Rob, good to see you. Vikas, nice to be with you.
Rob, you've described AI as the opportunity of a lifetime for
businesses.
What do you think makes the opportunity so compelling?
I don't think technology has ever been this accessible.
I look at the work we're doing with clients right now, and it's
not years, it's not weeks, and sometimes it's days.
And this is an opportunity to completely change how you do
business.
It's the productivity that it can bring.
It's how you can augment your developers.
AI is going to touch every business, every government, in
every part, which is why now is the moment.
It is the opportunity of a lifetime to take advantage of.
And Rob, we're here at Davos and there's a lot of dialogue around
both the opportunity.
There's so many stories about the impact of AI.
There are also a lot of stories about the worries and
challenges. So put yourself in the shoes of a CEO or a CIO.
If you're considering an AI transformation, what are the
factors that you should be considering?
Let's go big picture for a moment.
There's a there's an old macro investing equation that says GDP
growth comes from population growth plus productivity growth
plus debt growth.
Well, population is not growing in many countries around the
world if you look at the next 20 years.
So that means the only way we're going to grow as a global
economy is by driving productivity.
AI is going to be that catalyst to drive productivity.
How is it going to do it?
It's going to make everybody more effective, faster at doing
their job.
We've seen three major use cases for AI so far: customer service,
every company has customers.
They're trying to figure out how do I serve them better, how do I
make it a more intimate experience?
You can do that with AI.
Second is digital labor.
How do I augment my employees to make them 50% more productive in
doing repetitive tasks. Again, accessible to every customer.
Now I say third is code.
Most companies have software developers.
They're building products.
They're building technology.
If you can make them 30 to 40% more productive,
it completely changes how fast you can release products and
engage your customers.
So those are the use cases that I'm seeing in the real world
today.
And a lot of the talk around AI is around generative AI.
At BCG, we like to talk about the left brain and the right
brain, so both the generative, as well as the predictive
elements of AI.
How do you feel those will balance each other out, or how
do you think those are complementary to each other?
I do think people mix these, maybe intentionally, maybe
unintentionally. Maybe it matters, maybe it doesn't.
But I would say the generative AI is exactly what it sounds
like.
You're generating new content, so it's incredibly effective for
some of the use cases I talked about for doing summarization of
documents.
But let's not forget, we spent the better part of a decade
before on core machine learning, deep learning, predictive
analytics.
This is about how do I make a prediction about what might
happen.
The existence of generative AI has not reduced the need for
prediction.
If anything, I'd say it's made it more important.
So when we're working with clients, we say maybe don't
start with the technology yet.
Let's start with the use case, then let's figure out the right
technology to bring to it.
It's part of why what we've done with watsonx is making all types
of models available.
Machine learning models, open source models, some models built
by IBM.
We think there is a model for every job.
The question is, can you figure out what that is?
And similarly, what do you think is the relationship between AI
and cloud, hybrid cloud, quantum computing.
AI is probably perfect for this era of what we call hybrid
cloud.
If you go back five years, everybody was thinking how do I
move everything to one cloud.
I don't talk to any client now that says that's their
imperative.
The imperative now is how am I going to operate my business
across multiple clouds?
Public, private, edge.
And AI is all about how do you federate access to data across
those environments.
You may have applications across those environments.
So to some extent, AI will be accelerated by the existence of
hybrid cloud, not just cloud alone.
Let me switch gears here for a minute.
Rob, you've been an AI practitioner for a long time.
What was the moment when you first thought to yourself: Ha!
this could be really big?
I think it always comes to life with a client, and the one that
I saw, this was actually back to your point on the early days,
more machine learning, was
Bradesco, one of the largest banks in the world.
When I saw that they were doing 200,000 customer inquiries a
month without ever touching a human, which means they could
put all their people on the harder tasks, I was like, this
is going to completely change everything because now they can
get higher Net Promoter Scores.
Their employees are doing the kind of work that they want to
do, not the work that they have to do.
So that was the aha moment for me.
And I take that case and now it's even better with generative
AI.
So that was the aha moment for me.
And fast forward to today.
And you know, IBM has been announcing so much around
watsonx, what's your proudest customer moment,
more recently? We announced the partnership with Dun & Bradstreet
they're a data company.
They're trying to figure out how do they make their data more
accessible.
There's probably no better partnership for us than working
with a data company to bring their data to life with AI.
They're also using watsonx to transform their operations.
We're also building a go-to-market with them where we
can feature Dun&Bradstreet data as part of how we go to
market.
So I think it's an example of the kind of partnerships that
happen in this AI and hybrid cloud era, which are
multifaceted.
It's not just a customer vendor, it's how do we actually be
partners together.
Rob, thank you for a wonderful and thought-provoking
conversation.
Thank you, Vikas.