5 Hidden Costs of Outsourcing IT Services

Many organizational decision-makers choose to outsource because they see it as an easy way to cut costs. What they fail to realize, however, is that it’s rarely ever that straightforward. And since there’s little motivation for service providers to be transparent about these financial risks, business leaders must be diligent about identifying and accounting for these additional expenses. In many instances, it’s actually far less costly to keep IT services in-house. If you are considering an outsourcing arrangement, keep the following hidden costs in mind.

Change Orders

When it comes to outsourced IT services, just about every minor change comes at a price. Those managing outsourcing agreements must stay aware of what these change orders entail and how much they’re going to cost in the end. This can all be avoided, of course, by bringing IT on premise, where fixed IT staff can make changes to how work is performed and take on special projects at no additional costs.

Consulting

Another factor that can send costs spiraling out of control unexpectedly is consulting. These days, nearly all IT and digital engagements are led by consultants, which can skyrocket expenses far beyond what was originally anticipated. While some areas of IT service have moved to outcome-based pricing models, the consulting piece is still typically assessed on the basis of time and materials, which can vary. And while some organizations appreciate the added value, others may find the additional expenses difficult to justify.

Loss of Control

Over time, things change. Business leaders rotate, companies evolve. As a result, criteria originally agreed upon in the outsourcing contract can become obsolete. It’s imperative that someone holds the service provider accountable to deliver what was agreed on and paid for. It’s also important to audit and eliminate services that may no longer be needed. According to ISG, the average outsourcing contract loses anywhere from 5 to 15 percent of its value because the client is paying for more than what is actually being delivered.

Lack of Agility

One of the costliest things about outsourcing, and sadly one of the most often overlooked as well, is how these contracts can stifle a company’s ability to innovate and therefore compete. Far too frequently, a client will find themselves locked into an agreement at a time when dynamic change is occurring all around them. As such, they become locked out of next-generation technology opportunities, like robotics, AI and deep learning. Likewise, many traditional sourcing models don’t support things like data analytics and mobility. Adapting an existing outsourcing relationships to account for these changes can be incredibly costly, both in terms of time as well as money.

Employee Disengagement

When the costs associated with outsourcing are discussed, one thing many fail to consider is the impact such an arrangement can have on staff retention – particularly during the initial transition period. When IT employees have to make the shift from performing the work to simply managing it, there can be a sense of frustration. This is especially true for highly technical resources. The change in focus can lead to a feeling of being out of touch, and the inability to roll up their sleeves and get their hands dirty can cause a spike in attrition levels. Along with that inevitably comes the cost of hiring and training.

In conclusion…

At first glance, outsourcing IT services can seem like a great way to cut costs and stay competitive, but if you’re not careful, it could end up having the opposite effect. Decision-makers considering outsourcing should carefully weigh the financial risk – including the hidden costs, such as those listed above – to determine whether such an arrangement is truly a viable option.

On-premise IT services, on the other hand, can be surprisingly cost-effective, particularly once all the true costs of outsourcing are revealed. For instance, with on-site IT, changes can be made without additional expenses incurred and there is no need for costly consultants. And with internal control comes the ability to scale and adapt to changing technological landscape. Employees are happier and the company is able to compete at a higher level.

Curious about whether in-house IT services would be feasible for your company? It starts with the right foundation. Right now, you can experience our fully functional, next-generation IT automation and orchestration platform free for an entire 30 days. Click here to start your free trial today.

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How IT Service Management Can Be Transformed With Intelligent Chatbots

In today’s digital landscape, organizations are facing increasing demands to do more with less, keeping expenditure at a minimum and efficient output at a maximum. In response, more and more enterprises are turning to artificial intelligence to bridge the gap. In fact, a recent report by Oracle revealed that 80% of brands either already use or plan to implement AI — specifically chatbot technology — to better serve customers by the year 2020.

But what about internal customers? Couldn’t they, too, benefit from chatbots? The fact is that the IT help desk has become an indispensable component of business success. With increasing pressures to cut costs and a growing demand to drive efficiency, however, IT technicians and administrators often find themselves struggling to keep their heads above water. As a result, delays and bottlenecks impact end-user productivity, and IT talent is wasted.

I believe that intelligent chatbots have the potential to revolutionize the way the service desk is run, transforming inefficient, manual-laden workflows into a streamlined, self-driving operation.

What Are Chatbots?

Chatbots are essentially computer programs that are powered by artificial intelligence and machine learning technology to facilitate automated, digital conversations with people. If you’ve ever used the online chat feature of a website, it’s highly likely that you were interacting with a bot – and chances are, your issue was resolved entirely without the need for any human intervention.

