Speaker 1: Hey everyone, it's Robert and Joe here. Today we've got
Speaker 1: something a little bit different to share with you. It
Speaker 1: is a new season of the Smart Talks with IBM
Speaker 1: podcast series.
Speaker 2: Today we are witnessed to one of those rare moments
Speaker 2: in history, the rise of an innovative technology with the
Speaker 2: potential to radically transform business and society forever. The technology,
Speaker 2: of course, is artificial intelligence, and it's the central focus
Speaker 2: for this new season of Smart Talks with IBM.
Speaker 1: Join hosts from your favorite Pushkin podcasts as they talk
Speaker 1: with industry experts and leaders to explore how businesses can
Speaker 1: integrate AI into their workflows and help drive real change
Speaker 1: in this new era of AI. And of course, host
Speaker 1: Malcolm Gladwell will be there to guide you through the
Speaker 1: season and throw in his two cents as well.
Speaker 2: Look out for new episodes of Smart Talks with IBM
Speaker 2: every other week on the iHeartRadio app, Apple Podcasts, or
Speaker 2: wherever you get your podcasts, and learn more at IBM
Speaker 2: dot com slash smart talks.
Speaker 3: Hello, Hello, Welcome to Smart Talks with IBM, a podcast
Speaker 3: from Pushkin Industries, iHeartRadio and IBM. I'm Malcolm Glapo. This
Speaker 3: season we're continuing our conversations with new creators visionaries who
Speaker 3: are creatively applying technology in business to drive change, but
Speaker 3: with a focus on the transformative power of artificial intelligence
Speaker 3: and what it means to leverage AI as a game
Speaker 3: changing multiplier for your business. Today's episode highlights the power
Speaker 3: of collaboration. IBM has long been a supporter of the
Speaker 3: better Together mindset and embraces partnerships. They have been working
Speaker 3: together with Salesforce for more than two decades, but have
Speaker 3: recently launched a new collaborative effort surrounding generative AI. Pushkin's
Speaker 3: very own Jacob Goldstein sat down with Matt Candy and
Speaker 3: Susan Emerson. Matt is the global managing partner of Generative
Speaker 3: AI at IBM Consulting, helping clients and partners around the
Speaker 3: world in raised this new era of technology, and Susan
Speaker 3: is a senior vice president for Salesforce dedicated to AI,
Speaker 3: analytics and data. They discussed the historic collaboration between the
Speaker 3: two tech giants, explored the opportunity AI presents for customer service,
Speaker 3: and walk through how businesses can use generative AI to
Speaker 3: interface with clients. Okay, let's get to the conversation.
Speaker 4: Thank you guys for coming this morning. So I'm interested
Speaker 4: in how you both came to generative AI, or maybe
Speaker 4: it sort of came to you in the way it
Speaker 4: sort of came to all of us, But how did
Speaker 4: you arrive at working on generative AI.
Speaker 5: As part of my remitted Salesforce. Over the years, I've
Speaker 5: brought a lot of analytics and data and machine learning
Speaker 5: products to life under the Einstein brand at Salesforce. So
Speaker 5: as we pivoted Salesforce into taking advantage of the enertive
Speaker 5: AI moment, it was natural that I became part of
Speaker 5: the advanced team leveraging generative AI and it's become interesting.
Speaker 5: But what I see as I speak with customers the
Speaker 5: moment that everyone is facing in terms of how they
Speaker 5: incorporate genitive AI into their businesses, their workforces, and their
Speaker 5: technical stacks. It's actually opening up a lot of doors
Speaker 5: to other utility of analytics, data and AI. So it's
Speaker 5: been this big pull through in terms of incorporating not
Speaker 5: just generative AI, but a larger conversation around how we
Speaker 5: become all better using data in our day jobs.
Speaker 4: So that's a great frame for sort of what's going
Speaker 4: on at Salesforce with generative AI. Matt tell us a
Speaker 4: little bit about how that fits with the way IBM
Speaker 4: is approaching the space.
Speaker 6: Yeah, so I guess through three sides to that question.
Speaker 6: And so there's the technology side of it. So IBM
Speaker 6: has a technology organization, and so you know, we are
Speaker 6: building and have been over many years, decades In fact,
Speaker 6: IBM has been working in this space a generative AI
Speaker 6: stack that allows organizations to adopt generative AI technology aimed
Speaker 6: at enterprise and business use within their organizations. So then
Speaker 6: within the consulting business, you know, we have one hundred
Speaker 6: and sixty thousand people who work every day with clients
Speaker 6: across every industry, regulated industries, government organizations, and so this,
Speaker 6: you know, is a really important technology that those companies
Speaker 6: are going to be using to drive the next level
Speaker 6: of transformation in their enterprises processes and the types of
Speaker 6: experiences they build for their customers. And so you know,
Speaker 6: we work extensively with partners technology such as Salesforce, AWS, Microsoft,
Speaker 6: as well as our own technology. And then find I
Speaker 6: guess the third angle is the work that we've got
Speaker 6: to do to reinvent the business of consulting. And so
Speaker 6: if I think about you know, consulting in systems integration.
