Naspers' annual profit jumps on strong e-commerce, Tencent

JOHANNESBURG (Reuters) -South African technology investor Naspers posted a 59.4% jump in its full-year core headline earnings, driven by accelerated growth and improved profitability of its e-commerce businesses and contribution from China's Tencent.
Naspers said on Monday its core headline earnings per share (HEPS) from continuing operations rose to 1,830 U.S. cents in the year ended March 31, up from 1,148 U.S. cents.

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The best hiring decisions still require final human judgment. What AI can do is help recruiters spend less time on repetitive tasks and more time on high-value work. This is where a better framework is needed, one that views AI not as a substitute but as a support system. Augmented Intelligence refers to the intentional use of AI to enhance, not replace, human decision-making. In recruiting, it means AI assists with speed, insight and scale, while people bring context, judgment and relationship. This model remains the most accurate and forward-looking framework for how AI should operate in recruiting. What's changing is what AI is capable of. Today's advanced AI models, especially those powered by large language models (LLMs), do far more than analyze and accelerate. They can learn from hiring patterns, feedback loops and recruiter input. They begin to understand role requirements and the less tangible elements of cultural fit and leadership style. Over time, they adapt, refining candidate recommendations based on outcomes, team feedback and even subtle preferences that emerge across hiring cycles. For example, AI can now flag which candidates meet hard skill requirements and which ones are most likely to thrive within a specific team dynamic. It can pick up on tone, communication style and alignment with stated values, especially when that data is fed back into the system with thoughtful human input. That said, AI is not a standalone solution. It's a system that gets smarter in partnership with the people using it. Recruiters still play the essential role in validating, interpreting and humanizing decisions. They see the subtleties that algorithms can't always explain, like when a candidate needs reassurance before an offer call or when a resume doesn't tell the whole story. The real power lies in the partnership. When recruiters and AI systems learn together, hiring becomes faster, more intelligent, inclusive and aligned with long-term success. What's Holding Teams Back? While the technology exists, real adoption still lags. The reasons vary, but looking at my work with clients, internal recruiters and HR teams over the past few years, some common themes emerge: • Bias Concerns: Fears that AI will reinforce existing inequities. • Opaque Systems: Tools that don't explain how decisions are made. • Poor Integration: Platforms that disrupt more than they support. • Limited Training: Recruiters unsure how to use the tools effectively. • Lack Of Leadership Alignment: Tech investments without strategic backing. These are solvable problems. However, solving them requires a mindset shift from viewing AI as a one-size-fits-all product to understanding it as a framework that evolves with the team. What Recruiters Need Now For AI to create lasting value in hiring, it must be embedded in transparent, fair and recruiter-centric systems. That means: • Customizable scoring models that recruiters can adjust. • Mobile-friendly workflows that simplify scheduling, feedback and even initial interviewing. • Real-time summaries that keep teams aligned and data clear. • Ethical design principles that prioritize job-relevant skills over proxies like resume formatting or educational pedigree. It also means taking a hard look at the current recruiting tech stack. Many tools are siloed; they offer overlapping features but don't communicate. A more effective path forward is to consolidate around platforms that support recruiters in practical, flexible ways. For Talent Leaders, The Window Is Now The companies that win the talent war in 2025 and beyond won't be those that rely on AI the most. They'll be the ones that use it most wisely, choosing tools that respect the craft of recruiting while amplifying what makes it powerful. These companies will: • Replace reactive hiring cycles with data-informed planning. • Reduce time-to-fill without cutting corners on quality. • Deliver better candidate experiences, from first contact to offer. • Equip recruiters with insight, not just automation. This doesn't require a total overhaul. It starts with asking the right questions: Where are we losing time in our hiring process? What tools are our recruiters actually using, and which are getting in the way? Are we learning from each hire, or repeating the same process without feedback? If the answers point to gaps in consistency, efficiency or visibility, AI can help—but only if it's purposefully introduced. The Bottom Line The future of recruiting isn't about removing humans from hiring. It's about removing the obstacles that keep them from doing their best work. The tools are ready. 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