This audio was created using Microsoft Azure Speech Services

Bees and unicorns of the AI world

In the second episode of the AI at Scale podcast we welcome Allison Sagraves, AI and Data Advisor, Chief AI and Data Officer Faculty at Carnegie Mellon University, beekeeper and forest steward. The main topic of the episode is the discussion about today’s search for AI unicorns – not only among start-ups, but also C-level executives and AI experts. 

In the show, Allison talks about the current importance of Chief AI Officers in business. She describes their collaboration with Chief Data Officers, as well as shares top three skills to have to be a successful CAIO. As an extra, she reflects on her project with bees, which inspires Gosia, the host of the show, to bring the topic of the underrepresentation of female talents in STEM. 95% of bees living in the hive are females! In comparison, women now make up 26% of the STEM workforce. The conversation ends with an advice given to today’s aspiring female Chief AI Officers, and anybody who want to successfully land a job in AI. 

Listen to the second episode of the AI at Scale podcast.  

Listen to Allison Sagraves: Bees and unicorns of the AI world episode. Subscribe to the show on the preferred streaming platform (Spotify, Apple Podcasts) or play the episode on YouTube.  

Transcript

Gosia Górska: Hi, I’m Gosia Górska, and I’m the host of the Schneider Electric AI at Scale podcast. I am pleased to introduce my second guest, Allison Sagraves, board member and advisor in several companies in the past, and now adjunct faculty of the Chief Data Officer program at Carnegie Mellon University. She is a data and tech consultant and a recognized authority on data and analytics strategy, who advises startups, companies, and leaders on data monetization, AI, and strategy. Welcome, Allison. Thank you for joining the show. 

Allison Sagraves: Happy to be here. 

Beekeeping as a digital detox

Gosia: In this series, we discuss AI stories, and we certainly will in this episode as well. However, I would like to start with something else, with the two big words: technology and digital. Today we hear various stories, and even ourselves, we are using a lot of digital applications. We are very connected, and we see how all these new technologies are really simplifying our lives and helping us. 

On the other hand, people run away from the digital world. There is a growing interest in turning to roots, to nature, and we want to feel present here and now. I have this impression of kind of detoxifying from all the time spent digitally. And I’m introducing this because I know that you have a unique idea to do that. Is that right? 

Allison: I’m talking to you from my cabin in the woods. It’s actually a beekeeper’s cabin because I actually keep bees. I decided that being a Chief Data Officer for several years and also raising a family—my kids finally reached adulthood—and so my husband and I bought this cabin in the forest, and it’s where I go to detox from this very digital world. 

It’s such an antidote to the hyper-technical world that we live in and I come here to refresh and recharge and really think about what’s going on. There’s so much change that’s happening. Also, my hobby is to be a beekeeper. 

Gosia: Yes, exactly. Is there any particular reason why bees, then? What is so fascinating and special about them? 

Allison: You know, bees have a very kind of mysterious and almost poetic… They’re so interesting. I just became fascinated with bees, and then I became a beekeeper—not out of some great love for insects, trust me—but I really wanted to understand, like, what goes on in a hive. Like, who are these… You know, bee colonies are 95% to 99% female. 

So when I bought the cabin, my first task was to obtain some bees, and I actually started out—my minimum viable product was I got two hives. I started with two hives, and now I have a small apiary, and my bees produce raw honey, which I sell to customers all across the U.S. And I even have people that are using it for medicinal purposes, and my honey is used in a clinical trial. 

Gosia: Wow, that’s really fascinating. And I can still see this passion for data in the way that you take care of the bees. And it’s quite funny because our headquarters in Paris is also called La Hive, and we also have beehives on the roof of the building. It really brings us to the topic of our conversation. 

The evolving role of Chief AI Officers

Gosia: So, artificial intelligence—this is actually the way that we are even more connected today because we have so many opportunities with AI. My first question related to this topic that I wanted to ask is, what has changed in comparison to last year? Why has the role of Chief AI Officer—that, by the way, is exactly located in Le Hive in this building—why has this role become so important this year? 

