September 16, 2020 Episodes
Episode #48: How Microsoft Will Change The World (Again) Via Automation
In today’s episode of Ayehu’s podcast, we interview Charles Lamanna – Corporate Vice President, Low Code Application Platform at Microsoft
“To me, Microsoft is about empowerment… we are the original democratizing force, putting a PC in every home and every desk.” That quote by CEO Satya Nadella, of course, reflects the ubiquity achieved by the Windows operating system. His company’s feat of democratization however, is just prologue to the coming revolution Microsoft foresees in automation. An upheaval expected to be so disruptive to the status quo, it will empower the information worker masses to finally overthrow the oppressive yoke of robotic tasks smothering their productivity. With newfound freedom to unleash their ingenuity, they’ll not only enrich their own lives, but add greater value to the organizations employing them.
The Microsoft executive charged with redressing the imbalance between toil & talent plaguing white collar wage earners is Charles Lamanna. As Corporate Vice President, Low Code Application Platform, his portfolio of responsibility encompasses all the critical assets needed to bring Microsoft’s lofty vision to life. In this wide-ranging discussion, we get first-hand insight from a senior executive on the vital role automation plays in the software giant’s Cloud-First, Mobile-First strategy. Along the way we’ll also learn why the shifting ratio of repetition to creativity within a given task will determine which automation type it’s best suited for; the automation skills one should master to position themselves for success in the future; and what the single biggest disruptor for automation will be over the next few years.
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 Charles Lamanna, Corporate Vice President, Low Code Application Platform at Microsoft. Now, there are many products at Microsoft that Charles is responsible for which I’m sure our audience members are very familiar with, including the Dynamics 365 platform, Power Apps, Power Automate, Power Virtual Agent, AI Builder, and the Common Data Service products. And as everybody in IT knows, Microsoft almost always becomes a major player in any market they enter. The automation and AI markets which we focus on, are unlikely to be exceptions to that. So given the strategic automation and AI assets Microsoft has entrusted Charles with overseeing, he’s someone we absolutely had to have on this podcast. And we’re thrilled, he’s taken time out of his very busy schedule to join us today. Charles, welcome to Intelligent Automation Radio.
Charles Lamanna: Thank you for having me on the show today, Guy. I’m super excited to get into the thick of automation with you. I know I’ve been a listener recently, so really excited to get into the dialogue.
Guy Nadivi: So let’s start with that, Charles, please tell us a bit about your role at Microsoft and the types of automation you’re focused on.
Charles Lamanna: Sure thing. So as you mentioned, I’m the Corporate Vice President of Low Code Platforms at Microsoft. So I’m on the R&D side, engineering and product management, lead those teams related to the Power Platform and Dynamics 365. The most relevant products that I oversee when it comes to automation and AI is Power Automate, which is our robotic process automation offering at Microsoft. Power Virtual Agent, which is our low code chatbot experience, and AI Builder, which is our low code AI and machine learning tool for business users and business developers. And those three things really together combine to create what we call our automation platform.
Guy Nadivi: So earlier this year, Microsoft made a big splash in the automation market by acquiring Softomotive, an automation vendor with 9,000 global customers. And that capped off a sequence of high-profile transactions in the automation space, which made it clear this is going to be a market of intense focus for some very significant players. Charles, how does Microsoft’s automation fit into its Cloud-First, Mobile-First strategy?
