Intelligent Automation Radio is the #1 podcast for IT executives seeking insights on the impact and opportunities for innovation that automation is delivering to businesses around the world. Featuring thought leaders in AI, Machine Learning, Orchestration, Security Automation, and the Future of Work.

January 15, 2020    Episodes

Episode #57: Can The World’s Largest ITSM Vendor Innovate Fast Enough To Maintain Its Meteoric Growth?

In today’s episode of Ayehu’s podcast, we interview Dave Wright, Chief Innovation Officer at ServiceNow

Longtime Harvard professor Theodore Levitt once said “Creativity is thinking up new things. Innovation is doing new things”.  By that measure, ServiceNow must be among the most creative AND innovative organizations in the world. The disruptive product stream they’ve introduced to the ITSM market just in the last decade alone has propelled their growth into a $100 Billion software leviathan. They don’t appear to be slowing down either.  Accordingly, much of the IT world wants to know – can they maintain the same level of entrepreneurial creativity & innovation necessary to sustain that blistering pace? 

For insight, we speak with ServiceNow’s Chief Innovation Officer Dave Wright, the man in charge of nurturing his company’s innovative results & ensuring its market dominance.  Along the way, we learn about the three different vectors ServiceNow uses to measure the maturity & effectiveness of everything from digital transformation to hyper automation; some of the most innovative automation use cases ServiceNow witnessed due to the pandemic; and the one really important skill IT professionals must have in order for them & their organizations to succeed. 



Guy Nadivi: Welcome everyone! My name is Guy Nadivi, and I’m the host of Intelligent Automation Radio. Our guest on today’s episode is Dave Wright, Chief Innovation Officer for ServiceNow, the world’s largest IT service management software vendor.

ServiceNow, of course, has a long history of innovation which they’ve parlayed into a dominant leadership position in the IT operations market. More than 6,000 customers, including over 80% of the Fortune 500, use ServiceNow, which is branching out beyond their core focus on IT operations to target other areas of enterprise functionality with their Now platform. You can say this about their strategy – it’s visionary, it’s ambitious, and based on the results, it’s working. So we’ve invited Dave to come on the podcast and talk with us about how ServiceNow is going to leverage automation, AI, and digital transformation to continue conquering the platform as a service market.

Dave, welcome to Intelligent Automation Radio.

Dave Wright: Hey, Guy. Thanks a lot. What a great introduction, thank you very much.

Guy Nadivi: Dave, I’m sure much of our audience would love to hear what path you took that led you to become Chief Innovation Officer at the world’s biggest ITSM vendor.

Dave Wright: I get asked this quite a lot, and it’s a funny story. So it’s not a traditional path at all. I was born in Liverpool and educated in Liverpool. I left school at 17 and went straight into working. So I didn’t go down the college route and I ended up doing a few basic jobs. And then when I was 20 years old, I got the opportunity to kind of choose a career. So I ended up doing mainframe operations originally, and then became a mainframe programmer. And one of the products I was working with at the time was from a company called Campbell Software. And what happened is they came to me and said, would you like to work for us on the vendor side? And that was when I switched to the vendor area in a kind of pre-sales consultant role when I was in my very early 20s. Then I went through a number of different senior technical positions and ended up being at VMware. So I was at VMware for seven years looking after all their technical resources. So pre-sales, post-sales, technical account management, all that type of thing. And then just over nine years ago, actually it was nine years ago on Saturday, I was recruited into ServiceNow. And originally when I joined ServiceNow, I was based out of the UK and I was looking after the solution consulting team. So the team that work with the sales guys to actually do the technical part of the sale. And as I started to have more and more conversations with leadership, I ended up having more and more conversations with our CEO at the time, a guy called Frank Slootman, who you probably have heard of. Frank was pretty visionary in what he wanted to do from a product perspective. So as we had more and more conversations, one day, he said to me, you think about the strategy of the products in a different way to a lot of people. So what I’d like you to do, is I’d actually like you to be the Chief Strategy Officer of the company, which at the time was just a team of one. It was just me. And we were very focused. Then the strategy was all around well, what do we do from a product perspective? Where do we go next from a product perspective? And over time that evolved. So we got a new CEO when John Donahoe came in. Strategy for John was much more around the entire strategy of the company, the go to market, the segmentation. But what he said is, I still need that person who’s looking at technology or that person who understands the impact and potential of technology. So at that point, John made me the Chief Innovation Officer just over three and a half years ago. I’ve been Chief Innovation Officer ever since.

