Engineering Trustworthy AI: An Evidence-Driven SDLC for AI-Enabled Systems
Artificial intelligence is changing not only software capabilities but also the way systems must be specified, built, tested, released and operated. An AI-enabled application combines models, prompts, contextual data, retrieval mechanisms, tools, integrations and human decisions. Its behaviour may change when any of these components changes. Traditional software-development controls must therefore be extended to address uncertainty, data provenance, security, accountability and continuous evaluation.
This technical talk presents an evidence-driven AI System Development Life Cycle comprising five stages: Intent, Build, Review, Deploy and Verify. It explains how to define a bounded use case and prohibited actions; design traceable AI-system architecture; manage model, prompt, data and tool versions; construct representative evaluation sets; and assess outcome quality, security, privacy, latency and cost. Particular attention will be given to prompt injection, data leakage, unsafe tool use, human oversight, release authorization, rollback and incident escalation.
The session will also examine the evidence required at each lifecycle gate, the conditions that should prevent an AI system from entering production, and the monitoring needed after deployment. An illustrative workflow will show how engineering, security, governance and business teams can work within a common lifecycle without diluting accountability. Participants will leave with a practical framework for moving from an AI experiment to a controlled, measurable and trustworthy production system.
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Dr. Ashwini Kumar Rath of Batoi System
Engineering Trustworthy AI: An Evidence-Driven SDLC for AI-Enabled Systems
Artificial intelligence is changing not only software capabilities but also the way systems must be specified, built, tested, released and operated. An AI-enabled application combines models, prompts, contextual data, retrieval mechanisms, tools, integrations and human decisions. Its behaviour may change when any of these components changes. Traditional software-development controls must therefore be extended to address uncertainty, data provenance, security, accountability and continuous evaluation.
This technical talk presents an evidence-driven AI System Development Life Cycle comprising five stages: Intent, Build, Review, Deploy and Verify. It explains how to define a bounded use case and prohibited actions; design traceable AI-system architecture; manage model, prompt, data and tool versions; construct representative evaluation sets; and assess outcome quality, security, privacy, latency and cost. Particular attention will be given to prompt injection, data leakage, unsafe tool use, human oversight, release authorization, rollback and incident escalation.
The session will also examine the evidence required at each lifecycle gate, the conditions that should prevent an AI system from entering production, and the monitoring needed after deployment. An illustrative workflow will show how engineering, security, governance and business teams can work within a common lifecycle without diluting accountability. Participants will leave with a practical framework for moving from an AI experiment to a controlled, measurable and trustworthy production system.
Biography:
Dr Ashwini Kumar Rath is an entrepreneur, technologist, author and researcher, and the Founder and CEO of Batoi, where he leads strategic direction, product innovation and research. Trained in theoretical physics and software management, he later earned a doctorate in cybersecurity management, specializing in green-computing metrics and sustainable practices in DevSecOps.
His current interests span artificial intelligence, DevSecOps, quantum computing and sustainable computing, with particular emphasis on building trustworthy and governable digital systems. He has authored academic, business and technical articles and has addressed national and international forums on emerging technologies, software engineering, cybersecurity and digital transformation.
Dr Rath is a member of the IEEE Computer Society and a life member of the Computer Society of India. He also contributes to professional, academic and public-policy bodies, bringing together research, engineering and enterprise experience.
Address:Founder and CEO of Batoi, , Bhubaneswar, Orissa, India, 751024