-: This is really the moment when generative AI is popping,
because finally, it's allowing enterprises
to capture the value from AI
without having access to armies of data scientists,
which are a scarce talent.
It's allowing enterprises to use their domain knowledge
to query these generative AI models,
and get value generating results out of them.
It's proving to be a great equalizer
because of the API development talent
that's required to gain value out of it
is quite easily available,
so now everyone can have access to it and generate values.
It's a very exciting moment in AI.
I think there are really three things
that enterprises needed to do
to be able to take advantage of this technology
for their businesses.
Number one is, there's a very thoughtful selection
of the actual business use cases
that can derive benefit for the business
and take advantage of the specific trove of enterprise data.
Part two is picking the right platform
to power the enterprise journey.
The generative AI platform
needs to be enterprise-grade from day one.
This means it needs to be allowed for privacy,
for security, for ease of use,
for scalability, and so on and so forth.
This is still an emerging and dynamic space
and we expect new offerings to come up.
And so keeping an eye on these
and being able to evaluate those offerings
to pick a true enterprise-grade platform
will make a huge difference.
And third will be to establish
a very sound responsible AI framework within the enterprise
to guide the development of the use cases,
and make sure that issues like governance,
liability, trustworthiness,
and belief in the results of generative AI
can be trusted upon
to be able to drive enterprise results.