Speaker 6: You know, ultimately we are knowledge workers, right, and so
Speaker 6: from an industry perspective, I think you know, our industry is,
Speaker 6: same as many others, is going to is going to
Speaker 6: go undergo a level of disruption caused by this technology.
Speaker 6: But therefore that will also create a huge opportunity for
Speaker 6: us as well.
Speaker 7: So those three aspects, Jacob.
Speaker 4: Great, So, so that's the point of view sort of
Speaker 4: from your companies in your work. I'm curious to talk
Speaker 4: for a moment about AI from the point of view
Speaker 4: of consumers and employees kind of out in the world today.
Speaker 4: So just to start with consumers, when I'm just out
Speaker 4: as a person as a consumer in the world, how
Speaker 4: am I experiencing AI today?
Speaker 7: I'll give you a great little use case.
Speaker 6: Actually, I was on holiday three weeks ago in Tenerif
Speaker 6: in Spain, and I was trying to find somewhere to
Speaker 6: park the car with the family for dinner that evening,
Speaker 6: and I found this area next to this kind of
Speaker 6: shopping center and there was this sign there and I
Speaker 6: couldn't quite work out if it was saying I could
Speaker 6: park there or not, And so I took a photo
Speaker 6: of the sign and I uploaded it to an AI
Speaker 6: tool and I said what does this mean? And it
Speaker 6: basically explained to me what the sign was saying and
Speaker 6: basically told me that I shouldn't be parking there, and
Speaker 6: so I drove on and I found some somewhere else
Speaker 6: to park. But you know, that allowed me, in under
Speaker 6: sixty seconds to probably avoid one hundred euro fine by
Speaker 6: parking the car there. So just a simple example, but
Speaker 6: I think the ability that these tools have to take
Speaker 6: friction out of our daily lives, you know, and to
Speaker 6: be able to make just things that we do in
Speaker 6: our everyday life simple and more frictionless.
Speaker 2: You know.
Speaker 6: That's how I look at how mat the consumer's going
Speaker 6: to benefit from some of this type of technology.
Speaker 5: And from my perspective, it's also a travel story. I
Speaker 5: spend a lot of time on the road for work,
Speaker 5: but recently had to send my sister and her family
Speaker 5: to a destination they had never been to for a wedding,
Speaker 5: and it was really quick and easy to use some
Speaker 5: generitive tools to come up with a whole plan for them.
Speaker 5: Because they love to hike and to be outdoors and
Speaker 5: to hike in areas that aren't overly crowded with people,
Speaker 5: and so Jenai very quickly gave me an itinerary of
Speaker 5: a bunch of terrific hikes for them for a destination.
Speaker 7: So things like that great.
Speaker 4: And then what about the effect of AI and of
Speaker 4: automation more generally on employees on the.
Speaker 5: Workforce, Well, there's so many dimensions to take that from
Speaker 5: generitive AI really can up level a workforce in all
Speaker 5: sorts of ways by providing these consistent ways to engage
Speaker 5: with technology, with these natural language experiences. So I think
Speaker 5: it changes everything from it finds us content, it generates
Speaker 5: us content, it makes it easier to work with our
Speaker 5: systems of engagement and operation, and for many organizations it
Speaker 5: can be a lifting factor in terms of bringing a
Speaker 5: more consistent workforce experience because these tools can just be
Speaker 5: ever present in our systems of work.
Speaker 6: I mean, I'll give you a little example here in IBM,
Speaker 6: we have something called our skjar and so that's our
Speaker 6: conversational AI interface that we use to interact with HR
Speaker 6: services and ninety four percent of every employee interaction now
Speaker 6: happens without human intervention through that interface. But you would
Speaker 6: never know that. And so if I think about, you know,
Speaker 6: our HR processes. You know, we have this amazing conversational
Speaker 6: based AI that we use for all of our HR
Speaker 6: interactions and we surface that through SLACK, and so SLACK
Speaker 6: becomes the front door for how we access a lot
Speaker 6: of these different enterprise processes and capabilities and how we
Speaker 6: surface AI. In fact, I'm taking a flight shortly back
Speaker 6: to the UK and our our skhar boss is reminding
Speaker 6: me that it's raining in the UK and I should
Speaker 6: take an umbrella.
Speaker 5: Isn't it always like raining in England?
Speaker 6: Yeah, I don't think there's any AI needed for that.
Speaker 6: I think that's just a hard coded If England, then
Speaker 6: take umbrella.
Speaker 7: That's right, that's just a rule.
Speaker 6: That's just a rule, right, and you're able to converse
Speaker 6: and yeah, I need to book holiday, I need to
Speaker 6: move somebody between managers. I need to figure out the
Speaker 6: policy on this. And the AI basically navigates across the
Speaker 6: different systems to be able to help get that information,
Speaker 6: to summarize it back to be able to carry out
Speaker 6: the transactions that I need carried out, and it just
Speaker 6: removes all of that complexity and makes it easier to
Speaker 6: get things.
Speaker 4: Done when you are working with companies to implement generative AI. Now,
Speaker 4: what do you find tends to be their primary focus?