Charles Lamanna: That’s a great question. The first thing I’d say is that we’re super and incredibly excited about the Softomotive acquisition within Microsoft. We think it really is a great compliment to Power Automate, Power Virtual Agent, AI Builder. To really kind of map back what we were thinking around Softomotive in our general automation strategy, I do want to spend a second just talking about the overall automation vision at Microsoft, because that I think helps paint a really good picture for it. When we talk about that vision, there’s really four main pillars to it. The first one is that automation is more than just UI Automation. One of the big trends recently in automation technology has been robotic process automation or RPA. But RPA historically is incredibly centered and focused on UI Automation and more specifically Windows-based automation. And it’s our view that that UI Automation is necessary, but insufficient to really enable interesting automation scenarios and really transform every aspect of every company in every country around the world. So things like API connectivity or API-based automation or AI capabilities like natural language understanding or NLU or a whole bunch of other exciting AI technologies, those are also key ingredients. So just being more than UI Automation is really important. The second is being cloud first. We think there’s I’d say a legacy of automation being very PC-centric, very on-premise centric, and there’s some real potential to reimagine what automation looks like in a cloud native, cloud first way. So that’s really important to our vision. Number three is that automation has to be generated and supported by AI. Has to be enabled by AI capabilities in terms of identifying what can be automated and the best way to automate it. As well as when those bots run, use AI to go make them better over time. And last but not least, by far my favorite aspect of our vision is low code. And this permeates really a lot of work we’re doing at Microsoft these days. But low code is a whole idea that you want to make it so anybody and everybody can be a developer, can build bots, can contribute to the automation revolution. That’s not just constrained to a small group of experts or developers. So those are the four aspects more than UI Automation, cloud first, generated & supported by AI, and low code. But getting back to the Softomotive acquisition, the WinAutomation desktop app was really in our view the leading low code RPA tool out there, has a huge fan base, very frequently adopted virally and by business users. So people just going to a .com, downloading it, and starting to automate. Additionally, WinAutomation was built in such a way as well as with the new open source Robin programming language for easy accessibility into the cloud. So it can very easily integrate with a cloud provider. So that combination of that low code desktop application, as well as the cloud integration and cloud readiness made Softomotive a great fit for the Power Automate vision and the Power Automate offering, and therefore a really great fit for the broader and mobile centric cloud first approach that Microsoft is taking these days.
Guy Nadivi: Interesting strategy. So there are many professionals today Charles, that can be categorized as information workers and maybe eventually some of them will also become app developers in the sense that you were talking about. How do you envision automation changing the jobs of information workers, and which roles or positions do you think will be the most difficult to automate?
Charles Lamanna: Yeah, I would say, we think that automation will be an important part of really any modern information worker job in the future. But the importance and the criticality will be a spectrum from say, somewhat impactful to very impactful, but really all information workers will feel that impact, will feel the responsibilities change and evolve over the next five years or so. And a major reason for that is the advancements in artificial intelligence to understand unstructured content like voice, video, text, as well as the fact that basically all the information worker’s job is captured digitally, is running on a PC or on a mobile device or mirrored in the cloud. So you can really start to enhance and automate almost any profession. However, I’d say that this transformation isn’t, I’d say all or nothing. There’s actually two really different ways that we look at what automation will do. The first is what I would call human assisted automation. And the second is autonomous automation. When we talk about human assisted automation, the idea is it’s all about helping a human do their job better, be faster, reclaim time, spend more energy on creativity and high value, high cognitive tasks. Less on doing data movement or simple rote activities. And autonomous automation is automation happens in the background. Does things without interacting with the human, pulling work off a queue or responding to events. And there are two fairly different approaches in terms of how automation can impact an information worker. And we think that some jobs will be heavily impacted by autonomous automation while others will be impacted primarily by the human assisted automation. And the difference between the two is really going to depend on how much repetition and how much creativity happens as part of the job. There’s more repetition and less creativity, there’s going to be more autonomous automation. If there’s less repetition and more creation, there’s going to be more human assisted automation. And that human assistant automation can sometimes be really subtle. If you imagine, in Outlook these days there’s suggested responses to emails, right? That’s automation. That helps me respond to emails more quickly, things like that. So we’re really going to see this permeation of applications, whether they’re integrated with the standard SaaS apps, standard OS’s or custom bespoke automation built for a company, we’re really going to see an emergence across both those front, the human assisted and autonomous-based automation.
Guy Nadivi: Okay. Let’s expand a bit on what you said and assume that automation will be part of the role for all or most information workers in the future. If I’m a college graduate entering the IT job market, or a seasoned IT professional looking to change specialties and interested in automation either way, what skills should I focus on acquiring to accelerate my career?
