Transcripts
Hey Megan, let's do a podcast. Great idea. What
Speaker:should we talk about?
Speaker:Today we are talking about the Design and Implementation
Speaker:Enablers section of the AI Implementation
Speaker:Canvas. Megan, one of the things that I've heard you talk about with
Speaker:the AI Implementation Canvas is that it's a capability
Speaker:builder as much as a practical tool for a single
Speaker:implementation. It strikes me that this section of the canvas
Speaker:embodies that capability-building aspect more than any of
Speaker:the other ones. Yeah, I think I agree with you 100%. Well, no,
Speaker:"I think I agree with you 100%"? I totally agree with you 100%.
Speaker:The design of the
Speaker:Canvas is such that you use the Canvas for every implementation
Speaker:in an organization, and that
Speaker:means you might be using it a lot if you have a lot of things
Speaker:going on. And the more that you use it, and the more the team
Speaker:uses it, the more natural it's going to become to raise these
Speaker:questions and have these conversations. In the early days of gen
Speaker:AI release at Torrance Learning, our pilot teams... I think
Speaker:we had six teams at one point each using a Canvas. And
Speaker:that built in
Speaker:early on the practice and the routine of thinking
Speaker:around all these questions, these 14 planning dimensions, so
Speaker:that the team in future implementations can be arriving
Speaker:at each of these conversations faster. They're like, ah, I've been here before, done
Speaker:that. But when we get into design and implementation
Speaker:enablers, that's really about how do we start from
Speaker:pilots, make thoughtful selections, and then
Speaker:scale the projects that make sense scaling. So this is
Speaker:one in which we're using the Canvas a lot
Speaker:and really, really leveling up the entire game. Design
Speaker:and Implementation Enablers is just one of the four sections.
Speaker:There's Strategic Foundations, there's Technology & Experience
Speaker:Infrastructure, there's also Human-Centered Adoption & Change, which will be another
Speaker:conversation. That'll be a good one. Yeah, looking forward to that.
Speaker:You mentioned pilots. I mean, so many pilots when it
Speaker:comes to anything AI related. I've heard even
Speaker:the term "random acts of AI." So how do organizations
Speaker:pilot things efficiently and how do they figure out what
Speaker:pilot projects make sense to move forward? This
Speaker:is done in a number of different ways, but I think
Speaker:some of the most informed approaches I've seen
Speaker:have been almost like new product development.
Speaker:And there are a number of opportunities to get
Speaker:engaged, and they bring in.... One of the companies that I
Speaker:researched for the book had a very structured
Speaker:process by which they had a bunch of different pilots. Anybody could
Speaker:submit an idea, and then ideas were vetted with some
Speaker:criteria that were consistent across the organization so
Speaker:that everybody's idea got a look,
Speaker:but also that perspective and that feedback from that consistent
Speaker:rubric. And then things that passed that first look got a little bit of time
Speaker:and a little bit of funding to create a
Speaker:prototype and to experiment a little bit. They also got support from the
Speaker:organization. Can you imagine an organization of thousands
Speaker:of people and everybody's got an idea about how to use AI a different way?
Speaker:It's really hard from a governance perspective and keeping track of where is
Speaker:our data and what's going on. So how do you resource that and provide each
Speaker:one of those teams with some support? Requires a lot of transparency and
Speaker:communication. So when you make it
Speaker:okay to experiment, provide structured avenues and
Speaker:support for experimentation, you then
Speaker:bring all of those little random pockets in the organization that don't know
Speaker:what the other part is doing, brings them together and
Speaker:allows them to have a much more structured and organized
Speaker:approach to having a lot of innovation going on at once.
Speaker:Yeah. Another planning dimension you have here is
Speaker:scaling and integration. And when I think about
Speaker:scaling, you can think of pilots as like,
Speaker:they could be small scale, but they also could be really large scale.
Speaker:So it's sort of a layer on top of that even
Speaker:and just another dimension to look at. So some AI projects and organizations
Speaker:are going to be really big. They're going to like upend the way that systems
Speaker:and processes work across your org, or
Speaker:that there might be others that are going to be super small, right? Yeah. And
Speaker:I think once a project has been greenlighted to
Speaker:scale, that's not a "send the link to everybody!"
Speaker:kind of moment, right? "Yay!"
Speaker:That sounds dangerous.
Speaker:But because
Speaker:you're right, it's dangerous at that kind of
Speaker:pivot point from pilot to scale, right? If you can go to pilot,
Speaker:generally it may use dummy data, it may be a small portion of the
Speaker:organization, it may not have
Speaker:direct ... it may have a lot of humans sitting around watching it, making sure
Speaker:it's been paying attention. So as we move from pilot to
Speaker:scale, then we start looking at
Speaker:IT and security involvement. We start looking
Speaker:at stress testing and volume
Speaker:testing for products. We may look at,
Speaker:for lack of a better word, kill switch. How do we very
Speaker:efficiently get the signal that this thing has gone awry and turn it
Speaker:off before it causes more damage? And that's actually
Speaker:some of the considerations around projects that we've got. How
Speaker:do we monitor, by a human, maybe even
Speaker:supported with AI, but how do we monitor these things and then make sure that
Speaker:we turn them off if things aren't
Speaker:going well? And what are the rules for that? So there's a lot
Speaker:of considerations around scale.
Speaker:And then I think there's also, like, how do we manage? How do we manage
Speaker:this once it's huge and big and everybody's using it in an organization?