Speaker 5: I mean I speak with a lot of customers each week,
Speaker 5: and for the last several months, most organizations have just
Speaker 5: been reorienting themselves in terms of where are we in
Speaker 5: this moment, what is this technology capable of? What are
Speaker 5: the risks and governance and frameworks that I need to
Speaker 5: establish in order to engage and talk to everyone. Talk
Speaker 5: to my vendors, talk to my cloud providers, talk to
Speaker 5: my consultants, talk to academics, and generally get your sea
Speaker 5: legs under them. And the sort of the unstructured hand
Speaker 5: on keyboards fiddling with technology seems to be moving towards
Speaker 5: let's get some points on the board, let's turn this
Speaker 5: stuff on and go. So that's what I've been seeing
Speaker 5: in terms of the work within the salesforce ecosystem. Matt,
Speaker 5: you've got a larger apperture as well. What are you seeing?
Speaker 7: Yeah, so I definitely agree.
Speaker 6: I think, you know, there's been lots of getting sea legs, experimentation,
Speaker 6: just trying to build knowledge, being able to try and
Speaker 6: build almost you know, internal organizational point of view and
Speaker 6: reference framework. I've seen lots of what I would have
Speaker 6: referred to as random acts of AI.
Speaker 7: In terms of in terms of experimentation.
Speaker 6: But I think I think people now looking into twenty
Speaker 6: twenty four and this is all about now adoption and scaling,
Speaker 6: what's become really clear is organizations have started to realize
Speaker 6: this is going to be a very multi model world
Speaker 6: that they're going to live in. There is no one
Speaker 6: AI that is the answer for their organization, and so
Speaker 6: they're going to have lots of different generative AI models
Speaker 6: and technologies that they're going to sit in the organization
Speaker 6: servicing different use cases, different domain areas, different products and services,
Speaker 6: and so therefore having to figure out how they're going
Speaker 6: to navigate and manage this kind of open world that
Speaker 6: they're going to be sitting in and the decisions that
Speaker 6: they're going to have to make around that. I think
Speaker 6: the second thing that I've seen that people are now
Speaker 6: becoming very clear that this needs to be what I
Speaker 6: would refer to as use case lead and outcome focus,
Speaker 6: and so really needing to start with thinking about the
Speaker 6: business outcome and the problem that you know, we're trying
Speaker 6: to solve, and therefore, how do I use generative AI
Speaker 6: as part of the mechanism to solve that problem. And
Speaker 6: I think, you know, what Susan and the Salesforce team
Speaker 6: do is an amazing example of that. You know, they've
Speaker 6: got this incredible platform and engine that allows companies to
Speaker 6: transform their sales and service processes and to be able
Speaker 6: to put data in the hands of users, to be
Speaker 6: able to make better decisions, et cetera. And so now
Speaker 6: by weaving generative AI into that platform, we're going to
Speaker 6: be able to make those processes workflows even more efficient. Right,
Speaker 6: So it's generative AI plus all of these other amazing
Speaker 6: things that are there. It will be led through business outcome,
Speaker 6: and it will be led through use case and the
Speaker 6: business problem or workflow that we're trying to improve. And
Speaker 6: then I think the third thing is shifting from this
Speaker 6: experimentation to scale. You know, I think everybody's really early
Speaker 6: in this journey, but what's become clear is that you know,
Speaker 6: everybody now need realizes and is starting to lay down
Speaker 6: these ground rules, the guardrails, the frameworks to allow them
Speaker 6: to scale this across the organization. So, you know, I
Speaker 6: think we're in for an exciting, exciting time in twenty
Speaker 6: twenty four.
Speaker 4: So now that we're getting to this moment, what are
Speaker 4: the key things companies have to figure out about scaling
Speaker 4: generative AI.
Speaker 5: I would put that in kind of two categories, and
Speaker 5: following on what Matt was saying in terms of use,
Speaker 5: case defined and outcome, LAD one hundred percent on that
Speaker 5: in terms of starting with a hypothesis of value while
Speaker 5: at the same time people are getting you know, closer
Speaker 5: to the technology to know what their bounds are. But
Speaker 5: the biggest, you know, set of conversations is in the
Speaker 5: enterprise area in terms of embarking and using with generative AI,
Speaker 5: how to do it in ways that is safe for
Speaker 5: use of data that is safe around not just the
Speaker 5: larger topic of generative AI and hallucinations, which which are
Speaker 5: fun to talk about in the media.
Speaker 4: But it's a fun word, right If it was called
Speaker 4: something other than hallucinations, people wouldn't talk about it as much.
Speaker 2: It was just.
Speaker 5: Mistakes, Yeah, that's right, just things that aren't factually true.
Speaker 5: We've been doing a lot of work at Salesforce around
Speaker 5: using you know, dynamic and structured grounding the data so
Speaker 5: we can give very strong and non naive prompt instructions
Speaker 5: to lllms to get return on that. So so just
Speaker 5: to summarize top of mind for organizations using you know,
Speaker 5: large language models, is using their data in ways that
Speaker 5: are safe, trusted, not exposed, and reducing the opportunity for
Speaker 5: hallucinations and maximizing relevant content.
Speaker 2: Great.