Charles Lamanna: Yeah, the first thing I’d say is automation is a fairly broad ecosystem. So if you want to be part of the automation revolution in terms of contribute to building out these different automations within the enterprise, you have to I think go to a few different places. The first one I would say is UI Automation, RPA is a really key aspect of it. And that’s because there’s a whole lot of systems which can only be reached via UI Automation. Like I said earlier, it’s necessary but insufficient, but you definitely want to go out and get familiar with RPA tools and UI-based automation. The second thing is get a good view of APIs, and what enterprise application integration looks like, whether that’s APIs or event-driven architecture, because that’s the more future-looking way that automation will be built and created in the enterprise. And having a good view of service-oriented architecture, microservice, API catalog, event catalog, things like that will be very useful. The third is interesting because I’d say it’s not really related to technology at all. And that’s understanding business processes and designing business processes. Because automation is all about improving a business process. So knowing the language, the terminology, and the aspects you want to optimize when it comes to business process engineering is a really great tool. The fourth thing would be just a standard software development life cycle. If we go look at what it looks like to build out these automations, there is a design phase, there’s a planning phase, there’s development, there’s deployment. And the automation tools out there are compressing these cycles to be just hours or days long as opposed to weeks or months. But you still should know that cycle because that’s important to be successful in the enterprise. And the fifth, which I would say is the extra credit, but it’s going to really separate the good from great is going to be AI and ML understanding. And you don’t have to be a deep learning expert, doing super 40 megawatt AI model training like GPT-3 or something. We should feel comfortable around the … At least the high level concepts of machine learning. So things like reinforcement learning or transfer learning, which are going to be really important in the future when it comes to building durable, reusable, high value automation, at least from Microsoft’s perspective. So those are kind of the five things. Four, I’d say standard, and one, a little bit extra credit that would be important to really be successful in the IT space when it comes to building automation and the enterprise.
Guy Nadivi: Let’s talk about one form of durable automation that you’re referencing. In the form of AI-driven assistance or bots, which are growing in prevalence for a lot of customer-facing applications. Gartner believes there are as many as 1,500 chatbot vendors worldwide. And I quote, “The majority of these conversational platform vendors offer very simple platforms using modified open source components to deliver simple question and answer chatbots.” Now I think it’s safe to assume the market doesn’t need 1,500 vendors in this space and an inevitable shakeout is coming. Charles, what kinds of things do you think will differentiate the survivors in this market space from the vendors who will fall by the wayside?
Charles Lamanna: Yeah, I think like any kind of technology market, as it becomes more mainstream, you start to see more consolidation and all-in-one offerings start to emerge as opposed to lots of little point solutions. And folks that know me well, I love my numbered lists. So I’d say there’s probably four different aspects that will really define what chatbots in the future will look like, that at least map into our strategy at Microsoft. The first is omni-channel, and what we mean by that is a chatbot that only works in a web-based chat experience is going to be insufficient in the future. You’re going to need to support I’d say WhatsApp, SMS, Facebook, voice, things like Alexa. There’s really going to be a need to support all kinds of different form factors to be successful. And you need to abstract away those channels from the bot authors and bot developers. So the ability to go reach into tons of different channels will be absolutely essential. The second is really being deeply, deeply AI-enabled. Chatbots are probably one of the best places where we see amazing return on advanced AI right now. Things like reinforcement learning, where you actually improve the control flow in your chatbots based on experiments and the results, and improve your models basically for matching entities are intense. For the bots that have used that for our technology at Microsoft, that significantly improves the success rate of sessions. And that’s pretty sophisticated AI capabilities. The third is really integrating with broader business processes, because what we see is no bot is an island, right? No man is an island, no bot’s an Island. No bot just exists on its own. It has to integrate with other systems in the enterprise to take actions, to fulfill returns, to help a customer purchase something. That requires integrating with other workflow systems, other databases, and really kind of running the end to end workflow. So really that integration to a broader ecosystem is going to be key. And the fourth one, the last one I think is not always super obvious, but it’s the ability that go hand off to a human, to work with a human, to have a chatbot and humans work side by side. And this, the reality is that there is no general artificial intelligence. There is no chatbot that you can run that can answer any question of a customer with anything. So any chatbot will always run against its limit – the limit of its abilities. And in those cases, you can’t churn the customer out or push them to a dead end, or say “We’ll call you back.” Instead, you need a seamless amnesia-free handoff to a human agent that can continue the conversation and grind it out. And what we’re finding is that this is what allows the usage of chatbots as a main line dependency in mission critical enterprise defining business processes, because you can cover the 75% with the chatbot and then you can cover the 25% with the human. And this is a great example of that human assisted bot versus human assisted automation I was talking about earlier. And one of the great examples of this at Microsoft internally, we have a chatbot which we use for our support experiences at support.microsoft.com. There’s over a million support cases that run through it every month. And the chatbots and human agents work hand in hand to address the needs of our customers. This produced, when we rolled it out, demonstrably, better customer satisfaction. We improve the customer experience and at a much lower cost. So that last one we think is going to be key. And if you do just a chatbot and don’t have a story for human agents behind the scenes, you’re really going to be leaving a bunch of use cases on the table. Because when a customer runs up against those dead ends, they’re going to go bail on the chatbot entirely. So I think those are the four main things that we really think are going to be defining for the space over the next few years and therefore be defining for the vendors in the space over the next few years.
