4 days ago
AI With Empathy—And Humans In Control
Gaurav Basra, CTO,
Conversational AI is a game-changer and a business imperative, but how do we get it right? Replace everything with AI or something else?
From automating customer support to enhancing sales conversions, organizations across industries have embraced deploying AI-powered chatbots, voice assistants and virtual agents to engage customers more efficiently and cost-effectively.
Why Conversational AI Works
Conversational AI blends natural language processing (NLP) with machine learning to simulate human-like dialogue. Technology evolves with each interaction, providing smarter responses, better context and smooth escalation when needed.
Its benefits span both front-end and back-end operations. It allows customer support teams to be available 24/7 and can lead to faster resolution times and enhanced customer satisfaction. It provides sales and marketing teams with improved lead qualification, lead scoring, keyword analytics, retargeting, personalized engagement and intent analysis. HR and internal operations teams can streamline onboarding while having internal help desks and access to knowledge.
Gartner, Inc. has predicted that by 2026, 10% of all customer service interactions will be automated using conversational AI, saving businesses an estimated $80 billion annually.
Risks: Automation Without Oversight
While the potential is enormous, so are the pitfalls.
Generative models can provide inaccurate or misleading answers without clear boundaries or supervision. Limited training data, large language model design and a lack of real-world experience can create responses that meet the best probable response instead of factual answers. For example, if a website visitor asks for a specific procedure that isn't performed at a practice, but something similar is listed on the website, AI might assume that the procedure not listed is also performed due to a lack of knowledge base information.
Poorly designed bots may frustrate users by failing to recognize emotional tone or understand nuanced queries. In healthcare, empathy plays a vital role, as human-to-human interaction builds strong connections. When adopting AI, ensure there is a seamless transition to humans on demand. In my experience, live chat has provided more qualified leads than AI alone. These leads are nurtured during live chat interactions, and the probability of sales conversion is higher.
AI systems handling sensitive data must comply with regulations such as HIPAA, GDPR or SOC 2 and be guarded against prompt usage or data leakage attacks.
AI should not replace human interaction—it should enhance it. Success lies in striking a balance between machine efficiency and human empathy.
Human Element: Augment The Process, Not Replace Humans
The most successful deployments keep people at the center, and AI models should be designed to augment services rather than replace them. AI is as good as the data used to model it.
• Human-In-The-Loop Design: Build AI systems that escalate to live agents at the right time, preserving human connection in critical moments.
• AI Coaching For Teams: Use conversational analytics to coach human agents, improve tone and identify training gaps.
• Empathetic Design: Scripts and decision flows should reflect brand voice and emotional sensitivity. Human behavior must be modeled into interaction, especially in industries like healthcare, senior living and financial services.
In essence, conversational AI should free up people to do what they do best—solve complex problems, build relationships and deliver high-touch experiences.
Adoption Strategy: From Pilot To Scale
Implementing conversational AI requires more than plugging in a chatbot.
• Identify high-volume use cases. Start with repetitive, high-frequency tasks—customer FAQs, appointment scheduling or password resets—where automation delivers quick wins.
• Select the right platform. Choose a platform that offers scalability, NLP flexibility, integration APIs and hybrid support (live agent plus AI).
• Build with empathy and intent analytics. Effective bots are functional. They're also conversational. Design flows with emotional intelligence and use intent analytics to continuously optimize.
• Pilot, measure and iterate. Run pilots in real environments. Track key performance indicators (KPIs) like deflection rate, customer satisfaction, resolution speed and escalation rate. Refine based on feedback.
• Train people, not just machines. Equip support, sales and marketing teams to collaborate with AI, understanding its strengths, limitations and how to intervene when needed.
As GenAI evolves, we'll see greater adoption in complex decision making, financial planning, healthcare triage and legal advisory. The future is multimodal: blending chat, voice and visual interfaces to meet users wherever they are.
However, the winning formula remains clear—AI with empathy and humans in control. Businesses that get this right will reimagine customer engagement, create loyal relationships and build a smarter, more responsive enterprise.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
