Responsible AI in HR is about using technology to support better people decisions, without losing the trust and human judgment that those decisions depend on. Faisal Wahedi, Head of People – Asia, Infobip chats exclusively with Bhavya Bagga, Business Reporter, CXO Media how responsible AI is central to everything that HR does at Infobip.
As Head of People – Asia at Infobip, what leadership philosophy guides your approach to building high-performing and inclusive teams across culturally diverse markets?
My leadership philosophy centers on one principle: context-driven application. “What works” varies dramatically across locations. Malaysia’s talent market does not behave like India’s, and the engagement drivers in Kazakhstan differ from those in the Philippines.
I lead through three lenses: empowerment, clarity, and respect for local reality. Empowerment enables local teams to own their outcomes and test what works in their markets, and make decisions with accountability. Clarity means our objectives are precise and measurable, so everyone knows what winning looks like. And respect for local reality means we adapt global frameworks to local markets rather than force-fitting.
Infobip operates in a fast-paced communications technology ecosystem. How is the company shaping its people strategy to support rapid innovation, talent retention, and business growth across Asia?
Our people strategy is built on four global pillars, each contributing to the organization’s sustainable growth.
Hire and Enable for Impact: We introduced a bar-raiser process for all client-facing hires to ensure quality at speed, and we’re doubling down on referrals and structured interviewer enablement. This also enables a faster turnaround, accelerating hiring for client-facing roles that support the business.
Grow from Within: We target certain roles to be filled internally, including through our emerging talent pipeline. International mobility is active across the region, and some critical roles are filled by moving people across borders, also contributing to knowledge transfer. We’re also building readiness pools, from interns to SDRs to back-office talent, aiming for the majority of manager roles to be filled internally.
Stay Longer: Engagement is a core metric for us, and our goal is to maintain an overall engagement score above 80% across Asia. For us, this is not just a number — it reflects whether people feel supported, connected to our growth, and see a future for themselves at Infobip.
Lead Strong, Move Fast: We have identified that middle managers are the force multiplier. If they hire well, develop their people, manage performance, and set priorities, everything downstream improves. That’s where we’re investing.
AI is increasingly transforming HR from recruitment and workforce planning to employee engagement. How is Infobip leveraging AI internally, and where do you see the biggest impact in people management over the next few years?
AI adoption at Infobip is already strong —about 90% of employees are using AI tools, AI hackathons are scaling globally, and teams are upskilling across the board. We are using AI to automate multiple processes, freeing our People teams from repetitive admin so they can focus on strategic work.
In recruitment, AI helps us screen at scale and identify quality candidates faster. In workforce planning, we are building dashboards that give leaders real-time people insights instead of static quarterly reports. But the area I am most excited about is skills enablement. We are rolling out global skills assessments across 33 skills, with heatmaps, manager calibrations, and AI-powered simulations. The goal is to close 70% of priority skill gaps. That’s transformative because it moves talent management from “who’s available” to “who can be developed”, and AI makes that personalization possible at scale.
Where I see the biggest impact over the next few years: AI will fundamentally shift how we think about careers at Infobip. When you can map skills, predict gaps, and recommend learning paths with the help of AI, the conversation moves from “is this person promotable” to “what do they need to get there.” That’s a more honest, more productive conversation.
With AI increasingly influencing hiring decisions and workforce analytics, how do you balance automation with maintaining the human element in HR and employee experience?
I think this is one of the most important questions on everyone’s mind today. Technology is advancing rapidly, but HR is fundamentally about people, and people do not want to feel like they are being processed. Here’s how I think about the balance: automate the process, but keep the judgment human.
AI should support high-volume, pattern-based work such as screening resumes against skills matrices, identifying flight-risk patterns, and flagging engagement trends in survey data. That’s where AI can add real value. But every output from AI should inform a human conversation, not replace one.
There is a growing conversation around ethical AI and data privacy in HR. How is Infobip approaching responsible AI adoption while ensuring employee trust and transparency?
Responsible AI is central to everything we do at Infobip. HR departments hold data that is deeply personal — like compensation, performance, health, and other sensitive employee information. Using AI on that data without clear guardrails can quickly erode trust. Infobip’s approach is grounded in transparency and human oversight.
We also approach AI adoption in a structured way. We do not deploy tools without structure and accountability. We pilot, measure, and iterate, with clear governance around what AI can and cannot do in people processes. AI literacy is a key part of our enablement approach because teams need to understand both the value and the limits of these tools. Every HR team member is being trained not just on how to use AI tools, but on their limitations and risks.
On data privacy, we navigate GDPR, PDPA, PIPL, and multiple local frameworks simultaneously. Our focus is to meet the highest applicable standard, not just the minimum requirement. We’re building AI capabilities on a foundation that treats employee data with the same rigor we apply to our client data. AI can make HR faster and smarter, but only when employees trust that it’s being used responsibly. That trust is earned through transparency, not assumed through policy.
Ultimately, responsible AI in HR is about using technology to support better people decisions, without losing the trust and human judgment that those decisions depend on.