Guy Nadivi: Speaking of humans, when you talk with your customers, what are they telling you are some of the biggest challenges they’re experiencing in deploying automation within their organization?
Charles Lamanna: Yeah, I’d say the biggest thing we hear really with everybody is finding the right skills, finding employees and experts with the right skills. And when I talk about skills, it’s not just related to the technology. It’s also about how do you understand the problem, how do you understand business process engineering. How do you understand the business needs, where automation will provide value. And that combination of being able to understand the business process, understand the business needs, in addition to understanding the automation technology, whether it’s RPA, AI, or DPA – that combination is really what we see a lot of organizations struggle with, and things like creating automation centers of excellence or doing internal skilling and training programs. The combination of those things is really what customers are trying to do today to go respond to this challenge. I mean, there’s probably a tale that’s been around for quite some time for disruptive or interesting technologies, which is just that change management skilling and mapping into the business need is what’s really slowing down adoption in most cases. So I’d say having a good strategy for skilling and training is a really important aspect for a lot of the customers that we work with to go make them be successful with the technology that they have.
Guy Nadivi: We’re hearing more and more about process mining and other AI-based discovery platforms being deployed as part of digital transformations. Charles, how do you think these tools are impacting adoption rates for automation?
Charles Lamanna: They’re accelerating them. Massively accelerating them. And I think process mining and the AI discovery capabilities is probably the most interesting thing that we’re watching at Microsoft when it comes to automation over the next couple of years. And the reason is because it’s still early days today, of course, but these tools help you very quickly identify processes that are ripe for automation. And even more interestingly is they actually help with the calculation of the ROI for an automation project. And this really is the dream of most IT transformation projects. Before you invest in building out the bots, before you invest in building out the AI, you can quantitatively analyze your workforce, understand where there’s inefficiencies, and then project the actual efficiency gains and customer experience gains once you roll out automation. And once you have this kind of closed loop of mine the processes that are happening, identify the upside, address the automation need, then confirm that you saw the results you expected. This is going to create a very virtuous cycle of building bot after bot, after bot, after bot, that will really start to change the landscape in IT and for information workers. So we think this is really going to help just accelerate it, but it all goes back to just helping understand the economics, understanding the ROI, and understanding whether or not you were successful with a IT or automation project. It all goes back to those basic principles which every IT manager is always worried about. It makes that be much less of a guessing game. And if I were to make a comparison, it reminds me of the shift in marketing, from broadcast marketing, where it’s very hard to understand the impact of a marketing campaign, because you didn’t know how many people actually went to go purchase something as a result of a commercial or something in a newspaper. When you went to digital marketing, for the first time you could know for every ad, how many people actually purchased the good that you were advertising, because you have tracking and things like that. That is – and that actually drove a ton more adoption, a ton more digitalization of advertising. We think a similar phenomenon is going to occur because you are going to be able to go track from ideation of an automation project, to the ROI of the automation project end to end. So that is what I would say is the acceleration we’re seeing and the why, and how we really imagine it shifting over the next couple of years, going forward.
Guy Nadivi: Some organizations have really embraced automation, at least partially because they understand the ROI potential you just spoke about, and they’ve made it a core part of their IT operations. Other organizations have more of a wait and see attitude. Regardless of where an enterprise falls on the automation maturity spectrum, what do you think are the key factors they should consider when formulating their automation strategy?
Charles Lamanna: I’d say the most important thing to consider is that any automation project or automation transformation, is recognizing that it’s going to help your business processes go faster and be more efficient where it doesn’t inherently reimagine or transform your business process. And the reality is that automation is just like any other tool in the tool chain in IT. Whether it’s like cloud or mobile machine learning, event driven architecture, things like that. It’s going to help accelerate and reimagine your business process, but it’s not something you can really adopt in a vacuum and it’s not going to solve all of your problems. You frequently need to go look at the business process that you actually want to automate to make sure that you’re reimagining it, updating it, making it more modern in the process, because if all you do is automate every process exactly as it is, you may get some gains, but you’re really not going to be transformational. And that’s kind of a … Just one of the most important things that we really work through in terms of being successful with your automation strategy. And whenever I talk about this with customers, it always reminds me of a great quote from a football coach, Lou Holtz. He had a quote which was something like, “You’d rather have a slow guy moving in the right direction than a fast guy moving in the wrong direction.” Automation is kind of like that in that if you roll out automation for the wrong project, you’re just going to have the wrong business process go a heck of a lot faster in the wrong direction. So you really want to make sure you’re building your automation, you’re reimagining the business processes along the overall strategy and direction of the company, which maximizes for your business, as opposed to just taking what’s already there and making it go faster.
