Interview with Megan Beck
Co-Founder & President @ AIMatters

Megan works at the intersection of business and technology. She investigates how technology is changing our lives and particularly the way we work and businesses operation. She tries to quantify how things are changing and works with organizations who don't want to be dinosaurs waiting for a digital meteorite. She also does research and shares what she finds out. She's the Chief Insights Officer at OpenMatters, a digital/machine learning/advisory startup. Learn more about AIMatters here.
Hello Megan! Could you please introduce your work with AIMatters and tell us a bit more about what led to your founding the company?
Hi I'm Megan Beck, I'm a co-founder at AIMatters. We're a machine learning startup that helps leaders make better strategy decisions. I've been with the firm for more than five years and when we started, we were still headed on this path - although I don't think we knew exactly where the technology and where our customers would take us - but we've always worked from this simple hypothesis: that some companies are better than others. And what makes those companies better today is the technology, the assets and the business models that they use. Over 30 years there's been an enormous shift in what companies are gathering investor dollars, customer attention, the most talented employees. And it's been a shift from legacy business models, creating physical assets and offering services, to modern day business models which leverage highly scalable networks and technology platforms. And the difference between these two types of business approaches is amazing: it creates enormous economic value for those who are able to make the transition to networks and platforms, and it's affecting all industries. So we've seen transportation shift from Ford to Uber, and we've seen accommodations shift from Marriott to Airbnb. And no matter what your industry is, the the effective technology and networks is really changing where money is made. And so AIMatters uses data from traditional and alternative sources, in order to understand how well-adapted companies are to this age of technology and networks. Are their products leadership capabilities, customer relationships, employees and operations all tuned for the digital age? So our platform gives a score on how well companies are doing on those aspects, and then creates recommendations on how they need to evolve in order to best capture value.
What are some of the most surprising and innovative ways AI can affect business practices and executive team decision making processes?
One of the things that I have found most surprising working in AI and machine learning is that the algorithms are actually pretty capable of making some high-level and important decisions. So many of us, I believe, are used to the fact that artificial intelligence might affect the way we drive our cars, or the way items are picked in warehouses, and we tend to think of artificial intelligence as affecting some fairly low-level type jobs. But where has the A.I. revolution really transformed an industry? Well, just look at financial services. Financial advisors are quickly being supplemented, if not occasionally replaced, by robo-advisors that make recommendations on how you should invest your money, based on your age and risk profile. So, we have seen the similar thing happening when it comes to strategy: leaders and boards make really important decisions about how to invest their capital, in order to direct the trajectory of their organizations. And what's great about business is that there's a really formal way that that data is maintained and captured, so we have the data we need to look at: how are these capital allocation decisions affecting business outcomes? And so although AI will likely affect low-level jobs, too, it's quickly entering senior level decision making, the boardroom, and that's what's been surprising to me.
What was the process for developing the AIMatters platform? How long did this process take?
When we first started working on these business model and business strategy questions five years ago, we definitely did it the old fashioned way - with Excel spreadsheets and and analysis. And that really worked for providing some early proof points for our customers, both, but also for our articles and publications, like our book The Network Imperative. But we did quickly see we were going to need something more scalable, particularly to address the customer needs of expanding to new geographies, and new functions and new data sets. So about three years ago, we pivoted and started working on our platform. Over that time it has gone through many iterations, as we've gone deeper into the data and become more efficient with our machine learning processes. One thing we've certainly incorporated into the platform is that machine learning algorithm aspect, in order to shorten our development time. So three years now into the process, we definitely have a great platform that we're happy to share with customers, but development continues as we still are trying to meet new and ongoing needs.
What's next for your work with AIMatters and your consulting career? What are some of the innovations in the field that you're the most looking forward to?
This article, 'How Artificial Intelligence makes Emotional Intelligence more important for humans', was one of the pieces we wrote that got the most interest over the past couple of years, and I think it's because all of us know that artificial intelligence is going to change the way we work and the way jobs are done, and we each want to know, "How should I be adapting my own skill set in order to prepare for the shifts that may come to my role?" So, within almost all the work that human beings do there's a common process of gathering data, analyzing and synthesizing the data, connecting it to potential future outcomes, and then from the expected outcome, creating a path forward, right? That's what we do, whether we're working in strategy consulting, or in medicine, or in finance. So, in all of those paths what artificial intelligence is really good at is the first part: collecting and analyzing the data, and connecting it to potential results. But that still leaves a lot of space for human work, and what humans are better at than machines are things like: creativity, problem solving, and persuasion and motivation. So when it comes to, for example, the consulting path: the machine might do a lot of the analysis, but the consultant can really differentiate in his or her ability to persuade the client to take action. In the case of medicine: an artificial intelligence might be really good at diagnosing a disease, but the doctor might actually have to pull on his or her bedside manner in order to persuade the patient to take a certain course of action, or to collaborate with the patient on what that course of action should be. So I think all of us need to be focusing on these human aspects - creativity, motivation persuasion, and changed management - and those are the pieces of our roles that are going to really differentiate us over the next decade.