5 Things to Watch Out for Before Trusting an AI Vendor

October 15, 2024

1 hour

Speakers:

Alisher Yuldashev

Head of Security and Privacy Assurance, ASAPP

Theresa Liao

Director of Content & Design, ASAPP

About the webinar

How many pitches for AI solutions hit your inbox each day? We heard from one CX leader who counted 30 – just over lunch. That’s a lot of marketing spin to sift through. And that eats up time you probably don’t have. Which of these vendors offer AI solutions for CX that are safe and trustworthy?

Choosing a solution that’s right for your contact center is hard. Choosing the one that will protect your brand from novel AI risks while delivering outstanding results is even harder. If only you could spot them quickly – before you pull your IT, security, legal and compliance teams into the mix.

Join us to learn the 5 things to watch out for before trusting an AI solution provider with your data and your brand. Alisher Yuldashev, ASAPP expert in AI safety and trust, will walk you through the key considerations for eliminating unreliable providers and identifying the trustworthy partners.

What you'll learn:

How to manage your data, including usage in ML training

AI-specific safety measures

How to manage model development with robust quality assurance processes

About the speakers

Alisher Yuldashev

Head of Security and Privacy Assurance, ASAPP

Alisher Yuldashev is managing a team of security, privacy and compliance professionals building trust with ASAPP’s customers and prospects and managing governance and risk. As a seasoned Trust & Assurance professional currently specializing in AI Safety and Assurance, Alisher will share insights around things to look for when choosing an AI vendor. Prior to ASAPP, Alisher worked at a big-four accounting/consulting firm, where he led teams on various technology risk and security consulting engagements and audits.

Theresa Liao

Director of Content & Design, ASAPP

Theresa leads the Content Marketing & Design teams at ASAPP.

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What you'll learn

01

How to manage your data, including usage in ML training

02

AI-specific safety measures

03

How to manage model development with robust quality assurance processes

01

How to manage your data, including usage in ML training

02

AI-specific safety measures

03

How to manage model development with robust quality assurance processes

04

05

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5 Things to Watch Out for Before Trusting an AI Vendor

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