Guy Nadivi: There’s a variation on that Lou Holtz quote that I personally love, which is, “To err is human, but to truly screw up requires a computer.”
Charles Lamanna: Yes, too true.
Guy Nadivi: Charles, you’re certainly in a position to know. So I’d love to hear what you think are going to be some of the biggest disruptions we’ll see in the next one to three years, with respect to automation, AI, and other digitally transforming technologies.
Charles Lamanna: So I can only answer this in one way and with one thing. I’m a little bit biased about what I work on, but I have to say the single biggest disruptor for automation is going to be the low code development of automation. And the main reason we see this being the case is because of, I’d say four big shifts, four big changes that are happening in IT development today. The first is a workforce shift. 35% of the workforce today are millennials or 75% of the workforce will be millennials by 2025. This audience has incredibly high expectations for modern digital experiences at work. And they aren’t the folks that like to copy-paste data between 17 different systems or in green screen terminal applications and things like that. They really want modern, not rote, creative and innovative experiences at work. So the workforce is shifting. The second thing is because of the shift in workforce and because of these expectations and in general push. And that every company everywhere is that there’s a huge surge in demand and the need to digitally support and enable your employees. We can see this in really unprecedented demand in terms of the acceleration of digital projects. We project over the next five years, there’ll be as many digital solutions built in the enterprise as were built over the last 40 years. Just huge, huge demand. So a new workforce with high expectations and huge demand. But there’s a third problem, which is an incredible, a staggering shortage of professional developers and coders. In the United States alone, we’re going to be short a million developers over the next decade. There just aren’t enough developers out there to go solve and address this growing demand. And then to kind of top it all off is a fourth thing, with COVID-19 the associated recession, which we’re calling the great lockdown, we’re going to be in a period of time where IT is going to need to do more with less, or do more with your existing resources and your existing technology. So all of these things are kind of mixing together right now. These four things. And what we’re seeing is that low code is really going to be, I think, emergent as a result of these changes. Because low code automation technology, which make it possible for everyone to be an automation specialist, a business user, an IT professional, or a coder can all start to automate tasks is what low code is all about. This completely changes the calculus of automation projects, completely solves the problem that I’ve talked about throughout the discussion of, do you understand the business need as well as the automation need? It actually makes, so the people who understand the business need in the business can solve the automation problems with these low code automation tools. And this starts to change just what the IT landscape looks like, drives more collaboration between business users and IT, and the end result is a heck of a lot more automation being built in a fairly short period of time. So really over the next one to three years, we see that low code is going to be one of the most disruptive forces and in particular, low code automation tools, which have visual authoring environments, visual debugging environments, as well as easy to understand concepts and management configuration is going to be one of the most disruptive aspects. And that really is the heart of our thesis at Microsoft of where automation is heading over the next three years.
Guy Nadivi: I think you’re absolutely right about low code because the history of technology is that it gets easier to use over time, which democratizes its abilities for the masses. So history would seem to agree with you. Charles, 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 moving forward with automation.
Charles Lamanna: This may be obvious to some of your listeners, but I’ll repeat it because it bears repeating. Which would be the best time to start building out your automation strategy and getting serious about automation for all functions of your company was probably three years ago. The second best time is now as the saying goes. And just the reason is that the return on the ROI on projects in the automation space really is phenomenal. There’s a huge amount of digital processes that have been accumulated over the last two decades that are just waiting to be enhanced and improved through automation. You can improve the employee experience, make your employees happier, keep them working at high cognitive high value tasks. You can improve customer experience, solve the customer’s problems faster and more efficiently than ever before. And you can do all of this with relatively minimal budget, but large outsize return. These things all just make it easy and straightforward to go build the case, to go build … To create an automation strategy, and to go chart what automation is going to need over the next few years. So if anything, I would just say now is the time to really make sure that you’re getting serious, that you’re looking at how automation can reach all parts of your company. And I think just speed and moving quickly is going to be key because as we go look out over the next couple of years, which are going to be a little bit challenging, macro economically speaking, automation is going to be key to being efficient, being lean, and building a great customer experience during those times. So I will say, move, move fast, move now, if you haven’t already, when it comes to automation, that would be the biggest takeaway.