Guy Nadivi: Your CEO, Bill McDermott, recently stated that ServiceNow was, “The only born in the cloud software company to have reached a hundred billion dollar market cap without large scale M&A.” It’s well-known in Silicon Valley that the larger a software vendor gets, the more difficult it can be to innovate. As Chief Innovation Officer, how do you plan to keep the world’s largest ITSM company innovating at the same pace that’s led ServiceNow to its present level of success?

Dave Wright: So, first Guy, I mean, it’s not really that much of a problem, and you alluded to this at the start when you talked about the Now platform. The Now platform allows us to continually develop different solutions, but innovation itself, I suppose, is really about culture. So the way I think about it is no one person’s responsible for all that. And even though I’ve got the Chief Innovation Officer title, I’m not the sole source of ideas, and I shouldn’t be the sole source of ideas either. If it’s just you providing the ideas, you should probably be running your own company. And in reality, my job’s about hearing from customers who have deployed or explored a new technology and that are pushing the Now platform to its limits. So what I do is, it’s all about taking these customers, and being customer centric is one of the things that we’ve always had as a company, and we’ve always used that innovation based around what the customer wants. But it’s also about being aware of the changes in technology that are out there and thinking about different things that will affect you, and things that might affect you indirectly. The other thing that I think is interesting is, for us in ServiceNow, innovation is everywhere. So it’s not just the technology, it’s the techniques people use in sales, it’s marketing, it’s product. And we even structure part of the company so we have teams specifically set up that are focused on innovation to make sure we keep that drive going. And we’ve made sure that employees feel comfortable enough that they can fail. And they know that failure, it’s not just something that we tolerate, but, we’d encourage it. We like people to go out there and break glass. And as organizations grow, that becomes hard because they get more and more risk adverse. So one of the things we try and do to combat that is we try and set really high goals. So when we go out as a company and say, we want to be a $10 billion software company, everyone knows that that’s going to require a different way of thinking. So everyone constantly thinks about how you can do things differently.

Guy Nadivi: You’ve written about the world being in a kind of “COVID economy” where the work from home mandates are driving demand for digital workflows to fix problems remotely that can’t currently be attended to in person. That speaks to a need for greater enterprise resiliency. Dave, has resiliency now become more important than things like cost savings as a justification to invest more in automation?

Dave Wright: I think it depends on the business, to be honest, Guy. Some industries are going to want to take out costs, but what we wanted to do is try and understand a little bit more about what the impact of this was going to be on people. So we actually ended up doing a survey, we just called it “The Work Survey”, which looked at what the impact of COVID-19 was going to be on work. And when we got the results back, some things weren’t that surprising. So we had like, it was a … God, what was the percentage? It was something like 88% of organizations expected operational expenses to drop. So that’s no shock. Obviously, you’re not going to spend as much because we’re in a completely different environment, but some things were more interesting. So over half of the execs that we surveyed, they wanted to use those cost savings to actually drive digital transformation. So yeah, it’s not all about cost, it’s about a lot of other things. And you’re right, resiliency might be one of them. Because I think a lot of companies, they’ve kind of innovated rapidly during COVID, but some of the systems they’ve put in place are a bit rough and ready, they’ve kind of been deployed on the fly. So they are going to be at risk to the next major disruption. And again, one of the interesting things in that survey was most people thought that they wouldn’t be able to adapt within 30 days of another major disruption. And the reason for that, and this is one of the things that is going to start driving this whole economy, is because most businesses have a digital disadvantage. So again, in our survey … I’m really struggling now. I think that was around 90% of execs admitted that they still had offline workflows. So it could be anything. It could be document approvals, it could be security issue reporting, it could be tech support requests, so many different workflows that are still dependent on people following manual processes. And there’s so many of those that could be addressed and automated using digital workflows to actually start to make things a lot more efficient in this new economy.

Guy Nadivi: Now, speaking of various metrics, is there a particular metric you like above all others that best captures the effectiveness of automation to an enterprise?

