October 2, 2025Oct 2 Q 811. AI agents can process huge amounts of data and recommend actions quickly — but not every decision should be left to AI. Some choices involve ethics, empathy, or strategic judgment that go beyond data patterns. Think of one process in your domain where AI could handle 90% of the workload but must always defer to a human for the final decision. What makes that decision uniquely human, and how would you design the AI’s role so it adds value without overstepping? ⚠️ Note: Any answer that is generic or does not connect with a specific, relevant process will not be approved. 🏆 The best answer will be selected on the basis of: Relevance of the chosen process and decision Clarity in defining the AI vs. human boundary Practicality of the human-AI collaboration model Note for website visitors - This platform hosts two weekly questions, one on Monday and the other on Thursday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Monday or Thursday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be considered for winner selection. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honourable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error-prone because our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://quillbot.com/ai-content-detector. Only answers with less than 45-50% AI-generated content will be considered for winner selection.
October 4, 2025Oct 4 AI should be used to help human take the right decision based on historical data and pattern analysis and not to be used to eliminate Human completely. Human interventions are needed when it comes to Ethics, Human Emotions, handling conflicts, Legal compliances, Audits so on and so forth. Let us take corporate function as an example and understand what all are the areas where AI should allow human to decide. Corporate function deals with Human Resource ( HR), Finance and Procurement, Legal & Compliance, Marketing & communications, Operations and Supply chain and IT & Security. While AI brings enormous efficiency in the Corporate Function however everything can not be automated rather should not be automated. 1.Human Resource: AI involvement: AI can be used in Screening the resumes from the third-party job portals which is matching the job role/ descriptions as per the open positions Employee sentiment can be analysed using AI through the internal employees’ surveys Skill gaps can be identified based on the Role performed by the employee v/s the skills that is there for the employee and accordingly training plans can be designed for respective employees Human Interventions: Resumes can be shortlisted by AI, however conducting the interviews, analysing the knowledge ( Technical and functional) should be done by Human. This process does not only include the knowledge check but also check the behavioural and cultural fitment for the offered position. Which is advised to be done by the Human only. Deciding the performance rating, Promotions should be dealt by human only and should not be dependent on AI or automated process Resolving conflict amongst the employees should involve human touch than mechanical As all the above-mentioned actions require empathy, context and fairness beyond data 2.Finance and Procurement: AI can be used to automate a) Cash flow forecasting b) Fraud detection Human Intervention is needed a) Data analysis can help you create the different model however actual allocation of funds in different areas should be a Human Decision than an automation process b) Negotiating Vendor contracts should be done by human, AI can be used to identify the key takeaways from the contracts however decision making should be done by Human after analysis and considering other soft contributors All though AI can be helpful to analysis big data and help human to make right decisions, the above-mentioned areas need judgement, relationships and accountability to be considered before making decisions. Hence human intervention is needed. 3.Legal and Compliance: AI can be used to draft Contract and Flag the regulatory compliance However, Human decisions should be there a. to interpret the ambiguity and the sensitive cases b. Settlements, penalties and escalations 4.Marketing and communications AI can be used to draft the content, campaigns targeting etc Whereas Human intervention is needed a. in addressing any geopolitical crisis, Cultural or emotional public topics b. Drafting crisis communication or brand positioning To uphold the companies brand organisations should take care of the communication tone and should be empathetic rather than mechanical or robotic. Only human brain can understand the Social timing and sentiment. 5.Operation and Supply Chain AI can be broadly used in a. Demand planning b. Scheduling However, a Human driven approach is needed to a. Ethical sourcing of resources b. BCP planning to respond during disruption A strong leadership and well-designed recovery plan drive resilience at the time of crisis. AI can help in the decision-making process but should not own the decision making which affects people, ethics, reputation, strategy. Where ever there is a need of human values and ethics AI should let Human to decide.
October 4, 2025Oct 4 AI-Enabled Predictive Maintenance and Special Cause Variation Response System Cable Manufacturing - UAE One of the leading Cable Manufacturing company's leadership has been leveraging AI for early detection of anomalies such as insulation breakdowns, sensor irregularities on cable extrusion lines, temperature variations, cable diameter drift, and bearing wear. For these major contributing factors, AI recommends preventive maintenance, short-term pauses, or complete production shutdowns to prevent large-scale scrap. However, the final decision to act is always made by technical process experts—with human intervention remaining essential. AI Role Conduct real-time monitoring to detect small and large shifts in the production line. Classify anomalies based on severity and recommend appropriate actions, such as scheduling maintenance, implementing a temporary halt, or requiring a complete shutdown. Scan through all relevant global case studies on similar issues and justify why intervention is necessary, including suggested remediation. Human Intervention Review and interpret AI recommendations to assess their feasibility and relevance. Evaluate possible impacts in terms of operational targets, customer commitments, potential penalties, accountability for on-time delivery, and the impact on shift workers. Consult with the process excellence team, business leaders, and technical experts, recognizing that tolerating certain minor defects may be more cost-effective than stopping production and incurring downtime. Conclusion AI-enabled systems can expedite preventive maintenance, provide better insights, and recommend a wide range of alternative options. However, AI still lacks empathy, accountability, a deep understanding of business needs, ethical reasoning, and the ability to weigh the price of staying competitive—which sometimes involves tolerating certain anomalies.