Allison: Well, you know, it’s interesting because we’ve been using AI—I come from a financial services background in banking, and we’ve been using AI for a number of years with kind of more traditional AI. But I really think the onset of Gen AI, with all of the publicity around ChatGPT and so forth, the capabilities have really exploded and gotten into the public domain. 

So now there’s such strong interest and really need to apply these technologies in an organized way. And I really think that CDOs, in a way, were foundation setters. We set the foundation for this era, which we didn’t fully anticipate. But a lot of the things that I started to put in place, as did others in my timeframe, these foundational capabilities around data have become essential now for the age that we’re in. 

So it’s a very exciting age, and we really need people to apply these capabilities in responsible ways. I mean, the world is at a huge, huge inflection point. 

Gosia: Yes, I think that’s a very good observation that we definitely needed this foundation of data in many companies, like basic digitization as well. And now where we have this new technology, we can really reap the benefits out of this data foundation. 

But interestingly, you recently wrote an article for Harvard Business Review with an interesting title, “Why Chief AI Officers Are Doomed to Fail.” And I wanted to ask about this article because we see a massive recruitment effort for Chief AI Officer positions across the world, and especially in the U.S. After the publication of President Biden’s administration executive order that obligates all federal and state organizations to designate an AI-dedicated person, I’ve seen some estimates that even up to 400 new Chief AI Officers will be appointed. 

So now this new cohort of Chief AI Officers asks themselves the question, how do I succeed? Where should they start? 

Allison: You know, I think we’ve kind of learned through various cycles of having Chief Data Officers, Chief Digital Officers, this notion that a person is going to be able to mobilize an entire company and effect transformational change. I think we have a more nuanced understanding of how change occurs and that we are all responsible for change. And I’ll talk about that. 

But I think I actually came up with an acronym for a framework relating to bees. Because how is it that bees mobilize and scale in nature? They swarm. So here’s my acronym for how a Chief AI Officer can set up to succeed using the SWARM acronym. 

So first, Strategy and Vision—that’s our S. Then Win Support—W. Assess and Optimize—A. Roll Out Ethical Governance—R. And Mobilize and Scale—M. And let me just talk a little bit about each of those. 

So first, I think it’s important to really, from a strategy perspective, understand what are your organization’s goals and objectives. How does AI help advance those goals and objectives? I think we sometimes focus first on the capability and then figure out how it can—and we think it’s going to save everything. It’s really in reverse. One of my favorite people, Cassie Kozyrkov, says, “What’s the problem you’re trying to solve?” So I think we need to start with that and then come up with an AI vision that really drives the organization’s strategy. 

So that’s the S, and then W—Win Support. Relationship building is so important. The collaboration across an enterprise with business stakeholders, functional stakeholders, all of the typical areas—legal, compliance, risk, technology—it’s such a collaborative function. So winning support is critical, and a lot of time needs to be spent there. 

Assessing and Optimizing—what are your capabilities today? Do you have talent issues? What are your gaps? Rolling Out Ethical Governance—really, before you can implement anything, you need to have policies and frameworks. And then Mobilizing and Scaling—I think we’ve learned through earlier eras that it’s important to pick a few kind of like lighthouse projects that you will start to show value and learn from and then adapt and scale. 

So I think we’ve kind of learned what the model for transformation needs to look like. So that would be my advice for the first hundred days for a Chief AI Officer. 

Gosia: Yeah, I’m sure that they will appreciate this advice, and it really sounds very well-founded in your own experience as well within the data foundation building, and especially that these people, in some of the cases, will enter a completely new organization, right? Because previously there was no function like this. 

So they have to definitely build a team. This networking, collaboration seems really, really important, and probably this will be one of the challenges that they may face when they enter the organization, right? So I really like this model, and I guess it’s going to be very useful for our listeners. 

Collaboration between AI teams and business 

Gosia: Now, as you were Chief Data Officer for many years, and now you also run Chief Data Officer certification programs, how do you see exactly the cooperation between Chief AI Officer and Chief Data Officer? How can Chief Data Officers support Chief AI Officers? 

Allison: Well, it’s a very, very symbiotic relationship. I think this applies really to kind of larger, more mature organizations to have really both of those roles. But I think a good way that it could work is to really view the Chief Data Officer as being in charge of data as a raw material. 