Speaker 4: So, Matt Susan was talking about, you know, both what
Speaker 4: organizations are concerned with as a scale generative AI and
Speaker 4: how Salesforce is working to sort of address those concerns.
Speaker 4: What are you seeing at IBM here?
Speaker 6: So, I think certainly from a scaling of generative AI perspective,
Speaker 6: you know, this topic of governance, you know, and how
Speaker 6: organizations are going to have to govern all of these
Speaker 6: models that sit withinside, how they manage kind of bias fairness,
Speaker 6: model drift, you know, if you think about the data
Speaker 6: that's gone into a model and the output it gives
Speaker 6: to start with, not because the model changes, but because
Speaker 6: the context of the world moves on. And so being
Speaker 6: able to kind of manage this model drift is going
Speaker 6: to be a really important thing. I think data really matters,
Speaker 6: and so quality access security around data within the enterprise
Speaker 6: is going to be critical to scaling generative AI. And
Speaker 6: the other one I think that's going to be really important,
Speaker 6: and I think many organizations haven't even got there yet.
Speaker 6: In their thinking is around the ESG implications. So carbon
Speaker 6: you know, the use of this technology does not come
Speaker 6: without a cost of carbon.
Speaker 4: Carbon meaning it's very energy intensive.
Speaker 6: Correct, Yeah, the training of the models and so thinking
Speaker 6: about carbon disclosures and thinking about where I'm infusing it
Speaker 6: into my business and how much I'm using it and
Speaker 6: what the carbon cost of that is. As I think
Speaker 6: about the you know, you know, my own organizational responsibilities
Speaker 6: to reduce carbon I think, you know, there's all of
Speaker 6: these things that I think are going to become important
Speaker 6: factors as people are thinking about the scaling implications of
Speaker 6: this technology.
Speaker 3: AI is already making new experiences possible, but we must
Speaker 3: be mindful in how we integrate this new technology as
Speaker 3: we continue scaling generative AI. Matt touched on some crucial
Speaker 3: aspects from an IBM perspective. Governance, bias, fairness, and security
Speaker 3: are all key considerations when organizations aim to expand their
Speaker 3: use of generative AI. The environmental aspect is especially important,
Speaker 3: and it's refreshing to hear leading thinkers like Matt and
Speaker 3: Susan highlight these issues As this technology continues to evolve.
Speaker 3: These factors are becoming increasingly important for organizations to address
Speaker 3: the historic collaboration between IBM and Salesforce is helping to
Speaker 3: remedy issues companies face when scaling AI.
Speaker 4: So IBM and Salesforce recently announced a new collaborative project
Speaker 4: around generative AI. Tell me more about that.
Speaker 6: We've been partners for over two decades now IBM and Salesforce,
Speaker 6: and so within our consulting business, we work with Salesforce
Speaker 6: technology to help our clients implement that technology to transform
Speaker 6: their businesses. We've got a huge practice, over twelve thousand
Speaker 6: people with certifications around Salesforce platforms, and so you know,
Speaker 6: as Susan and her team and the broader team in
Speaker 6: Salesforce are infusing more capability into the platform around generative AI,
Speaker 6: then our mission is really simple. It's to help clients
Speaker 6: who are using the Salesforce platform adopt those capabilities to help.
Speaker 7: Them get more benefit within their organization.
Speaker 6: You know, we're also a significant user of Salesforce technology
Speaker 6: within IBM. We're one of Salesforce's largest customers globally, and
Speaker 6: so you know, as we continue to transform our own
Speaker 6: sales and service processes within IBM, then you know our
Speaker 6: use of the generative AI capabilities that they're infusing into sales,
Speaker 6: cloud service, cloud slack, et cetera will be something that
Speaker 6: will become really important to us driving productivity within the company.
Speaker 6: And then the other thing that I would say is,
Speaker 6: you know, as I think about the work that we
Speaker 6: do with clients, you know, as they're implementing and on
Speaker 6: their generative AI journeys, you know they're going to utilize
Speaker 6: and leverage the salesforce capabilities within the platform and their
Speaker 6: generative AI technologies. But then you start thinking about processes
Speaker 6: and workflows that run beyond the walls of CRM right
Speaker 6: that run into supply chain and into the finance area
Speaker 6: of the organization. And so there is work that we're
Speaker 6: doing with clients where we're using ibms. What's the next
Speaker 6: platform to be able to help get access to to
Speaker 6: generate insights from data sources that sit in all of
Speaker 6: these kind of back office areas of the enterprise and
Speaker 6: to be able to get that data across the salesforce,
Speaker 6: into these customer interaction points and into the employees who
Speaker 6: are servicing those customers using salesforces AI and generative AI technologies.
Speaker 6: So there's a kind of one plus one equals three
Speaker 6: kind of you know, better together, you know, and being
Speaker 6: able to bring our technologies together in service of these
Speaker 6: clients problems as you think about these processes that run
Speaker 6: across their enterprise. So yeah, so huge hut unity and
Speaker 6: what we're doing together in the market to help clients.
Speaker 5: Yeah, building on that, it is a huge moment for
Speaker 5: organizations and for technology companies like Salesforce, and we couldn't
Speaker 5: be happier to have partnerships like we have with IBM.