October 5, 2025Oct 5 Solution Let’s answer this question taking example of healthcare claims adjudication process. HealthCare BPO Associate receives the claims from the Payer where decision has to be made to accept or reject the claim In Claims adjudication process, AI can easily handle 90% of work – most of which is repetitive. Tasks include scan the claim form, basic validation, duplicate checks, COB checks, verifying CPT/ ICD codes, checking if any exception code has been triggered, and flagging any rule violations using configuration logic defined by Payer However, the final decision to release the claim (approve or deny) should always rest with human examiner, especially in case if complex claims, where medical necessity is questionable and patient circumstances don’t always fit the rulebook Such cases demand empathy and ethical judgement -reading between the lines and understanding doctors’ intent. The decision should always reflect balancing compliance with compassion. Since algorithms are trained purely on data patterns, such nuances cannot be expected to be executed by AI accurately A practical AI Precision Assistant – Human collaboration model can be designed in this example where AI can do the heavy lifting 1. Claim intake and basic validation can be done by AI agent using OCR+NLP models to extract and validate member, provider and service fields 2. Rule based checks and duplicate checks which involved applying payer policies, checking if claims fall between designated coverage limits, and assessing historical claims data – all these can be handled by AI agent 3. Predictive scoring: AI agent can rank the claims by likelihood of approval/denial and can assign confidence score to it 4. If confidence score assigned by AI model is <85% or if patient context is not clear, then these claims will get routed to human examiner who will evaluate intent, context and fairness before making the final call This clear demarcation allows AI to work as Precision assistant while human examiner will retain the ethical and strategic accountability. This clear demarcation between AI Agent and Human examiner is required and human should make final decision because: · We are not just processing claims, but impacting person’s health and financial well being · Only human examiner can recognize when a rule should not override compassion · Only human can bring in unique blend of empathy, sound judgement and ethical awareness
October 6, 2025Oct 6 AI can analyze past data, spot gaps / anomaly logically and give a list of smart suggestion much faster than human but AI cannot feel, care and understand human emotion, and ethics. That’s why for any people emotion and relationship related issue, human must take the lead not AI. For example, during talent acquisition lifecycle with AI integration, AI can shortlist all suitable candidates based on their skill fitment and relevant experience, but the final decision should be taken by human (function head), because it need the trust and ethics both. Human can think what morally right not just what statistically significant. Especially when the situation is new and ambiguous or unclear, where AI can learn from the past data pattern and gaps, AI can guess wrong also. But human can use their intuition and creativity to handle any new problem together (AI+Human integrated system) . Because AI is great with past data and facts, but not with coming context. For example, in corporate leadership decisions specially in negotiation stage with multi stakeholder environment or for a critical client negotiation stage during new deal or renewal deal case , understanding individual tone, stakeholder’s body language, or unspoken concerns are also key factors. That’s where human intuition work effectively. So, the ownership should be with human not on AI . AI can advise only as a tool but cannot take blame for a very crucial decision (like a human life and death issue in healthcare). So, whenever a decision need human intuition, AI should step back and human decide.
October 6, 2025Oct 6 Author Rohan’s answer on AI in Healthcare Claims Adjudication stood out for its exceptional clarity, empathy, and practicality. He demonstrated how AI can perform 90% of the heavy lifting — from OCR and validation to confidence scoring — while ensuring that humans retain final decision authority in cases requiring compassion, fairness, and contextual judgment. His design of a Precision Assistant model (AI–Human collaboration with threshold-based escalation) made the response both insightful and implementable. Runner-up – Shashi Prakash Shashi’s example from Cable Manufacturing (AI-enabled Predictive Maintenance) was highly commendable. His explanation of AI recommending preventive actions while humans weigh business impact and accountability reflected excellent balance between automation and decision ownership. 👏 Other Approved Responses – Indrani Ghosh Dastidar and Sanjib Ghosal Both presented meaningful perspectives on where AI should step back — Indrani with a comprehensive corporate function view, and Sanjib with a thoughtful articulation of emotion, ethics, and intuition supported by a clear visual. However, these were broader in scope and less focused on a single process example.
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