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Hi everybody, and welcome to our
first conversation of the new
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year about artificial
intelligence. I'm Dan Loney.
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Great to be joined once again by
Stefano Puntoni, Marketing
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Professor here at the Wharton
School, and also co-director of
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the Wharton AI Human Research
Program. Stefano, great to talk
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to you again. How are you, sir?
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I'm great and happy New Year to
everybody.
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All right, so as
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the calendar turns to 2026— and
certainly 2025 had a lot of
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conversation around around
artificial intelligence. What is
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it that really has your interest
piqued as maybe some things to
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look out for as we go into the
new year?
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I was thinking about what will be
exciting to think about for 2026.
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These are— you know, there's
lots of stuff going on. Many,
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many trends, many things to
watch out for, but maybe I'll
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share quickly a list of six
things that I think is exciting
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to look forward to in 2026, and
that are going to shape a lot of
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processes and conversations
around AI. So let me go through,
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quickly, that list. I think the
first one will be really on the
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engineering side. We're going to
see an increasing specialization
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of models. We're going to have
faster models, more specialized
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models. If you take, for
example, ChatGPT already today
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is not one model, but it's more
like a switchboard that directs
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you to the model that is best
suited to answering a particular
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query that a user has. And we're
going to see that kind of
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specialization and flexibility
trade off between, you know,
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thinking, reasoning models or
test time compute kind of— you
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know, emphasis— versus speed and
quick and cheaper models. And so
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for companies that are going to deploy
language models across lots of
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different functions to do lots
of different jobs, the
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procurement process is going to
shift a little bit away from
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which vendor is the best, towards
more this idea of optimizing a
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portfolio of models. I think
that's one trend. The
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second trend will be towards
agentic systems. And so we've
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been talking about AI agents for
a year now already. So it's not
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a new thing. But here, I
emphasize the word system. So
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what we might see more and more
is where AI agents are not going
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to be just one agent performing
a multi-step operation. What
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you're going to have, you're
going to have a set of models
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which are going to be working in
concert to produce this work
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output across a set of steps.
And you're going to have models
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doing the work, and then you're
going to have other models
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checking the quality of the work
done by the first model. So
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you'll have more of a system-
like agentic AI. That's the
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second. The third one is
something more for consumer
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markets, where we're going to
see this everyday AI, trend
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continuing. We're going to see
more on-device AI. So devices
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like consumer electronics, such
as, you know, say smartphones,
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that are going to be optimized
for AI models. So, for example,
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just announced by Samsung, the
news is that they are planning
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to ship about 800 million
devices in 2026 that are AI-
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first. So this on-device trend
and everyday AI is one. Then, to
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me, it's interesting from the AI
labs and the platforms' point of
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view, how are we going to
monetize the free products? And
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we talked shortly about this in
a previous segment. But
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basically, these AI companies
say OpenAI are offering this
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free product, which is serving
hundreds of millions of
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customers, and they are not, you
know, paying anything for it.
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And so right now it's a massive
cash burn that will end. And so
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somehow these companies will
need to find a way to make money
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out of the free product, and
that basically means
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advertising. So we're going to
see increasing efforts to
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monetize the free
offerings.
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The fifth and sixth
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trends are more macro. The fifth
is regulation. On January 1, in
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California and Texas, new
laws on AI came into force. And
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we can expect more state level
and maybe government level
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across the world actions around
AI. Some of those conversations
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are going to be shaped also by
geopolitical forces and
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competition. And finally, of
course, is the one everybody talks
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about. It's about investments
and valuations and share prices.
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Are we in a bubble? Are we not
in a bubble? And what kind of
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bubble is it? We recently wrote
a short article in Knowledge at
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Wharton discussing this issue.
And everybody is excited to see
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what is going to happen in 2026.
This is a very short overview of
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a few things I think are
interesting to watch out for.
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So let me ask you this then.
From your perspective as a
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professor, and even to a degree,
the Wharton School as well,
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which I guess for the purposes
of this discussion, we could
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call the Wharton School a
business. How are— how is the
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Wharton School and your work
being impacted by AI? And how do
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you expect it to continue to
develop in 2026 because of AI?
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Oh, this academic year, I think, is
a very important academic year for
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the Wharton School when it comes
to AI. Because in September, we
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launched our AI major and AI
concentration for the MBA and
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undergraduate programs,
respectively, being the first
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year school to try that. So we
are in the middle of that
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experiment, and we are seeing
how this is panning out. I am
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actually very excited about my
course. I'm starting to teach in
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about two weeks. My course is
called AI In Our Life, and it's
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a quarter-length course for MBAs
and undergraduates. And I can
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tell you, this year, I'm adding
three new sections, three new
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topics to the course. The first
one is a session on creativity
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and ideation using language
models. The second one is a
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session on skills, and also deskilling.
What kind of skills do
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we need to develop to be
effective working with AI, but
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also what kind of skills we
should be careful about not
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losing when we work with AI? And
the third one is about AI agents
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and basically delegation of work
and integration of AI in
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workflows. These are basically
the three topics I'm adding. And
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I'm excited to meet lots of
bright students this quarter.
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Yeah. What is the
students' reaction when you're
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doing classes like this? And
they obviously understand the
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importance of AI and what it
means for not only their
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education, but for the
businesses that they work with,
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especially the MBA students.
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There's a huge thirst for
insight into AI. All the
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students recognize that AI is
going to be something that's
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going to shape a workplace to a
very significant extent. And
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also they realize that if they
can be competent and, you know,
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insightful in the way that they
understand how AI can impact
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business practices, they will
have an edge in the job market.
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And so— because all companies are
excited to to hire talent like
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that. So I think that's where we
see— we are curious to see what
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kind of interest the major is
going to get. We don't know,
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basically, how many students are
going to take the major. We'll
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see when they accumulate credits
and they try to credential in
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that. But judging from
enrollment in my course, there's
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certainly quite a lot of
interest in the topic.
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Stefano, always great to talk
with you, and again, we look
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forward to chatting with you
every month, talking about AI
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this year. Thanks. All the
best.
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Thanks, Dan, great to be here.
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You got it. Stefano Puntoni,
Marketing Professor
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here at the Wharton School, and
co-director of Wharton AI Human
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Research Program.