The Chief Data Officer typically oversees data governance, data quality, and data lifecycle management. They ensure that data is accurate and accessible and secure, and they’re responsible for building out the data infrastructure. So it’s really now the Chief AI Officer who can leverage this data to deploy into AI models that help advance the organization’s goals. 

And the Chief AI Officer, I would say, is also responsible for the ethical and responsible use of these models. So they really work together. I’d say a way to think about it is the Chief Data Officer ensures that the raw material supply is good to be deployed and manufactured, so to speak, with the AI Officer, and that could be federated across the organization. But I think at this point, we probably want some kind of centralization to ensure that there are standards that are applied across an enterprise. 

Gosia: Yeah, that’s true, but I also was thinking that this would be an ideal situation in which, in a company, we have both Chief Data Officer and Chief AI Officer, so both of them have specific roles, specific responsibilities. But what about smaller companies that not necessarily have this possibility to have both positions? 

Like the company is rather small, and they would like to start implementing AI, starting, as you mentioned, with some real value that they see for their company. If there is one person designated to do both jobs, how do you see this division between these two responsibilities? 

Allison: There’s the component of ensuring that the data supply chain is robust and fit for purpose for applying to the use cases that are going to advance the business. You can be a Chief Data and AI Officer and have all of those responsibilities, and then you would typically have somebody that was responsible more on the governance side and somebody that’s more responsible on the deployment side. 

So those could be separate roles, or it could be put into one structure, but you would just need, I think, some separate support for each of those focus areas. 

Gosia: And you also mentioned in this SWARM model that cooperation basically is very important. Now, if we dig deeper a little bit into the cooperation between the AI teams and the business, how important it is and how to support a situation where generally in a company, the business lacks in collaboration. 

Allison: Yeah. So I think that we are learning as a society and organizations, these organizational walls need to be broken down. And so I think organizations are just maturing in their agility and in their ability to kind of look at things more from kind of like a product level and breaking down and having cross-functional teams. 

So I’d say that those companies that are further along that journey are best poised to be able to adopt AI at this point because they’re organizationally flexible enough and have that sort of collaborative practice to be able to apply to something new. 

I think organizations where they’re not as mature and adaptive and flexible, it’s going to be a little bit harder. But I think that it’s inevitable that we all become adaptive and flexible to be able to deploy innovation that is ultimately going to be so disruptive. So it’s really only a matter of time. 

Gosia: Yeah, that’s right. And I think it’s a proper way of thinking about AI as the innovation. So you need to be prepared for change management. You need to be prepared to boost the adoption of these new tools and help to prepare the whole company. 

So if any company is still working in silos, this will be quite challenging for them to really move on at pace and adopt this new technology. 

Skills required for Chief AI Officers 

Gosia: We discussed a bit about the companies and what are the key success factors for Chief AI Officers. Now, if we look a bit from a different angle, in another article, you also mentioned that AI is a business opportunity, and rather than looking exclusively to technologists for solutions, we should ask, who are the high-performing people across the spectrum who understand business and understand change? 

You mentioned that we need interdisciplinary people, execution-focused problem solvers with the skills and mindset to use AI to solve business challenges, not simply to apply the technology because it’s there. So it’s a quote from the article, and I wanted to follow up on these thoughts from the article to know what would be the top three skills of a successful Chief AI Officer, and how would you prioritize them? 

Allison: Yeah, so I think there are three dimensions that a Chief AI Officer in a large organization needs to cover. I think these are all equally weighted, actually. And for simplicity’s sake, I’ll call them IQ, TQ, and EQ, and I’ll talk about each one. 

So from an IQ perspective—and I’m being somewhat light here—but you really need to have a very keen strategic mind and deeply, deeply understand the business and the competitive landscape and the broader macroeconomic environment and how the world is changing as a result of this. And with that, some experience in terms of execution discipline in a highly fluid environment. 

So that’s one dimension. You’ve got to be battle-tested and have a particular kind of enterprise change-oriented mindset. So that’s one. I’m putting that under IQ, so to speak. 