Dave Wright: Yeah. So let’s expand it a little bit beyond just automation and talk about everything from digital transformation to hyper automation. This is an interesting challenge for everyone. So as the world changes, what are we going to do, how are we going to measure the effectiveness of it? And I always took great inspiration from one of my friends, Chris Bedi, who’s our CIO. So obviously in Chris’s role as CIO, he’s got to be able to prove he’s effective, he’s got to be able to prove that he is transforming. So what he did was he came up with a way to be able to map out where about he was from a maturity model. And it’s a really cool model, I’ll just walk you through what he did and then we can talk through some of the measurements that that created. What he did was, he said, okay, let’s look at three different vectors. Let’s look at velocity, intelligence, and experience. So they’re the things that we’re going to measure. And then within each of those vectors, you define four levels. So is it basic, is it productive, is it optimized, or is it transformed? So let’s take experience as one of those. Basic experience would be you’re receiving issues from phone calls. A productive experience would be that your portal-based, that people are now starting to do things online. If you got to the optimized level, then you’d be kind of a mobile first concept, you’d be using virtual agent technology. And if you got to the transform level, that’s where the platform would be proactively doing work for you based on your needs. Now, once he got that, he could map every process in every department and create a heat map for whereabouts they were in regards to how automated or transformed they were. And it led to a lot of interesting metrics that come out. So the big difference now is that you don’t measure what has happened, you started to measure what didn’t happen. So how many calls came in that were actually resolved at source via a chat bot or via a knowledge management system? Or how many events were predicted and then prevented? How many issues were actually fixed via orchestration technology or AI technology, as opposed to being fixed by a person? But I think the most interesting metric that comes out of all of this, and the best way to measure the effectiveness of automation at an enterprise level, is employee satisfaction. So let your employees do things that are meaningful, because if you can get an engaged employee, that’s incredibly valuable. So potentially, this carries benefits that go way beyond the immediate game that you get from automation, into actually the overall success and happiness of your company. But I would say, having worked with a lot of customers to talk about how they’re going to measure the effectiveness of this, if anyone’s listening to this and they’re going on this journey, the one thing I would tell everyone to do is make sure you start recording what it looks like before you do all this. Because like with any pain, when you suffer the pain, you feel it, but once the pain goes away, it’s hard to remember what that was like. So always make sure you have that before scenario recorded.

Guy Nadivi: Just like a weight loss program, you need a before and after picture.

Dave Wright: Absolutely.

Guy Nadivi: Dave, I’m sure in this year of the pandemic you’ve seen and heard about a lot of innovative automation projects. Are there any in particular that stood out to you which you can share with our audience?

Dave Wright: So some were use cases where things happened really rapidly. So it was interesting when we looked at the city of Los Angeles and they wanted to be able to track COVID tests for like, four million citizens. They came to us to say, well, could we build an app that allows us to manage and automate that process a bit? And they managed to build that in two days, which kind of blew me away from a development perspective. Then we had companies who were doing things in areas that I wouldn’t have really imagined. So the NBA came to us, and when they wanted to create the bubble or the campus to enable them to play the games, they needed a way to be able to get all of the players tested. And then they needed to be able to work with journalists, doctors, officials, for the games to be able to get the games ran. And what they did was they came to us and actually built workflows around all of that. So when the NBA launched, they were actually running all the logistic processes behind that via ServiceNow. But I think because COVID caused a lot of things where there was a sudden increase, it was areas where we were dealing with the knock on effects of COVID that really started to see the benefits of automation. So the state of Delaware’s Department of Labor, they had this avalanche, effectively, of unemployment claims coming in. So if you looked at their model, like I said before, always record the before model, before COVID hit, they were processing around 450 claims a week. And when COVID hit, in the first four weeks that went up to 64,000. So a massive increase, just a multitude of factors affecting that. But what they did was they deployed ServiceNow’s customer service management product. They deployed virtual agent technologies and they deployed knowledge management. And that meant that they could allow people to self-serve around a lot of common issues and actually give themselves a little bit of space to breathe. So they had an amazing result out of that. So they ended up seeing 475,000 virtual agent interactions, I think it was. And in that time period since COVID’s arrived, they managed to process 150,000 claims, which is something they just couldn’t have done without applying automation. And that’s one of the interesting things about COVID, it drove us into situations that we accelerated into way faster than we ever thought we would’ve.

