It’s safe to say we live in a video-first world.

In fact, 9 out of 10 people prefer learning about products or services through video over text. Also - employees are 75% more likely to watch a video than to read documents, emails, or PowerPoints.

However, only ~1% of a company’s employees have the skills to create videos. The remaining 99%, from training and support to sales departments, primarily rely on text-based resources like PowerPoints and PDFs to share information with each other and customers.

Synthisia is changing this, empowering the 99% by making video easy for everyone. 

Synthesia enables anyone to create high-quality content, nearly identical to human produced. This includes text, images, music, voices, and hyper-realistic digital humans, all generated with simple text input. 

In this session, you’ll learn how Synthesia’s large enterprise customers are:

• Doing away with long, dense handbooks, PDFs, and instead opting for engaging videos featuring AI avatars that can deliver information to employees in 140+ languages.
• Creating high-quality, professional videos without the need for cameras and studios.
• Allowing quick and easy updates to videos to keep information up to date without having to create a new video every time.
• Enabling anyone on the team, from an HR manager to a salesperson, to become a video creator.

We all understand the power of generative AI & we are still a long way from large scale deployment becoming mainstream, but there is no doubt that every business should be utilizing it in some capacity. Questions arise however, when we delve into the logistics: which capacity and how should we practically go about this without any problems arising. When you are deploying generative AI into production on a large-scale within an enterprise that has real world implications, you need to be exact and you need to prove that it’s the right strategy for your business.

·       What challenges specifically do we want to be addressed and how can we realistically utilize generative AI for these?

·       What internal changes do we need to implement? Who will be doing this?

·       How can we mitigate any problems arising with large-scale deployment?

·       How can we balance cautiousness and innovation?

·       How do we decide on business metrics we want to use to measure it?

·       How to assess all the smart, realistic, ethical, political and economic considerations when you have a real world impact?