The New Automation Mindset: AI + Automation + Integration

Why Trimble’s VP of Technology Innovation Embraces Chaos while Reducing Friction

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Oct 22, 2025

Aviad Almagor, VP of Technology Innovation at Trimble, has over 25 years of experience bridging the physical and digital worlds across various industries. In the discussion, he highlights Trimble's transition from hardware to software and the importance of connected, quality data for successful AI initiatives. Aviad dives into the role of generative AI in merging structured and unstructured data, and shares insights on why many AI pilots fail. He emphasizes embracing chaos in workflows and the need for interoperability to reduce friction in fragmented organizations.

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INSIGHT

Connect Field Data To Office Workflows

Trimble combines sub-centimeter field data with office workflows to enable better decisions across projects.
Connected, contextualized data unlocks planning, resource allocation, and collaboration value.

ADVICE

Fix Data Quality And Governance First

Improve data quality, context, and accessibility before scaling AI systems.
Implement governance and fine-tune models to ensure trust and security for AI use.

INSIGHT

Reduce Friction, Don’t Erase Silos

You cannot remove silos overnight; focus on reducing friction and enabling interoperability.
Use common data environments and open standards to create a single source of truth.

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In this episode of The New Automation Mindset, Markus Zirn is joined by Aviad Almagor, VP of Technology Innovation at Trimble, to speak about how the nearly 50-year-old company is integrating predictive and generative AI into its global operations. They explore how Trimble went from using ML for infrastructure analysis to deploying GenAI-powered agents across design, product development, and internal workflows. Aviad shares real-world examples of some of the innovations his team leads and discusses what makes AI pilots succeed or fail.

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Guest Bio

Aviad Almagor is a product and technology innovation leader with more than 25 years of experience at the intersection of industrial sectors—spanning Architecture, Engineering, Construction & Operations (AECO), transportation, agriculture, and geospatial—and cutting-edge technologies. Trained as an architect, Aviad transitioned early into 3D design and disruptive digital tools, eventually pioneering large-scale adoption of mixed reality, robotics, and AI in these industries.

Today, as Vice President of Technology Innovation at Trimble, Aviad leads global initiatives that connect the physical and digital worlds—helping these industries become more productive, efficient, and sustainable.

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Guest Quote

"The big value is not in doing what we do today more efficiently or faster. The big value is in the redefinition of the work. The way we’re working with an agent, this is something that will evolve, and we need to design for that." – Aviad Almagor

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Time Stamps

00:00 Episode Start

02:50 The history of Trimble

05:00 Setting higher standards for your data

08:05 Building trust in your data

11:20 Embrace complexity, reduce friction

16:00 The importance of IT / Business collaboration

20:15 Trimble's journey implementing AI efforts

23:55 Overcoming resistance to new tools

27:20 Specific examples of AI transformations

31:10 What stands in the way of AI adoption

38:10 The future for both predictive and generative AI

44:45 Aviad's advice for other CIOs

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Episode Key Takeaways

Culture accelerates transformation: Trimble's collaborative, innovation-first culture enables bottom-up AI exploration, leading to enterprise-wide adoption. Executive support, psychological safety, and shared outcomes are essential to scale cross-functional AI teams.
Think beyond productivity: AI’s value isn’t just in speeding up tasks, it’s in transforming how work gets done. GenAI can open creative workflows, reimagine design collaboration, and personalize user experiences.
Predictive AI and GenAI work best together: Predictive models offer consistent, domain-specific analysis where GenAI adds creativity, natural interaction, and automation. When integrated, they can power end-to-end, intelligent workflows.

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