Speaker 5: Like the range of thought leadership that is appropriate at
Speaker 5: the moment is everything from what is that hypothesis of
Speaker 5: value and what are those use cases? And what is
Speaker 5: the order of operation in terms of approaching it just
Speaker 5: in terms of focus, but then things that would help
Speaker 5: organizations assess their AI readiness and then their approach Like
Speaker 5: you know, we talked earlier about frameworks and guardrails. You know,
Speaker 5: what are use cases that we're comfortable with given the
Speaker 5: state of the technology that face employees or face customers.
Speaker 5: So creating these much larger roadmaps in terms of how
Speaker 5: to approach this over a series of initiatives, the way
Speaker 5: it can fundamentally change the way we engage with technology
Speaker 5: and what that means for the you know, training and
Speaker 5: change management and use cases that fundamentally shift how you
Speaker 5: engage with systems like Salesforce. There's just a massive opportunity
Speaker 5: for us together.
Speaker 4: So you're talking in sort of general terms, I'm interested in,
Speaker 4: you know, thinking in particular about the way generitive AI
Speaker 4: can essentially lead to better business outcomes, right Like, what
Speaker 4: does that look like? How do you measure it? You know,
Speaker 4: there's a certain bottom line question there, right like, how
Speaker 4: does AI make businesses work better? And in what ways?
Speaker 5: You know, as consumers of products and services, we all
Speaker 5: love and respect great service, you know, in terms of
Speaker 5: getting timely, quick answers, resolving issues quickly, all those those
Speaker 5: types of things. And from the perspective of using generitive
Speaker 5: and predictive capabilities for agents who are interacting with customers,
Speaker 5: there is just a whole ton of opportunity to take
Speaker 5: friction out of the process in terms of finding answers,
Speaker 5: resolving issues, in terms of using these generatives capabilities that
Speaker 5: will bring you know, answers and content to the fingertips
Speaker 5: more easily to the human agents that are working with customers. Now,
Speaker 5: taking that to the next step, for organizations when they're
Speaker 5: ready to move into more customer facing automation. That's yet
Speaker 5: another channel. As a consumer, we'll all enjoy with the
Speaker 5: brands and the products and the services that we want
Speaker 5: in terms of fast answers and resolutions to customers, and
Speaker 5: as we all know, great customer experience yields return business.
Speaker 5: Now on the sales side, you know, maybe a different example,
Speaker 5: and these are areas where I think the capability of
Speaker 5: predictive and generative go very well together in terms of
Speaker 5: focusing on business outcomes. And a classic example would be,
Speaker 5: you know, predictions that help us understand customer health. You know,
Speaker 5: is this customer engaged, is this customer at risk? Predictions
Speaker 5: that help us understand next best product or next best conversation.
Speaker 5: These all help focus sales team's time on a customer
Speaker 5: or a territory, and so that deep focus puts all
Speaker 5: the wood behind an arrow, so to speak, in terms
Speaker 5: of where we should be engaging. And those types of
Speaker 5: driven sales organizations that have these capabilities just lead to
Speaker 5: better performance and outcomes and customer experience too. Now, let's
Speaker 5: also layer in generitive capabilities, where we're using the generative
Speaker 5: capabilities to assist and augment a sales team where we're
Speaker 5: using the power de generitive for everything like generating personalized
Speaker 5: and relevant customer interaction content, for example, leveraging our customer
Speaker 5: data like engagement history, product purchases, service history to create
Speaker 5: an email or a campaign. And this scale of automation
Speaker 5: has just never been possible before. And you know, maybe
Speaker 5: even taking this one step further with genitive where we
Speaker 5: take all the administrative friction out of the day job
Speaker 5: doing things for sales teams like summarizing their calls or
Speaker 5: creating a meeting plan for them, and you know, very
Speaker 5: broadly speaking, using generative AI to change the interaction mode
Speaker 5: with systems like Salesforce from clicks and training where people
Speaker 5: have to focus on the process to more conversational user
Speaker 5: experiences which are much more engaging and easier to use.
Speaker 5: So all of this together is just incredible and transformational
Speaker 5: and makes all businesses and people work better.
Speaker 4: So I just want to spend one more moment on
Speaker 4: the partnership between IBM and Salesforce and generitive AI. And
Speaker 4: there's this phrase that's interesting to me. It's ecosystem partnership
Speaker 4: that I think is relevant here. So what is an
Speaker 4: ecosystem partnership and why is it helpful in creating scalable
Speaker 4: AI solutions.
Speaker 6: This idea of being open, I think is probably one
Speaker 6: of the most important premises for US as technology companies,
Speaker 6: for us as consultancies and system integrators, and for our clients.
Speaker 6: To think about the sources of value that can be
Speaker 6: created through taking an open approach is hugely important. So
Speaker 6: if I think about for US, ecosystem means making sure
Speaker 6: that we have all of the different partnerships that we
Speaker 6: need with technology providers, with service providers that we can
Speaker 6: bring to our clients the right set of capabilities to
Speaker 6: solve the problem that they've got, and not thinking that
Speaker 6: just you know, what we have in house, or what
Speaker 6: we have with just one other partner that we work with,
Speaker 6: you know, is the right thing. And so you know,
Speaker 6: I think every problem that our clients have is solved
Speaker 6: through a range of technologies that come together in service
Speaker 6: of creating that business outcome.
