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Tetra Tech’s Tech 1000.AI Challenge Addresses Real-World Client Challenges

Tech 1000.AI finalists pose for a group photo on stairs

During our annual Tech 1000.AI Challenge technology incubator, Tetra Tech employees from around the world pitched creative solutions leveraging artificial intelligence (AI) and machine learning (ML) for client challenges in environment, water, and sustainable infrastructure.

The 8-week Tech 1000.AI competition brought together teams from across Tetra Tech to assess existing and potential client opportunities, build on our technology and technical excellence, and generated more than 200 scalable ideas that apply AI and ML. The annual challenge links teams across markets and geographies, promotes innovation, and increases participants’ understanding of AI to further advance our Leading with Science® approach.

Meet our 2024 Tech 1000.AI challenge winners

Finalists from around the world attended the final challenge round and award ceremony from April 4–6 in Arlington, Virginia. The final four teams presented ideas for building urban resilience, advancing the energy transition, improving wildlife conservation efforts, and improving airport infrastructure for safety and operations efficiency. Winners were selected by a panel of senior leaders representing various Tetra Tech markets.

T1K Grand Champion

Idea: Using AI to tackle challenges in the aviation industry worldwide
Team: Carmen Yu and Colin McGuire

Runner-up

Idea: Using AI to mitigate the impact of heat islands in urban cities
Team: Jonathan Barnes, Holly Miller, Neel Simpson, Darwin Dyck, Ivan Salhus, Greg Williams, Jonathan Smith, Graham Elgie, Andrew Campbell, Damian Ling, Winnie Cheah, Eddie Feher, and Matt McCowan 

Finalist

Idea: Leveraging AI technology for wildlife conservation efforts worldwide
Team: Steve Dimitriadis, May-Le Ng, Garry Straughton, April Hutchinson, Audrey Wee, Elise Lok, and Patrick Rath  

Finalist

Idea: Using rapid AI-enabled greenhouse gas sequestration measurements to advance the energy transition
Team: Emily Gardner, Casee Lemons, Xander Mckinstry, and Matthew Smiles 

The Tech 1000.AI Challenge is a fantastic initiative by Tetra Tech, and I really enjoyed interfacing with people across the company in the US, Canada, UK, Australia, and elsewhere. I’m looking forward to keeping the momentum going and bringing this solution to our clients!
Colin Mcguire, Water Resources Engineer, Tech 1000.AI Grand Champion

Supporting competitive learning for our global workforce

At Tetra Tech, we recognize the importance of not only hiring technical leaders, but also providing platforms for employees to create scalable ideas that anticipate current and future client needs. Tech 1000.AI is a great example of a learning and networking program that is available to participants across the company, creating new relationships and fostering collaboration and learning.

As part of the Tech 1000.AI Challenge, participants engaged with clients and collaborated with Tetra Tech’s AI expert coaches and technical mentors to create tailored solutions that answer client needs. In addition to assessing the technical viability of their solutions, judges also considered the cost-saving, regulatory, privacy, and safety considerations that affect project implementation.

Building on 60 years of industry-leading, technology-driven experience

Since its inception in 2020, the Tech 1000 Challenge has generated hundreds of innovative solutions with applications across key Tetra Tech markets and sectors. The internal competition brings together our digital and technical expertise to create technology-focused solutions that leverage AI-enabled software platforms such as FusionMap® and OceansMap™ and builds on our Tetra Tech Delta suite of technologies. Past solutions generated from the challenge include Façade AI, an AI-powered tool that auto-recognizes defects in brickwork, stonework, and concrete.

Participants will be taking their ideas from this year’s competition forward to provide innovative, sustainable, and scalable solutions to our clients.

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