Guy Nadivi: Now, for contrast, given the current state of the art, what do you think are some of the most unrealistic expectations currently plaguing the field of automation and AI?

Dave Wright: Yeah. Okay. I mean, obviously I hear these on a day-to-day basis and see people doing things that surprise me. The first unrealistic expectation people have is that when they invest in artificial intelligence or machine learning, there’s an expectation that the project will generate an immediate return on investments and it’s just going to be a silver bullet that solves all problems. That is not the reality because … It’s as interesting when people come on day one and say, we want to deploy AI on day one. Obviously, for artificial intelligence to work, it needs a corpus of data to be able to train the machine learning models. So until you’ve amassed enough data to do the training, you can’t actually deploy AI and get any effectiveness. So the first thing is understanding that there’s going to be a ramp up while you actually build the data levels to train the system. Or if you’ve already got the data in place, there’s still going to be a ramp up for you actually getting the models built, getting them rolled out, and then starting to get them used. The second unrealistic expectation is people kind of think AI is magic. So they think they can throw any data at it and it’s going to source out the good data from the bad data and build this brilliant mathematical model. But that’s not the way it works, we don’t have self-correcting data. So when you train a machine to be able to make decisions, the first thing that you need to do is be able to make sure you give it the most optimized data to be able to build those models. So make sure that you’ve cleansed data, that you’re giving it the right data that it needs in order for it to be able to build the models that are going to be most effective. The other two things, I suppose, that people talk about quite a lot is the concept of general AI. I think people are sometimes on the misconception that we’ve already got to general AI and we haven’t. By general AI I mean a machine that’s able to make decisions around things that are hasn’t necessarily been trained on just by being able to pull those assumptions. I think movies like the Terminator have got a lot to answer for when it comes to people’s perception of AI. But they’re the four main areas that I see when people come to me talking about what they expect from AI.

Guy Nadivi: Dave, with the growing strategic importance of automation to an enterprise’s competitiveness, is it time for automation functions to be unbundled from IT so that automation can become its own department reporting directly to the CEO via a Chief Automation Officer?

Dave Wright: Wow, that’s a tough one. I haven’t seen a Chief Automation Officer yet, but that doesn’t mean it wouldn’t arise. Whether it reports into the CIO, that’s another interesting debate as well. I think, I mean, things are changing. If I look at our company, back in May this year, we hired Vijay Narayanan, and Vijay came on as our first Chief AI Officer. So he was actually overseeing all the company’s artificial intelligence efforts. So if we’re already at the point where we’re seeing AI Officers, then I wouldn’t be surprised if we started to see Automation Officers in the future. And it would be pretty cool when you think about it, because I suppose there’s three things that they’d really be looking at. They’d be looking at well, what could be automated, what should be automated, and what should the approach to automation be? Because obviously, you’ve got everything from orchestration to integration, to robotic process automation, you could use virtual agents, AI. There’s so many different solutions out there that allow you to automate solutions, probably making the right decision is something that should be centralized. But even if they did report into the CEO, I think you’d need to have a lot of trust in what that person was doing. They’d have to be given authority to be able to go out there and be able to fix the problems, but they would have to be phenomenally well aligned to the CIO as well. And perhaps even the Chief Data Officer.

Guy Nadivi: With the growth in deployments of automation, especially this year, I think much of our audience will be curious to hear your answer to this question. Regardless of whether I’m a college graduate entering the IT job market or a seasoned IT professional looking to change specialties, what skills should I focus on acquiring to accelerate my career in the automation field?