Speaker 4: I want to touch briefly on ethics and governance. Something
Speaker 4: like eighty percent of CEOs see explainability, ethics, bias, trust
Speaker 4: as major concerns on the road to AI adoption, and
Speaker 4: so I'm curious how business leaders navigate these things, and
Speaker 4: in particular, how Salesforce and IBM are building these concerns
Speaker 4: into how they work with customers.
Speaker 5: You know, we've been incorporating predictive machine learning into our
Speaker 5: products since mid last decade, and at that time we
Speaker 5: started with all of our ethics and governance work at
Speaker 5: that time in terms of frameworks for engaging with AI
Speaker 5: and ethical and safe ways, and have a lot of
Speaker 5: guidance for customers in terms of those programs. The machine
Speaker 5: learning focus that we've had at Salesforce has always been
Speaker 5: deeply focused on explainability. So if we're making you know,
Speaker 5: predictive recommendations to explain how we got to that, you know,
Speaker 5: whether that's something that a user sees as they're engaging
Speaker 5: with it, they have full trust in terms of interacting
Speaker 5: with it, but also for the practitioners who are building it.
Speaker 5: So we have this like long standing vibe and capability
Speaker 5: with our predictive side of the house and on the
Speaker 5: generative side of the house. You know, the state of
Speaker 5: the marketplace right now is llms for most people are
Speaker 5: largely black boxes in terms of not fully interpretable in
Speaker 5: terms of how they come up with their content. Now
Speaker 5: that said, there is a lot that you can do
Speaker 5: in terms of audit, in terms of you know, transparency,
Speaker 5: in terms of what are the prompts that are being
Speaker 5: submitted to these llms, what do these llms provide back
Speaker 5: in terms of return, and then what did the human
Speaker 5: do to change it, use it, or adjust it. So
Speaker 5: we've been updating all of our ethics and governance frameworks
Speaker 5: now I guess I would call it with safety components
Speaker 5: as well, in terms of how to work with data
Speaker 5: in safe ways and with these turned parents governance models.
Speaker 6: Yeah, So I mean this is an area that IBM
Speaker 6: has been kind of working on for many years. And
Speaker 6: so you know, our AI Ethics Board that we have
Speaker 6: internally kind of governs and provides frameworks and guidance for
Speaker 6: everything that we do in the company. There's a lot
Speaker 6: of work that we do to help our clients and
Speaker 6: organizations establish their strategies for AI governance as well as
Speaker 6: their own internal policies, models, approaches, ethics boards, et cetera.
Speaker 6: And so you know, helping them put in place these
Speaker 6: ground rules and guardrails, organizational process changes, et cetera. I
Speaker 6: think is a really important part of this scaling discussion.
Speaker 6: That we were having earlier, as people are going to
Speaker 6: be kind of rolling out more of this technology internally,
Speaker 6: and then I think there's a lot that organizations are
Speaker 6: going to have to do to think about, especially in
Speaker 6: the generative world, around all of the different types of
Speaker 6: models that they're using, models that they're training and tuning
Speaker 6: and building, and how they manage all of those for
Speaker 6: explainability and bias drift, and actually regulatory requirements, Like if
Speaker 6: you think about what's happening around the world, there's different countries,
Speaker 6: the EUAI Act, you know, there's lots of different regulatory
Speaker 6: requirements that are going to be coming in, and so
Speaker 6: for multinational companies operating across multiple countries, how they're going
Speaker 6: to have to make sure that they're complying with all
Speaker 6: of not only their own internal policies, but the requirements
Speaker 6: of the country as well as potentially industry regulatory requirements
Speaker 6: as well.
Speaker 7: And so there's a lot that.
Speaker 6: We are doing and going to be doing in helping
Speaker 6: them manage complexity. But IBM has a very firm view
Speaker 6: that we believe that this is all about regulating AI risk,
Speaker 6: not AI algorithms, and so focusing on precision regulation.
Speaker 7: So you know, use the bodies and regulatory bodies that.
Speaker 6: Are out there to provide the control as opposed to
Speaker 6: trying to regulate the technology.
Speaker 4: So genitive AI is changing kind of absurdly quickly. Right,
Speaker 4: a year and a half ago, we wouldn't have been
Speaker 4: having this conversation. We're here today. Everything's happening now. I'm
Speaker 4: curious what you both think about about the near term
Speaker 4: future of genitive AI. Right, if we came back in
Speaker 4: a year, or let's say two years from now, if
Speaker 4: we came back two years from now to talk about
Speaker 4: the work you're doing in genitive AI, what would we.
Speaker 7: Be talking about.
Speaker 5: I use this example sometimes I have three kids, and
Speaker 5: I don't think any of them have ever gone into
Speaker 5: a bank to deposit a check. Right, They pull out
Speaker 5: their mobile phone and they scan the check with the
Speaker 5: camera and they're done.
Speaker 4: I'm surprised that they even know what a check is,
Speaker 4: for the record.
