A new category of AI—including generative AI, large language models and foundation models—is becoming table stakes for any business operating in tomorrow’s market. With the sheer volume of data and insights needed to drive solutions for the problems enterprises face, business leaders will need to lean on the full capabilities of next-generation AI.
I’m back to traveling again and I’m loving it. I’ve been connecting with family, friends and colleagues and sampling the sights, sounds and flavors from all corners of the globe. And I know I’m not alone. Anyone who has spent any amount of time at an airport over the last 12 months can assure you that the passion for travel is back, and the flame is more alive than ever. Our latest consumer survey shows that 71% of consumers plan to sustain or increase their current spending on leisure travel in the next year.
And it’s not just travelers who are loving it. Travel companies are also seeing the benefits of this major jump in demand, and are finally reaping the rewards of the investments they made in technology during the pandemic. However, while many of these investments were made to take advantage of pent-up demand as pandemic restrictions were lifted, they quickly became part of a patchwork of technology solutions that have led to a fragmented traveler journey. As a result, many travel companies currently find themselves in a situation where they can only fulfil certain stages of the traveler journey and are missing out on opportunities to add value in other areas.
Imagine every employee in your company had an assistant that "knew" everything your organization had ever known—the entire history, context, nuance and intent of the business and its operations—and could process, analyze and use that information in a matter of seconds, in infinitely repeatable ways.
We're at a phase in the adoption cycle when most organizations are starting to experiment by consuming foundation models "off the shelf." However, the biggest value for many will come when they customize or fine tune models using their own data to address their unique needs.