Speaker:So it's a worthy
Speaker:time to have a slowdown, a pause, and a lot of conversation.
Speaker:You used a word when you were talking there. You said the word
Speaker:signal. And that makes me think about measurement and impact
Speaker:as well. I know we've talked in a lot of other episodes
Speaker:that we've done about the importance of measurement. I'm
Speaker:sure there's aspects that we want to measure here too, right?
Speaker:Yeah. One of the things we want to be looking at as we design pilots
Speaker:and then move into scale is what does success look like?
Speaker:How will we know when we have it? And
Speaker:what does success look like for people, for performance, for the organization
Speaker:overall? And
Speaker:this gets tied back to our business goals. What are we trying to achieve
Speaker:here? And are we achieving this? And what happens
Speaker:when we do? Right, so say a goal is to reduce a particular
Speaker:process, reduce the speed it takes to complete that. If we
Speaker:reduce the speed it takes to complete that, what do we do with that extra
Speaker:time? So there's all sorts of
Speaker:considerations here. And some of these things are going to be easy to measure, and
Speaker:some of these things are not going to be easy to measure. But one of
Speaker:the things that learning professionals bring to the table is
Speaker:this focus on measurement and impact. And
Speaker:both in the activity measurements — "are people using it?" The
Speaker:effectiveness measurements — "are they using it well and using it
Speaker:to change their work and outcome metrics?" Like, did it
Speaker:achieve those desired outcomes? So there's lots of
Speaker:opportunities here for us to apply the skills that we have already in
Speaker:learning design and that
Speaker:we could
Speaker:borrow from our learning products into these AI products
Speaker:and projects. When I'm
Speaker:thinking about takeaways here, the first thing that comes to
Speaker:mind is that this is almost about a
Speaker:transition in a way, like we're talking about maybe
Speaker:pilots to scaling and almost a maturity that's
Speaker:taking place in this section of the quadrant. Would you say that's right? I
Speaker:do. Yeah, I agree. And it's even — I think there's
Speaker:both maturity in moving from pilot to implementation with a rigorous
Speaker:measurement, but also maturity in even having those structures
Speaker:in the organization in the first place. Mhm, and having those conversations. What's
Speaker:one more thing you've got for us? You know,
Speaker:one of the things we talk about is like, "where are the people in each
Speaker:of these sections?" And the
Speaker:people here are — what I love
Speaker:about the, especially the experimentation and pilots perspective,
Speaker:is there's innovation and a
Speaker:divergence-of-thinking opportunity to get
Speaker:a lot of people involved and excited and an
Speaker:opportunity for sideline skill development around that.
Speaker:"How do I make a business case?" "How do I present my case?" "How do
Speaker:I team with other people across the organization to be on this
Speaker:part of this project team?" And "how do I connect in with the purpose of
Speaker:my organization by participating in this innovation
Speaker:effort?" So there's a lot there and
Speaker:a lot of really good conversation, I think,
Speaker:to be had. Yeah. I mean,
Speaker:pilots need people. Pilots need people.
Speaker:And feedback, which we can measure. Go figure.
Speaker:All right, Megan, how'd that one go? That was a lot of fun to
Speaker:talk about. It was — I love, you know
Speaker:me, I love a good hackathon. So I get very
Speaker:excited about the experimentation end of things and
Speaker:the prototyping, like, "hey, can we build this thing?" And I know, like, personally,
Speaker:sometimes I get frustrated when you hit what
Speaker:feels like organizational friction
Speaker:to scaling. That friction is there
Speaker:for a really good reason. And so
Speaker:that's important. But it is definitely a gear shift and a
Speaker:speed shift that's important but sometimes hard for
Speaker:individuals to internalize.
Speaker:Instead of friction, I thought you were — you mentioned "antifragile" the
Speaker:other day, and it almost
Speaker:made me think of like, I thought your brain
Speaker:or my brain was starting to go towards, like, "I hit the organizational
Speaker:rigidity." Yes!
Speaker:But yet from an antifragile — right. So let's back up,
Speaker:right? The concept of "antifragile," or "anti-fragility." And we'll
Speaker:put the link to the book in the show notes because it's a concept —
Speaker:I'm super fascinated, right? So one of the
Speaker:core themes here is that things that are fragile,
Speaker:when you push up against them, they break.
Speaker:Your pilots might be fragile. Right. It's a prototype. It's
Speaker:not built out and robust. Things that are rigid,
Speaker:when you push up against them, they also break. They push back
Speaker:or they stop. That's not healthy either. And then
Speaker:things that are antifragile, when you push up against them, they actually get
Speaker:stronger. And it helps the team get stronger, it helps the organization and the process
Speaker:gets stronger. So that pushback from the organization — at
Speaker:scale, at governance, at bringing the security people and
Speaker:looking at the wider impacts — absolutely makes an
Speaker:idea stronger. This is Meg Fairchild and
Speaker:Megan Torrance, and this has been a podcast from
Speaker:TorranceLearning. Tangents is the official podcast of
Speaker:TorranceLearning. (As though we have an unofficial one.) Tangents
Speaker:is hosted by Meg Fairchild and Megan Torrance. It's
Speaker:produced by Dean Castile and Meg Fairchild, engineered and
Speaker:edited by Dean Castile, with original music also
Speaker:by Dean Castile. This episode was fact checked
Speaker:by Meg Fairchild.