Dave Wright: Well, I think if you already look at what’s happening now, the talent wars for roles in cybersecurity and data science are definitely going to heat up. We’re already seeing a shortage now in cybersecurity professionals, especially ones that have got automation expertise. And their role is becoming increasingly more important as organizations are starting to shift to a remote work model. So creating more opportunities for cyber threats is something that’s inherent once you start to move outside of the walls of a company. Also, now we’re starting to see a pairing of AI & machine learning with data science intelligence, to be able to provide more efficient solutions for the business processes. These roles are going to become more difficult to fill, I think, as companies move forward with their digital efforts. And I think that you start to see trends like AI expertise becoming more and more critical for IT automation professionals. So as advanced or intelligent automation, so automation that uses AI and ML capabilities, becomes ubiquitous, expertise in AI/ML is going to become kind of mission critical for that success. But I think when I describe roles like that, it seems like I’m going to be looking for a load of PhDs, that’s not necessarily the case. I think ignoring the soft skills side is a big mistake. So developing these soft skill sets, that’s what’s going to allow IT professionals to be set up for future success through their entire career. I think IT leaders today are expected to be much more than just technologists, they need to build relationships with other leaders. So whether that be the CIO, the CHRO, the CNO, and with customers as well, while also driving technology implementations right across the whole organization. So at the end of the day, as technology proliferates through the organization, a human-centered approach is pretty critical in being able to drive those results. But it’s hard to know exactly what the future holds. So maybe if there was one really important skill to take away, that skill would be to be adaptable.

Guy Nadivi: Interesting. Since we’re looking into the future, as a Chief Innovation Officer, I’m curious to hear what you think are going to be some of the biggest innovations we’ll see in the next one to three years, with respect to automation, AI, and other digitally transforming technologies?

Dave Wright: Well, it’s always a risk to put yourself down on digital media with predictions, but I’ll take a crack at it. I think the one thing that is going to happen immediately, is you’re going to start to see convergence. So all automation is going to become intelligence. Intelligent automation is going to expand what’s possible with automation technology. It will evolve process mining to include things like prescriptive recommendations, or it’s going to evolve to decision managements where we’ve got automated decision making systems. I think we’ll also see that integration of AI to business operations tools, where automation becomes a combination of low-code, no-code developments, process mining, artificial intelligence, and things like business process rules. I think the next thing we’ll see is artificial intelligence in automation for everyone. So low-code is going to make building apps and automation tools like building Excel models, while AI itself will be able to do the process mining and build the apps and workflows that start to improve that performance. The other thing I’ve started to see more and more recently, and I’ve just been doing research about it, is the concept of synthetic AI. So what’s happened at the moment is when people look for data to put in systems, a lot of that data contains information that people don’t necessarily want to share. So huge data sets are what obviously power deep learning and AI algorithms, but it can be pretty difficult for organizations to access all that data due to that PII information or concerns around that PII information. So I think the concept of synthetic data actually allows organizations of every size to be able to take a core amount of data, take the information out that’s sensitive, and then be able to build much bigger data sets to be able to get more accurate artificial intelligence algorithms from. And I think the other element that we haven’t seen yet is we haven’t really seen the application of artificial intelligence to collaboration tools. So current collaboration tools tend to just enable a conversation between people, but over time, I think we’ll start to see the inclusion of more AI functions within collaboration. So this whole concept will swap, where artificial intelligence is able to augment discussions. And I think that’ll be an interesting evolution as well.

Guy Nadivi: Dave, for the CIOs, CTOs, and other IT executives listening in, what is the one big must have piece of advice you’d like them to take away from our discussion with regards to implementing automation?

Dave Wright: Okay. So I think when the pandemic hit, it became apparent that automation was just a necessity, something that had to be done. Now it’s all about looking at how people work. So now you’ve got this distributed workforce. What are the repetitive tasks that are done again and again? And take the easy ones first and then move into a review cycle where you constantly go back and reevaluate, because if you can look at your top 10 repetitive issues and go through and you can automate half of them, that’s not where you’re done. I mean, you need to go back and go through that process cyclically and do it again and again. And you need to use tools like process mining or process optimization to be able to review things, because the one thing that people never focus on is looking at how to improve things that work. Now, I know there’s that classic saying, if it’s not broke, don’t fix it. But if you look at all the work that happens on a day-to-day basis, normally people will look at how long it takes to perform something and if it’s within acceptable time, then they never really bother investigating that. What we get now with artificial intelligence and process optimization is the capability to even look at the things are operating within the SLAs or OLAs of your company and see whether there are bottlenecks or whether things could be done better in that area as well. And I think that COVID-19, for me, has created the perfect environment for innovation. Practically overnight, the business world shifted to a near universal remote work scenario. And if you imagine how long that would have taken most companies to debate that, if they said, okay, we’re going to go to a work at home environment. A good company, might’ve done it in six months, maybe a year, but we ended up doing it in 72 hours, we just flipped that switch and away we went. And now we’ve started to unleash this new period of experimentation and innovation. That work study that I’d talked about at the start, I think it was 92% of execs in that said that they’ve now rethought how their company operates as an outcome from the whole pandemic. But the last thing I suppose, I’d leave people with is that automation’s going to advance, and that’s going to be caused by the application of new AI functions to traditional automation technologies. Think about the way chat bots talk to people. So when you have a conversation with a chat bot now, it’s getting information from you, you’re giving it information, but you could just as easily talk to chat bots on other systems. So once you’ve got integrations like that, you start to change perceptions about things like APIs, how you actually start to integrate systems together. So AI will be able to suggest automation targets and maybe even solutions to how you could automate. And for me, this is an amazing time in history. I think the next 10 years is where we’re going to see things happening that few people could even imagine now.