Guy Nadivi: I think that’s very prudent advice because if you don’t, your competitors certainly will.
Charles Lamanna: Absolutely.
Guy Nadivi: All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Charles, it’s been fantastic having you here today and learning about your perspective on the automation and AI space. I think everyone is going to keep a keen eye on what you and your team at Microsoft will be doing to shape the future of this market and continue moving it forward. Thank you very much for joining us.
Charles Lamanna: And thank you for having me, Guy.
Guy Nadivi: Charles Lamanna, Corporate Vice President, Low Code Application Platform at Microsoft. Thank you for listening everyone. And remember don’t hesitate, automate.
Corporate Vice President, Low Code Application Platform at Microsoft.
Charles leads the Engineering teams for the Low Code Application Platform (LCAP) in the Business Applications Group at Microsoft. The LCAP team includes the Dynamics 365 platform, Power Apps, Power Automate, Power Virtual Agent, AI Builder and the Common Data Service products.
Under his leadership, the Dynamics 365 service moved to Azure and evolved into a fully managed SaaS–on a single version, with regular updates. The Dynamics 365 platform is now one of the largest fully Azure hosted SaaS products in the world, deployed to over 30 datacenters and supporting the entire Dynamics 365 business.
Before that, Charles worked in Azure for 4 years, leading the engineering teams that created Azure Resource Manager, Azure Autoscale, Azure Logic Apps, Azure Activity Logs and several other management related capabilities. Before Azure, Charles founded MetricsHub, one of the first offerings for public cloud cost management and service health monitoring. MetricsHub was acquired by Microsoft in 2013.
Charles can be reached at:
Try it out: Power Automate
“…RPA historically is incredibly centered and focused on UI Automation and more specifically Windows-based automation. And it's our view that that UI Automation is necessary, but insufficient to really enable interesting automation scenarios and really transform every aspect of every company in every country around the world.”
“We think there's I'd say a legacy of automation being very PC-centric, very on-premise centric, and there's some real potential to reimagine what automation looks like in a cloud native, cloud first way. So that's really important to our vision.”
"…low code is a whole idea that you want to make it so anybody and everybody can be a developer, can build bots, can contribute to the automation revolution."
“…we think that automation will be an important part of really any modern information worker job in the future. But the importance and the criticality will be a spectrum from say, somewhat impactful to very impactful, but really all information workers will feel that impact, will feel the responsibilities change and evolve over the next five years or so.”
“I think process mining and the AI discovery capabilities is probably the most interesting thing that we're watching at Microsoft when it comes to automation over the next couple of years. And the reason is because it's still early days today, of course, but these tools help you very quickly identify processes that are ripe for automation. And even more interestingly is they actually help with the calculation of the ROI for an automation project. And this really is the dream of most IT transformation projects.”
“35% of the workforce today are millennials or 75% of the workforce will be millennials by 2025. This audience has incredibly high expectations for modern digital experiences at work. And they aren't the folks that like to copy-paste data between 17 different systems or in green screen terminal applications and things like that. They really want modern, not rote, creative and innovative experiences at work. So the workforce is shifting.”
“…there's a huge surge in demand and the need to digitally support and enable your employees. We can see this in really unprecedented demand in terms of the acceleration of digital projects. We project over the next five years, there'll be as many digital solutions built in the enterprise as were built over the last 40 years. Just huge, huge demand.”
“…the best time to start building out your automation strategy and getting serious about automation for all functions of your company was probably three years ago. The second best time is now as the saying goes. And just the reason is that the return on the ROI on projects in the automation space really is phenomenal. There's a huge amount of digital processes that have been accumulated over the last two decades that are just waiting to be enhanced and improved through automation. You can improve the employee experience, make your employees happier, keep them working at high cognitive high value tasks. You can improve customer experience, solve the customer's problems faster and more efficiently than ever before. And you can do all of this with relatively minimal budget, but large outsize return.”
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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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
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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