Speaker 5: But yes, well yeah, sometimes their parents give them one,
Speaker 5: like they get direct deposit. But anyway, like this experience
Speaker 5: of like, what do you mean a go into a
Speaker 5: branch in cash at check? Just do this with my
Speaker 5: mobile phone? And I think a little bit of it
Speaker 5: that way in terms of the systems that we use
Speaker 5: at work. I can imagine explaining to my kids, like, oh, yeah,
Speaker 5: at Salesforce, you know, back when someone had their first
Speaker 5: day on the job, you know, as a service agent
Speaker 5: or as a salesperson, they would have tabs on the
Speaker 5: screen and they would be trained where to click, and
Speaker 5: they'd have documented processes in manuals, and that showed them
Speaker 5: where to get from point A to point B. And
Speaker 5: as the clock turns forward, they're just interacting with the
Speaker 5: natural language prompt. But it just kind of fundamentally changes
Speaker 5: the way we'll be able to interact with our systems
Speaker 5: or record at work.
Speaker 4: It'll be just much more conversational. Instead of clicking through something,
Speaker 4: you'll just basically have a conversation.
Speaker 5: Much more conversational.
Speaker 6: Yeah, this is the biggest paradigm shift in how we
Speaker 6: interact with technology I think since the invention of the
Speaker 6: graphical user interface, and it's going to enable us to
Speaker 6: almost put us all of that complexity within organizations around
Speaker 6: system silos, process silos flows, because you're just going to
Speaker 6: layer this just simple natural language interface over all of
Speaker 6: that complexity.
Speaker 7: Yeah, it's going to amplify.
Speaker 6: I think the potential of every person on every team
Speaker 6: in a way that we've never been able to see before.
Speaker 6: And the other thing that I think as you project
Speaker 6: forward in a couple of years, and Susan just picking
Speaker 6: up on the point that you talked about about banking,
Speaker 6: you know.
Speaker 7: I think there's a wonderful little example.
Speaker 6: Look, if you think back to the seventies and the
Speaker 6: eighties when the ATM kind of cash machines were rolling out,
Speaker 6: and at that time, it wasn't really a reaction that
Speaker 6: was one of awe or appreciation for convenience, but people
Speaker 6: were concerned that we were automating away the bank teller jobs.
Speaker 2: Right.
Speaker 6: But now, when you think about it, what actually happened
Speaker 6: was this technology allowed the banks to scale their branch networks,
Speaker 6: more branches never before, more bank tellers than ever before,
Speaker 6: teler employment and salaries increased, even though we automated them
Speaker 6: out of work, because when they weren't having to spend
Speaker 6: their time counting cash out for people, they were able
Speaker 6: to do more valuable things, right, and new types of
Speaker 6: financial products and services and mortgages and so like. If
Speaker 6: I think back to that in the seventies and eighties,
Speaker 6: and then I project to where we are today, we're
Speaker 6: just going to unleash this creativity and potential for employees
Speaker 6: and enterprises by freeing up the time that they're spending
Speaker 6: on things that you know, they can do far more
Speaker 6: value added tasks. And so I think we're going to
Speaker 6: be amazed. I think around what happens and what companies
Speaker 6: and people are going to be able to do as
Speaker 6: we give them the time and space to be able
Speaker 6: to do that great.
Speaker 4: So, just to close, I want to talk about how
Speaker 4: both of you use creativity in your own work. Just
Speaker 4: to start with you, Matt, I know that you love
Speaker 4: to combine creativity and technology through design. Do you use
Speaker 4: generative AI in your own creative process?
Speaker 7: Yeah?
Speaker 6: So, I I'm a firm believer that this combination of
Speaker 6: experience in AI is going to be the thing that
Speaker 6: makes a difference. Like these large language models, and this
Speaker 6: technology has been around actually for a number of years,
Speaker 6: and it's only at the point late twenty twenty two
Speaker 6: where open AI wrapped a digital experience around this and
Speaker 6: put it in the hands of people that suddenly the
Speaker 6: transformative power of this technology was realized. And so I
Speaker 6: think the way that we surface these capabilities and put
Speaker 6: them in the hands of people to be able to
Speaker 6: adopt it in a really frictionless way is the thing
Speaker 6: that's going to be hugely important to the adoption and
Speaker 6: scaling of this. So I think the most important thing
Speaker 6: for companies to do is to make people, not technology
Speaker 6: central to their strategy.
Speaker 4: Just to go more broadly into your work, Susan, I mean,
Speaker 4: I know that you have launched Salesforce's AI products into
Speaker 4: the market, and that you know a lot of those
Speaker 4: have been built obviously given Salesforce business around helping people
Speaker 4: build stronger customer relationships, right, And so I'm curious what
Speaker 4: creativity did you bring to that work.