And then TQ—I think you need to have a technical quotient. I mean, you need to understand the technologies and how they can actually advance your organization’s goals. So a deep understanding of technology and models and how they can be practically deployed for value. So I would say that those are equally weighted elements. 

And then further equally weighted is EQ—having the emotional intelligence. Given the high-stakes nature of AI, we need to have very, very trusted leaders who are excellent communicators and change champions who are strong relationship builders and strong communicators. 

So, you know, these are three things that are—they’re hard to—any one of these things is often hard to find in a person. Trying to find all three—there is a bit of a unicorn aspect to this. But it’s these kind of like whole-brain people that bring the IQ, the technical component, and the people emotional intelligence component. 

I think that we need to put this level of person in such critical roles at this state and where we are. 

Gosia: Okay, so everybody looks for the unicorns right now. Yeah. But I think you’re right about these three dimensions. And I was even thinking about the TQ. You mentioned that nowadays we have so many applications, and the technology is developed at such a quick pace that it’s really hard to follow. 

And a person who doesn’t have this technological background, they may be sometimes kind of blinded or too attracted by the newest technology that is proposed by the shiny demos that are presented. So actually, this capability of being able to see on one side the benefits and potential of these new technologies, new applications, but also the limitations, is quite crucial at this job, right? 

Allison: Yes. I mean, I think especially now with everything changing, there are just so many technologies, there are so many vendors. I think it’s really hard to sort out, but I think that will settle down. I think we’re in kind of an organizing period for a few years. 

But yes, I think it’s important to have a technically adaptive mind that understands how changing technologies can be used to support your underlying organizational model and can help your customers and reduce your cost structure and truly achieve the digital transformation that I think has eluded so many companies in the past few years because we truly just didn’t have the level of tooling that AI is bringing to us to enable the automation that we’ve aspired to. 

Encouraging diversity in tech

Gosia: And I would add even one more challenge to the fact that you already search for unicorns because we still lack women in tech. So unlike in your bees, where 95% you mentioned are females… 

Allison: 95-plus percent. 

Gosia: Exactly! So we don’t see this kind of representation in tech jobs. And the statistics this year are not very optimistic about how companies are progressing with hiring women for these top positions. So do you have any specific advice for female Chief AI Officers? 

Allison: Yeah, well, I think if you’re a female Chief AI Officer, you are already at the table. So please, please take full advantage of this privileged seat that you have. And it’s terrific that we have—to the extent that we have—diverse representation in these roles. I think it’s critical because this is ultimately going to change the way things are organized in our society. So we need all kinds of voices at the table. 

To those who are not at the table yet, in terms of being Chief AI Officers, things are changing so fast that we really have to take it upon ourselves in many ways to learn and pay attention to the things that interest us. So my call to action is everybody who wants to be engaged in the economic ecosystem needs to really start to understand how can I start applying AI to improve my personal productivity. That’s something that we can all be doing today. There are things that I do integrate into my day. 

I think women have been socialized to some extent—I can say this for myself—to think that we need to check every box in a role. You know, I just described a bit of a unicorn role, and I think we all need to just have a lot more courage and experiment. You know, I was not a certified master beekeeper when I got my bees and started the hives. How I learned was I got stung, and I had some crazy stuff happen to me. So I think we all just need to be emboldened. 

I think of when I was young—I was raised some time ago, so this was unusual at the time—but my father was teaching me how to golf, and he kept saying to me, “Swing at it, swing at it,” because he knew that I had a lot of potential, and he knew that I could take more risk and get better results. So I’ve used that as a bit of a metaphor in my life: Am I swinging at it? Am I giving it my all? 

So I encourage—and this applies to everybody, but I think women especially—take more risk. We need you. You have more power than you think. Create your own table. Become engaged at your organization, at your schools, in your community. This is a “we” thing. We don’t have—it’s not about the few people at the top deciding for everybody. We all have a role to play in how our society will change as a result of this level of disruption and change in technology. This is a once-in-a-lifetime moment. 

Gosia: Yes, I totally agree. I think it’s a lifetime opportunity to also be engaged, and especially that AI technology is evolving and it’s being developed as we speak. There is plenty of opportunity for everyone to be involved and to be part of this. So it’s definitely a moment not to miss for everyone. 

