
Playbook: Outcomes-Based AI
Outcomes Drive AI with Purpose
AI is entering the most consequential corners of our world, from financial oversight to public trust and citizen services. In these domains, performance isn’t measured by novelty, but by impact and outcomes – with requirements for control, transparency, and sovereignty. The question isn’t what AI can do, but what it must do reliably, transparently, and in alignment with high-purpose goals.
This paper explores a shift in focus: from testing how AI can work, to building AI that delivers. Because in high-stakes environments, outcomes aren’t a byproduct. They are the benchmark.
What’s Inside
- Avoid common pitfalls that cause AI projects to stall before they deliver value
- Shift from technology-first to outcomes-first, starting every initiative with clear business objectives
- Learn from real-world examples across finance, legal, insurance, public sector, and defense on how organizations achieved measurable results
- Pair quantity with quality metrics so you can prove both efficiency gains and user satisfaction
- Adopt a proven framework for building, testing, and scaling AI applications with confidence
Featured Speakers
Disclaimer
Gartner Cool Vendors in AI Engineering, Arun Chandrasekaran, Manjunath Bhat, Arup Roy, George Brocklehurst, 6 November 2024
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