applications, and they were losing top candidates to competitors. We piloted an AI-driven tool to screen resumes and conduct initial candidate assessments, aiming to cut screening time by half. The results were promising—we reduced the initial review phase by 60%, and about 30% of the candidates flagged by the AI ended up in final interviews, which was a solid indicator of its accuracy. However, the hurdle was real: transparency and bias concerns loomed large. We had to double down on auditing the algorithm to ensure it wasn’t inadvertently favoring certain demographics, and frankly, the lack of comprehensive training for the HR team—only about 30% felt confident using the tool initially—meant we had to slow down scaling. I remember the tension in the room during our first review meeting; you could feel the skepticism from the team, but once we iterated based on their feedback, trust started to build. It taught me that AI isn’t just plug-and-play—it demands governance, ethical design, and a human touch to balance the tech with the people.
With over 75% of organizations moving toward continuous feedback and skills-based approaches, how have you fostered a culture of peer and upward feedback in your experience? Could you walk us through the training process and share a standout moment from a leadership feedback session?
Creating a culture of continuous feedback, especially with over 75% of organizations embracing this shift, is about breaking down old hierarchies and empowering everyone to speak up. In one of my consulting roles with a mid-sized tech company, we completely revamped their feedback system by introducing peer and upward feedback mechanisms alongside regular growth check-ins. The training process was intensive—we held workshops for both employees and managers focused on how to give and receive feedback constructively, emphasizing direct communication with a positive spin. We rolled out mock scenarios over several weeks, ensuring folks felt safe to practice tough conversations, and paired this with digital tools for real-time feedback to ditch the rigid annual cycles. I’ll never forget a 360 feedback session with the executive team—one senior leader received candid upward feedback about their overly directive style, and you could see the surprise on their face, almost a flicker of defensiveness. But then, they leaned in, asked questions, and later shared how that moment shifted their approach to team meetings, making them more collaborative. It was a raw, emotional turning point, reminding me that feedback isn’t just data—it’s a bridge to trust and growth when handled with care. Building that muscle at the top sets the tone for the entire organization.
You’ve emphasized talent density as a competitive advantage, particularly in cost-effective expansions like achieving development capability at a third of the usual investment in markets like India. How do you pinpoint high-impact roles for such strategies, and what does the cross-functional alignment process look like with specific success metrics?
Talent density is all about focusing on quality over quantity, ensuring you have the right skills in the right places to drive outsized impact. When strategizing for a cost-effective expansion, such as the one in India where we achieved development capability at roughly a third of the typical cost, identifying high-impact roles starts with mapping business goals to skill needs. We analyzed which roles—think specialized tech developers or data scientists—would directly accelerate product innovation, then assessed skill gaps in the existing workforce. Cross-functional alignment was critical; we brought together HR, finance, and operations leaders to align on priorities, budget, and timelines, ensuring hiring in India wasn’t just cheap but strategically tied to global objectives. Success showed up in metrics like time-to-market for new features, which dropped by 25% within the first year, and a 30% increase in project delivery capacity without inflating headcount costs. I recall walking through the buzzing new office in Bangalore, feeling the energy of a team that wasn’t just filling seats but solving real problems for the business. It’s a reminder that talent density isn’t a numbers game—it’s about precision and collaboration across functions to maximize return.
Your concept of a ‘g-local’ culture strikes a balance between global coherence and local nuances across numerous markets. How do you determine which principles stay uniform and which get adapted, and can you share an example of a tailored talent practice or rewards system for a specific region?
The ‘g-local’ approach is about weaving a common thread of values and identity across an organization while respecting the unique fabric of each local market. When deciding what remains uniform, we anchor on core principles like integrity, fairness, and our mission—these are non-negotiable and create a sense of unity across hundreds of markets. But practices like talent management or rewards? Those often need a local lens to resonate with cultural expectations and labor norms. For instance, in a consulting project for a multinational, we adapted the rewards system for a Southeast Asian region by incorporating festival-based bonuses tied to major cultural holidays, rather than the standard year-end bonuses used elsewhere. The thought process was rooted in understanding local employee expectations—surveys showed over 80% valued culturally significant rewards—and competitive analysis of regional labor markets. I remember the HR lead in that region lighting up when sharing how employees felt truly seen during the first payout, with team morale visibly lifting during the festive season. It wasn’t just about money; it was about signaling respect for their traditions, proving that local adaptation can strengthen global cohesion if done thoughtfully.
As HR shifts from programs to products with a focus on employee experience, how have you used agile methods to redesign talent systems? Can you describe the testing and iteration process, along with feedback that influenced the final outcome?
Reimagining HR as a product-driven function is a game-changer—it’s about crafting experiences that employees and leaders actually want, not just policies to follow. In one of my projects with a tech firm, we applied agile methods to redesign their learning and development system, moving away from static training programs to a dynamic, user-centric platform. We started with rapid prototyping, building a minimum viable product focused on personalized learning paths, then tested it with a small cohort of employees over a six-week sprint. Iteration was constant—based on weekly feedback loops, we tweaked features like adding gamified progress tracking after users said they wanted more engagement. One piece of feedback that hit hard was from a manager who felt the initial interface was too cluttered; I can still picture their frustrated expression during the demo, which pushed us to simplify the design significantly. Employees later shared how the final version felt intuitive, almost like a consumer app, with 70% reporting higher usage compared to the old system. Leadership appreciated the data insights on skill gaps, which helped strategic planning. It was a messy, fast-paced process, but that agility—testing, listening, iterating—turned a clunky program into a product people valued.
Looking ahead to the evolving role of HR in driving business performance, what is your forecast for how technology and talent strategies will shape the workplace in the coming years?
I believe the next few years will see HR solidify its position as a strategic growth engine, with technology like AI becoming the backbone of how we structure work, rather than just a shiny add-on. We’ll likely see talent strategies pivot even more toward hyper-personalized experiences—think AI tailoring career paths or feedback in real time—while balancing ethical concerns and transparency to maintain trust. The rise of global talent mobility will push ‘g-local’ frameworks further, demanding HR leaders to be cultural navigators as much as business strategists. I envision workplaces where continuous feedback isn’t just a trend but a core way of operating, breaking down silos and fueling adaptability. My forecast is optimistic yet cautious—technology will amplify HR’s impact, but only if we prioritize human connection over automation. I think we’ll see the most successful organizations being those that blend tech-driven efficiency with a deep, empathetic understanding of their people.