And if we could give also some real-life examples for the ladies and also for any other people who are interested in AI careers and AI opportunities, do you have from your experience any example of a particular successful AI application that was driven by a visionary Chief AI Officer or very effective Chief Data Officer? 

Allison: Well, yes. So coming from the banking sector, I just chaired a panel at a conference, and on my panel was a woman who is in charge of innovation and fintechs at one of the largest banks in the country. And we were talking about what’s being deployed at her organization, and we talked about this idea of “boring is the new sexy.” 

And it’s funny because as I’m leading this panel, I’m thinking I wouldn’t have expected one of the top banks in the country to be talking about how AI is being used in boring ways. And she went on to talk about how AI—and I know this from being in banking—that AI has been used already for years in things like fraud, anti-money laundering, cyber, lots of predictive analytics kind of in the defensive space, like those capabilities that I just mentioned, and operational automation and so forth. 

And that’s where I think a lot of the activity is, let’s say, in financial services, in these more sort of back-office operational areas, primarily because it’s a heavily regulated sector, and it’s hard to apply something like Gen AI to loan decisioning at this stage because of the regulatory infrastructure. There’s an example from financial services of a visionary innovator. 

Gosia: Yes, and I also like this tagline that “boring is the new sexy,” because I think we—as we mentioned, sometimes we can be blinded by the newest technology, the newest applications, while actually there is a whole AI technology that kind of—we can call it traditional AI technology—that was already deployed some years ago. 

It works perfectly, and we can find many use cases that are maybe undiscovered in our companies to put this AI to work and have some really great results that may seem boring, but they are extremely successful for our company. 

Citizen science and personal involvement 

Gosia: Allison, I really loved your TED Talk about citizen data scientists. The last question I wanted to ask, and your final message to everyone listening, is how we can support the usage of science and artificial intelligence for the sake of the planet and society. How can we all contribute? 

Allison: So, yes, we can all be citizen scientists. I think the first thing that we can do is to choose our area of interest. For me, it turned out to be bees. I’ll tell you a little bit more about that in a second. But whether you’re interested in climate change, whether you’re interested in wildlife, whether you’re interested in oceans, there are so many projects that you can be involved in. 

So I would direct people to look at things like iNaturalist, Zooniverse, NASA. I’m actually doing an experiment with my bees. Believe it or not, I live in the path of totality for the 2024 eclipse, which is a very narrow band that only happens, if we’re lucky, once in a lifetime, that you actually live in the path of totality where we experience total darkness in the middle of the afternoon. 

So I will be collecting audio data of my beehives and submitting it to NASA so we can start to understand what happens with bees, what happens with other forms of wildlife in terms of what activity happens when it becomes dark for three to four minutes in the middle of the afternoon. 

So that’s something that I’m really, really excited to participate in, and I’ll be sharing what my findings are on my website in the spring. So, you know, I would just say, jump in, find something you’re interested in, and who knows where it will lead. We can all be advocates for change, and we can all be scientists. 

Gosia: Yes, exactly. So, as your father said, let’s swing at it, let’s be brave, and let’s try. Thank you, Allison, it was great hosting you today. 

Allison: Thank you for having me. 

Like what you hear?  

• Visit our AI at Scale website to discover how do we transform energy management and industrial automation with artificial intelligence technologies to create more sustainable solutions.  
• Read more about Allison’s 2024 Total Eclipse of the Sun Soundscapes Project. Listen to her TedxBuffalo in which she shares her story of becoming a Citizen Data Scientist. 
• Listen to the first episode with Philippe Rambach, Schneider Electric Chief AI Officer.

AI at Scale Schneider Electric podcast is live! 

The first Schneider Electric podcast dedicated only to artificial intelligence is officially live and available on all streaming platforms. The AI at Scale podcast invites AI practitioners and AI experts to share their experiences, insights, and AI success stories. Through casual conversations, the show provides answers to questions such as: How do I implement AI successfully and sustainably? How do I make a real impact with AI? The AI at Scale podcast features real AI solutions and innovations and offers a sneak peek into the future.