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The Future Isn't Just Gen AI - It's Ethical, Orchestrated Intelligence
From academic curiosity to business transformation - Peter van der Patten's journey through AI spans decades, beginning in 1989 when he first explored the fundamental nature of intelligence. As Lead Scientist and Director of Pega's AI Lab, Peter brings a unique perspective that bridges theoretical understanding with practical implementation.
[Sponsored]
The conversation reveals how AI has evolved from isolated research projects to become deeply integrated into enterprise operations. Peter articulates a vision where intelligence isn't merely a technological overlay but woven into every customer interaction. This philosophy has guided Pega's approach: creating a horizontal platform where different AI technologies - from process mining to speech recognition, decisioning engines to generative models - work in concert within broader business ecosystems.
What emerges is a nuanced view of enterprise AI implementation. The most successful deployments blend multiple AI approaches, combining the predictability of traditional decisioning with the flexibility of generative capabilities. Take insurance claims processing: automated systems can assess approval likelihood or fraud risk while agentic components gather information and synthesize findings - all within structured workflows that maintain regulatory compliance.
This orchestrated approach addresses one of generative AI's central challenges: hallucination. By embedding large language models within established decisioning frameworks and governance structures, organizations can harness creative capabilities while maintaining accuracy and accountability. Peter emphasizes that ethical principles like explainability and transparency become even more critical as AI systems grow more complex and autonomous.
Looking toward the horizon, Peter identifies research agents as an early "sweet spot" for agentic implementation - tools that gather and synthesize information across sources while posing relatively low risk. The next frontier? Multi-agent collaboration, where AI systems must negotiate, understand each other's goals, and work cooperatively across organizational boundaries. Join us for this fascinating exploration of AI's past, present and emerging future - and discover why effective implementation demands more than just advanced technology.
๐ Watch Peter's interview on YouTube - https://youtu.be/W01zmYX-K8A
#PegaWorld2025 #AI #AgenticAI #PegaWorldย #AILiteracy Pegasystems #ad #Sponsored
Support the show
๐๐ผ๐ป๐๐ฎ๐ฐ๐ my team and I to get business results, not excuses.
โ๏ธ https://calendly.com/kierangilmurray/results-not-excuses
โ๏ธ [email protected]
๐ www.KieranGilmurray.com
๐ Kieran Gilmurray | LinkedIn
๐ฆ X / Twitter: https://twitter.com/KieranGilmurray
๐ฝ YouTube: https://www.youtube.com/@KieranGilmurray
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By Kieran GilmurrayFrom academic curiosity to business transformation - Peter van der Patten's journey through AI spans decades, beginning in 1989 when he first explored the fundamental nature of intelligence. As Lead Scientist and Director of Pega's AI Lab, Peter brings a unique perspective that bridges theoretical understanding with practical implementation.
[Sponsored]
The conversation reveals how AI has evolved from isolated research projects to become deeply integrated into enterprise operations. Peter articulates a vision where intelligence isn't merely a technological overlay but woven into every customer interaction. This philosophy has guided Pega's approach: creating a horizontal platform where different AI technologies - from process mining to speech recognition, decisioning engines to generative models - work in concert within broader business ecosystems.
What emerges is a nuanced view of enterprise AI implementation. The most successful deployments blend multiple AI approaches, combining the predictability of traditional decisioning with the flexibility of generative capabilities. Take insurance claims processing: automated systems can assess approval likelihood or fraud risk while agentic components gather information and synthesize findings - all within structured workflows that maintain regulatory compliance.
This orchestrated approach addresses one of generative AI's central challenges: hallucination. By embedding large language models within established decisioning frameworks and governance structures, organizations can harness creative capabilities while maintaining accuracy and accountability. Peter emphasizes that ethical principles like explainability and transparency become even more critical as AI systems grow more complex and autonomous.
Looking toward the horizon, Peter identifies research agents as an early "sweet spot" for agentic implementation - tools that gather and synthesize information across sources while posing relatively low risk. The next frontier? Multi-agent collaboration, where AI systems must negotiate, understand each other's goals, and work cooperatively across organizational boundaries. Join us for this fascinating exploration of AI's past, present and emerging future - and discover why effective implementation demands more than just advanced technology.
๐ Watch Peter's interview on YouTube - https://youtu.be/W01zmYX-K8A
#PegaWorld2025 #AI #AgenticAI #PegaWorldย #AILiteracy Pegasystems #ad #Sponsored
Support the show
๐๐ผ๐ป๐๐ฎ๐ฐ๐ my team and I to get business results, not excuses.
โ๏ธ https://calendly.com/kierangilmurray/results-not-excuses
โ๏ธ [email protected]
๐ www.KieranGilmurray.com
๐ Kieran Gilmurray | LinkedIn
๐ฆ X / Twitter: https://twitter.com/KieranGilmurray
๐ฝ YouTube: https://www.youtube.com/@KieranGilmurray