Guy Nadivi: It really is astounding how much this year has accelerated digital transformation. All right. Looks like that’s all the time we have for, on this episode of Intelligent Automation Radio. Dave, it’s always great hearing about automation directly from a senior executive at a market leader like ServiceNow. I know myself and much of our audience will be watching closely to see how you and the company will be continuing to accelerate digital transformation for organizations going forward, especially in light of everything that’s changed due to the worldwide pandemic. Thank you so much for coming on the podcast today.

Dave Wright: No, thanks for having me Guy, it was good fun.

Guy Nadivi: Dave Wright, Chief Innovation Officer for ServiceNow. Thank you for listening everyone. And remember, don’t hesitate, automate.



Dave Wright

Chief Innovation Officer at ServiceNow

Dave Wright is ServiceNow's Chief Innovation Officer and chief evangelist for connecting all aspects of digital transformation to the future of work. In this role, Dave is responsible for improving the employee experience as it pertains to workplace productivity. In his view, that depends on a great employee experience first, which in turn leads to more innovation, higher profitability and higher levels of customer satisfaction.  

Previously, Dave was the Chief Strategy Officer and Global Vice President of Solutions Consulting for ServiceNow. In this role, Dave was responsible for driving the company’s value and technical portfolio in order to promote technology excellence to customers and partners across the globe. Dave has almost 30 years of experience in the IT industry, specifically within Virtualization, Cloud Infrastructure, service management, performance management, data center automation and software development. 

Dave can be reached at: 

LinkedIn: https://www.linkedin.com/in/davewright2/ 

Twitter: https://twitter.com/TheWrightView 

Email: dave.wright@servicenow.com 

Quotes

“The Now platform allows us to continually develop different solutions, but innovation itself, I suppose, is really about culture. So the way I think about it is no one person's responsible for all that. And even though I've got the Chief Innovation Officer title, I'm not the sole source of ideas, and I shouldn't be the sole source of ideas either. If it's just you providing the ideas, you should probably be running your own company.”

“…we've made sure that employees feel comfortable enough that they can fail. And they know that failure, it's not just something that we tolerate, but, we'd encourage it. We like people to go out there and break glass.”

"…I think a lot of companies, they've kind of innovated rapidly during COVID, but some of the systems they've put in place are a bit rough and ready, they've kind of been deployed on the fly. So they are going to be at risk to the next major disruption." 

“I think movies like the Terminator have got a lot to answer for when it comes to people's perception of AI.” 

About Ayehu

Ayehu’s IT automation and orchestration platform powered by AI is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by hundreds of major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe.

