Rajiv Shesh, Chief Revenue Officer at HCLSoftware – a global division of HCLTech –discusses how businesses can maximise the value of artificial intelligence by building frameworks for meaningful human-AI collaboration.
AI THAT HELPS HUMANS – THE FUTURE OF WORK
As artificial intelligence (AI) becomes core to how businesses in the Asia Pacific region (APAC) operate, the narrative must shift from AI vs. human jobs to augmented intelligence.
This human-centric approach lies at the heart of the emerging ‘agentic future’ – using AI as a force multiplier to enhance human skills.
For example, imagine an AI chatbot quickly finding an order status, then smoothly handing you over to a human for a complex issue. AI handles repetitive tasks, freeing people to focus on big ideas, creativity, and ethical judgments.
Given APAC’s commitment to AI governance and maximising economic impact, maintaining a ‘human in the loop’ approach is essential for ensuring trust, transparency, and accuracy across the region.
The companies moving fastest aren’t waiting for grid solutions. They’re deploying storage systems, building control capabilities, and turning energy management into a competitive advantage, whilst their competitors treat it as an unavoidable cost.
AI’S TWO POWERS: HELPING AND ACTING INDEPENDENTLY
Augmented intelligence isn’t about giving control to machines; it’s about using AI to make human skills much stronger.
AI can quickly find patterns, detect anomalies, and predict future trends. This helps people make quicker, smarter choices, whilst upholding human responsibility.
Consider financial experts. AI can analyse vast market data and suggest investment strategies, but the human expert applies judgment, considers broader economic factors, and makes the final decision. AI helps them decide; it doesn’t decide for them.
A key element of augmented intelligence involves ‘autonomous agents’ – AI tools that operate independently within human-set boundaries.
These agents will transform industries from IT management to traffic control, where AI systems can adjust traffic lights to optimise vehicle flow.
However, for them to work well, we must maintain strong governance ensuring accountability and human oversight.
MAKING AI FAIR, CLEAR, AND ETHICAL
For augmented intelligence to truly succeed, people need to trust it and understand how it works. Unlike older AI, which often felt like a mystery box, this AI shows its work. However, challenges remain:
- Unfair AI – AI systems are only as fair as the information they learn from. If the data is biased, AI might repeat old prejudices and lead to unfair results. Researchers at the Massachusetts Institute of Technology (MIT) have developed methods to reduce this risk by identifying and removing data that could make AI biased or hurt its performance.
- Ethical AI and rules – AI systems need to be open and responsible from the very start. Ethical augmented intelligence isn’t just about showing its work; it needs strong rules that focus on making fair decisions, protecting user privacy and following new AI laws. Companies, lawmakers, and AI experts must work together to create good rules for AI.
- Closing the AI skills gap – For augmented intelligence to work, people must develop new skills alongside it. Training programmes will help ensure experts can interpret AI results, companies foster cultures of responsible use, and AI enhances rather than replaces jobs. The World Economic Forum’s Future of Jobs Report 2025 confirms AI will create more jobs than it replaces if companies invest in training.
RETHINKING AI: THE WAY FORWARD
Augmented intelligence isn’t just incremental progress for AI – it’s a significant leap for human potential.
To maximise its value, companies must go beyond simply adopting AI tools. They should build frameworks for meaningful human-AI collaboration, focusing on:
- Clear and controlled – AI should help people, not control them. When AI shows its decisions, people trust it more and use it.
- Ethical development – Rules must guide AI systems to be fair, safe, and responsible from the start.
- Practical use – AI should be used for real business results, not just because it’s trendy. It needs to fit into how a business works, with clear goals and ways to measure success.