Speaker 5: Some of the products that I've worked with a Salesforce there,
Speaker 5: they're deeply visually focused. And my personal perspective is is
Speaker 5: that the world can be really noisy. We're just inundated
Speaker 5: with all sorts of demands on our time through so
Speaker 5: many channels. Right, Like the phone is firing off, you're
Speaker 5: getting instant messages, you're getting slack messages, you're getting you know, dms,
Speaker 5: you're getting emails, your phone is ringing. There's processes that
Speaker 5: are bearing down on you. And if we can use
Speaker 5: really good design to filter out and essentially weed the garden,
Speaker 5: because you know, we have this this phrase at Salesforce
Speaker 5: is everything. If everything's important, nothing's important. So using really
Speaker 5: good design to create the user experience in Salesforce, that
Speaker 5: just brings stuff to life in the most powerful way.
Speaker 5: So I always think of it from that perspective, like,
Speaker 5: if I'm going to put this on a screen and Salesforce,
Speaker 5: what did I not put on? Is this the most
Speaker 5: important thing? And is this the thing that's going to
Speaker 5: align everyone to the larger initiative of the firm. So
Speaker 5: it's that kind of design thinking that I use probably
Speaker 5: every moment of the day, whether I'm building a demo
Speaker 5: or talking to an executive as a company in terms
Speaker 5: of as I see a vision for how they might
Speaker 5: deploy our products to actual product development.
Speaker 4: Just to kind of bring together these two themes we've
Speaker 4: been talking about, on the one hand, the sort of
Speaker 4: ecosystem partnerships and on the other hand, creativity, I mean,
Speaker 4: can you talk a little bit about how working with
Speaker 4: partners can foster a different kind of creativity.
Speaker 5: More perspectives are always better than few perspectives.
Speaker 7: I completely agree.
Speaker 6: I think the more minds, the more perspectives, the more experiences.
Speaker 6: You know, if I think about some of the best sessions,
Speaker 6: best workshops, best work we do with clients when you've
Speaker 6: got people not just from one industry, but from many industries,
Speaker 6: because actually the adjacencies and the things that are happening
Speaker 6: in these other spaces trigger new thoughts and new ideas,
Speaker 6: and so, you know, I think the richness that we
Speaker 6: get when we partner with salesforce together around helping clients
Speaker 6: transform their front office, their sales service marketing processes. We
Speaker 6: all bring these unique experiences, and I think that just
Speaker 6: opens the aperture to better outcomes and better perspectives for
Speaker 6: our clients.
Speaker 5: Well, you know, you've been asking these questions about like
Speaker 5: the use of tech and AI and creativity are sort
Speaker 5: of in the same sentence. And one of the things
Speaker 5: that I also think of is in terms of remaining
Speaker 5: deeply creative, is the actual process of unplugging from all
Speaker 5: that stuff. So taking a trail run with no earphones
Speaker 5: in your head, for me, is always a really good
Speaker 5: way of unleashing and writing a lot of creative spirit.
Speaker 5: Just that downtime and the unstructured time where your brain
Speaker 5: can just run free, actually not assisted by any kind
Speaker 5: of device in my head or in my face.
Speaker 4: So I think with that praise of unplugged time, we
Speaker 4: should say goodbye and let's unplug it. It's lovely to talk.
Speaker 3: With you guys.
Speaker 4: It was really interesting to learn about your work and
Speaker 4: the relationship between the company. So thank you for your time.
Speaker 7: Thank you, Jacob, thank you.
Speaker 3: A huge thanks is due to Jacob, Matt and Susan
Speaker 3: for illuminating the possibilities of generative AI. This technology has
Speaker 3: great promise for creating new experiences in the future, but
Speaker 3: requires the scaling capabilities made possible by partnerships like IBM
Speaker 3: and Salesforce. As our conversation with Susan and Matt illustrated,
Speaker 3: we're at an exciting phase of adoption. Most companies have
Speaker 3: moved beyond experimentation and are now prioritizing scaling. The key
Speaker 3: areas of focus for organizations now include managing multiple AI models,
Speaker 3: as well as thinking about specific use cases and desired outcomes. However,
Speaker 3: this scale is difficult for companies to do on their own.
Speaker 3: To unlock the real potential of generative AI in transforming experiences,
Speaker 3: they'll require the scaling capabilities made possible by partnerships like IBM,
Speaker 3: and salesforce. This conversation showed the promise of teamwork. When
Speaker 3: massive companies combine their brain power to push forward technology,
Speaker 3: their collaborative efforts have the potential to revolutionize industries. One
Speaker 3: quick programming note, we will be taking a little time
Speaker 3: off and will be returning in just a few weeks
Speaker 3: with a new episode. Smart Talks with IBM is produced
Speaker 3: by Matt Romano, Joey fish Ground, David Jaw and Jacob Goldstein.
Speaker 3: We're edited by Lydia gene Kott. Our engineers are Jason Gambrel,
Speaker 3: Sarah Bruger and Ben Holliday. Theme song by Gramoscope. Special
Speaker 3: thanks to Andy Kelly, Kathy Callahan and the eight Bar
Speaker 3: and IBM teams, as well as the Pushkin marketing team.
Speaker 3: Smart Talks with IBM is a production of Pushkin Industries
Speaker 3: and Ruby Studio at iHeartMedia. To find more Pushkin podcasts,
Speaker 3: listen on the iHeartRadio app, Apple Podcasts, or wherever you
Speaker 3: listen to podcasts. I'm Malcolm Gladwell. This is a paid
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