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Links

Episode #1: Automation and the Future of Work
Episode #2: Applying Agility to an Entire Enterprise
Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work
Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations
Episode #5: Why your organization should aim to become a Digital Master (DTI) report
Episode #6: Insights from IBM: Digital Workforce and a Software-Based Labor Model
Episode #7: Developments Influencing the Automation Standards of the Future
Episode #8: A Critical Analysis of AI’s Future Potential & Current Breakthroughs
Episode #9: How Automation and AI are Disrupting Healthcare Information Technology
Episode #10: Key Findings From Researching the AI Market & How They Impact IT
Episode #11: Key Metrics that Justify Automation Projects & Win Budget Approvals
Episode #12: How Cognitive Digital Twins May Soon Impact Everything
Episode #13: The Gold Rush Being Created By Conversational AI
Episode #14: How Automation Can Reduce the Risks of Cyber Security Threats
Episode #15: Leveraging Predictive Analytics to Transform IT from Reactive to Proactive
Episode #16: How the Coming Tsunami of AI & Automation Will Impact Every Aspect of Enterprise Operations
Episode #17: Back to the Future of AI & Machine Learning
Episode #18: Implementing Automation From A Small Company Perspective
Episode #19: Why Embracing Consumerization is Key To Delivering Enterprise-Scale Automation
Episode #20: Applying Ancient Greek Wisdom to 21st Century Emerging Technologies
Episode #21: Powering Up Energy & Utilities Providers’ Digital Transformation with Intelligent Automation & Ai
Episode #22: A Prominent VC’s Advice for AI & Automation Entrepreneurs
Episode #23: How Automation Digitally Transformed British Law Enforcement
Episode #24: Should Enterprises Use AI & Machine Learning Just Because They Can?
Episode #25: Why Being A Better Human Is The Best Skill to Have in the Age of AI & Automation
Episode #26: How To Run A Successful Digital Transformation
Episode #27: Why Enterprises Should Have A Chief Automation Officer
Episode #28: How AIOps Tames Systems Complexity & Overcomes Talent Shortages
Episode #29: How Applying Darwin’s Theories To Ai Could Give Enterprises The Ultimate Competitive Advantage
Episode #30: How AIOps Will Hasten The Digital Transformation Of Data Centers
Episode #31: Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation?
Episode #32: How To Upscale Automation, And Leave Your Competition Behind
Episode #33: How To Upscale Automation, And Leave Your Competition Behind
Episode #34: What Large Enterprises Can Learn From Automation In SMB’s
Episode #35: The Critical Steps You Must Take To Avoid The High Failure Rates Endemic To Digital Transformation
Episode #36: Why Baking Ethics Into An AI Project Isn't Just Good Practice, It's Good Business
Episode #37: From Witnessing Poland’s Transformation After Communism’s Collapse To Leading Digital Transformation For Global Enterprises
Episode #38: Why Mastering Automation Will Determine Which MSPs Succeed Or Disappear
Episode #39: Accelerating Enterprise Digital Transformation Could Be IT’s Best Response To The Coronavirus Pandemic
Episode #40: Key Insights Gained From Overseeing 1,200 Automation Projects That Saved Over $250 Million
Episode #41: How A Healthcare Organization Confronted COVID-19 With Automation & AI
Episode #42: Why Chatbot Conversation Architects Might Be The Unheralded Heroes Of Digital Transformation
Episode #43: How Automation, AI, & Other Technologies Are Advancing Post-Modern Enterprises In The Lands Of The Midnight Sun
Episode #44: Sifting Facts From Hype About Actual AIOps Capabilities Today & Future Potential Tomorrow
Episode #45: Why Focusing On Trust Is Key To Delivering Successful AI
Episode #46: Why Chatbots Are Critical For Tapping Into The Most Lucrative Demographics
Episode #47: Telling It Like It Is: A 7-Time Silicon Valley CIO Explains How IT’s Role Will Radically Change Over The Next Decade
Episode #48: How Microsoft Will Change The World (Again) Via Automation
Episode #49: How One Man’s Automation Journey Took Him From Accidental CIO To Unconventional VC
Episode #50: How Automation Helped LPL Financial Grow Into The Largest Independent Broker Dealer In The US
Episode #51: Why Cognitive Architecture Might Be An Early Glimpse Of A Future With Artificial General Intelligence
Episode #52: Chatbots Aren’t Human, So Don’t Expect People To Pretend They Are
Episode #53: Why End User Experience May Be A Better Measure Of Automation Success Than ROI
Episode #54: How Digital Dexterity Will Generate Competitive Advantage For Agile Enterprises
Episode #55: Is It Time To Start Hiring Digital Coworkers So Human Staff Can Spend More Time With Customers?
Episode #56: How Intelligent Automation Will Empower People, Transform Organizations, & Improve Our World

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Disclaimer Note

Neither the Intelligent Automation Radio Podcast, Ayehu, nor the guest interviewed on the podcast are making any recommendations as to investing in this or any other automation technology. The information in this podcast is for informational and entertainment purposes only. Please do you own due diligence and consult with a professional adviser before making any investment