In the rapidly evolving world of artificial intelligence (AI), companies are learning that success goes beyond simple automation. According to KPMG’s global tech report in 2023, 55 per cent of organisations delayed their progress toward automation because of their concerns about how AI systems make decisions.

As we approach 2025 and beyond, leading businesses are shifting their focus to human-centric AI—AI systems designed not just to automate, but to collaborate with human intelligence. These systems are proving essential for enterprises that aim to balance innovation with ethical responsibility, and here’s why they’re becoming a priority.

The limits of automation

Automation has been a game-changer for many companies in recent years, streamlining repetitive and routine tasks. However, it’s becoming increasingly evident that automation has its limits. While it’s great for enhancing productivity, automation alone cannot handle the depth and complexity required for higher-level problem-solving.

One key limitation of traditional automation is its lack of reasoning ability. Unlike human-centric AI, which can analyse context and make decisions based on understanding and reasoning, automation follows predefined rules and struggles with tasks that require judgment, adaptability, or thoughtful decision-making. The ability to reason is crucial for navigating complex situations that demand creative solutions and a deep understanding of human behaviour, something pure automation cannot achieve.

Thus, for tasks requiring creativity, emotional intelligence, or strategic thinking, automation falls short. If businesses rely too much on it, they risk creating rigid systems that don’t adapt well to the real-world needs of their employees or customers.

Human-centric AI: A necessity for enterprises

In highly regulated industries—such as finance, healthcare, and insurance—simple automation isn’t enough. Leading enterprises are recognising that their success hinges on understanding human behaviour. Here’s why:

• Complex web of interactions: From employees and stakeholders to customers, operations involve multifaceted human interactions.
• Internal and external needs: Human-centric AI enables businesses to streamline operations while maintaining the human touch that is essential for building trust with staff and customers alike.

Human-centric AI helps companies improve how they work and interact. It balances the benefits of automation with the human touch that’s essential for building trust and meeting industry regulations. Cathay Pacific Airlines have saw immediately after implementing AI-powered “Fly Ready” which able to customise emails to fit each passenger’s unique situation, keeps communication personal, making interactions feel more human, over 200,000 hours of labor costs were reduced.

Navigating human complexity with AI

AI faces a significant challenge in dealing with the complexity of human behaviour. People are diverse, with different preferences and behaviours, making it difficult for traditional AI to predict their needs accurately. Human-centric AI, however, takes a different approach.

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It leverages AI to predict and influence behaviour by employing behavioural science to understand human behaviours, predict needs and preferences, and influence desired actions without being forceful. This approach transforms interactions into more authentic experiences.

It covers the key areas below to make AI more impactful and effective in both internal operations and customer-facing interactions:

• Diverse behaviours: People exhibit varying behaviours and preferences, making it difficult for traditional AI to predict needs accurately.
• Tailored strategies: Human-centric AI can adapt to different audience segments, crafting personalised messages and strategies that resonate on a deeper level.
• Genuine influence: By understanding what truly matters to each person, human-centric AI can drive decisions and behaviour in ways that feel authentic and personal.

Key elements of human-centric AI

The power of decision AI and operational AI

AI is no longer just about automating basic tasks. Today’s companies are combining Decision AI and Operational AI to supercharge their growth.

• Decision AI: It uses data to enhance strategic choices, empowering employees to make well-informed decisions that align with business goals and customer expectations.
• Operational AI: This AI focuses on optimising workflows and automating routine processes, allowing human employees to focus on higher-level problem-solving and innovation.

Together, Decision AI and Operational AI form a powerful framework that allows businesses to innovate swiftly, respond to market demands, and accelerate growth.

The role of behavioural science in AI

Understanding human motivations, emotions, and decision-making processes is key to enhancing AI’s effectiveness. Behavioural science adds a crucial layer to human-centric AI, allowing for:

• Tailored user experience: AI systems can be designed to better serve both individuals and organisations, adapting to human nuances.
• Empathy and connection: By leveraging behavioural insights, AI systems foster stronger relationships, built on empathy and deeper understanding.

This human-first approach enables companies to strengthen customer loyalty and improve employee satisfaction, both of which are essential for long-term growth. KewMann has empowered one of the oldest financial services company owned by the government in Asia increase 7x of collection efficiency after implementing human-centric AI platform that provides personalised messaging based on behavioural analytics that influence more customers the willingness to pay.

Responsible AI and Explainable AI: Building trust

As companies deploy AI in more sensitive areas, responsibility and transparency become critical. Responsible AI ensures that systems operate with fairness, accountability, and transparency.

Also Read: AI revolution: Balancing human empathy and robotic efficiency in customer service

• Ethical considerations: Leading companies prioritise AI systems that don’t just enhance efficiency but also uphold ethical standards, especially in regulated sectors where trust is paramount.
• Explainable AI: In medium- and high-risk scenarios, AI systems must be transparent and understandable. Companies need to know how and why AI makes its decisions, making explainability a crucial feature for human-centric AI.

By ensuring that AI systems are responsible and explainable, companies not only mitigate risks but also build trust with customers and regulators, ultimately strengthening their compliance and reputation.

Why human-centric AI should be the standard, not just the future

Prioritising human-centric AI is not just about keeping up with technological advancements; it’s about creating a sustainable, innovative, and customer-focused business model. For organisations looking to thrive in 2025 and beyond, prioritising in human-centric AI is essential.

This approach not only enhances operational efficiency and customer satisfaction but also builds a resilient and adaptable organisation that can confidently navigate the complexities of the future.

As you consider your AI strategy, remember that the ultimate goal is not just to implement technology but to enrich the human experience at every level—internally and externally. Embrace human-centric AI and position your organisation as a leader in an increasingly interconnected world.

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