Intelligent chatbots are capable of understanding language, both written as well as spoken, and contextually interpreting that information to a significant degree in order to produce an appropriate response. In addition to pre-programmed data, intelligent bots also have the ability to extract data from various sources, such as wikis, best practices and user guides to help end users resolve issues quickly without having to open help desk tickets.

The Role Of Chatbots In IT Service Management (ITSM)

Some experts estimate that anywhere from 30% to 50% of all Level 1 help desk support functions are repetitive in nature (password resets, anyone?). Not only are these tasks time consuming and monotonous, but they are also quite costly from a human resource perspective.

Paying skilled IT personnel to perform laborious elemental work day in and day out isn’t just a waste of money. It’s a waste of talent. And when the work isn’t meaningful, the risk of employee turnover also goes up.

Meanwhile, from an end-user perspective, sending help desk tickets and waiting for responses impedes productivity. So, not only are IT agents bogged down by tedious requests, but the entire workforce can potentially be impacted.

A Better End-User Experience

Introducing chatbots into the IT service management process enables organizations to shift the regular and repetitive tasks and workflows away from human agents and toward AI-powered software. Intelligent bots are capable of answering simple user inquiries, troubleshooting issues and providing self-service remediation options. When an end user has a problem that they need IT’s assistance to solve, they can get their answer or resolution via a quick chat using a conversational electronic interface — just as customers do when using a live chat.

As a result, end users no longer have to wait for resolution. In fact, in many cases, employees can be empowered to use self-service options to resolve issues entirely on their own.

Cutting Costs

Simply requests like password resets are time-consuming and costly. Consider the time it takes for the end user to get locked out, open a ticket to the help desk and wait, as well as the time it takes the IT agent to manually process the request. Surely there are better ways for talented IT professionals to spend their time and energy.

Shifting simple but essential tasks like this from human to chatbot can save tremendously, both in time and in end-user productivity levels. And this is just one example. Take into account the aforementioned 30% to 50% of other repetitive Level 1 help desk functions, and you’ve got something you can really take to the bank.

Finally, though equally as important, introducing intelligent chatbots into the service desk system can take much of the pressure off of IT personnel. Enter artificial intelligence and machine learning, which, according to Gartner, Inc., will free up to 30% of support capacity for IT service desksby the year 2019. Rather than wasting time and energy on mundane, tiresome tasks, IT workers can use their creativity and cognitive abilities to perform work that interests and challenges them.

Getting Started With AI And Chatbots

If your organization decides to invest in chatbots, maximize your investment by looking for quick wins that solve specific ITSM issues, or tasks that can be automatically performed by a bot. These are typically relatively easy to automate but will produce a fast and measurable return on investment.

A good place to start is with a simple IT service desk chatbot that can create and assign tickets, escalate tickets to real agents, assist end users with questions and provide important updates on critical incident IT and security.

Intelligent bots can take that a step further. In my experience, here are a few good places to start:

• Ticket handling: Categorization, prioritization and assignment of tickets.

• Level 0 support: Leveraging artificial intelligence to provide 24/7, self-service support.

• AIOps: Use of advanced analytics technologies to proactively detect, diagnose and address problems.

• Decision support: Utilization of the predictive capabilities of machine learning algorithms to make better, more data-driven decisions.

Simply put, intelligent bots have the potential to supercharge the IT help desk, skyrocketing the productivity of both the support agents and the end users. This ultimately results in greater efficiency, lower operational costs, improved retention and the opportunity to innovate at a much faster rate. And in today’s digital age, this is what will separate the success stories from the failures.

This article was originally published in Forbes Technology Council. To see the original publication, click here.

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Have you fallen for these 3 common AI misconceptions?

Artificial intelligence has been around for decades, though it just recently became a hot topic in the business world. During this time, many individuals have confused AI with automation, sometimes going as far as using the two terms interchangeably. The reality is, while the general concept may be similar, the two are distinctly different. Furthermore, this confusion has led to a number of other myths and misconceptions. We’d like to clarify a few things, beginning with the difference between AI and automation.

IT process automation involves programming technology to perform routine, manual tasks based on a prescribed set of instructions. Artificial intelligence takes this concept several steps further by using intelligent machines which are capable of displaying human behavior, thought and decision processes. Where automation is essentially set in stone (unless manually modified), an AI machine increases its own intelligence and can adapt its actions automatically, based on information it receives.

From a business perspective, artificial intelligence has the power to help organizations make more informed decisions. It can extract valuable information from mountains of data, analyze and organize it in a logical manner and essentially close the gap between insight and action. Given its complexity, however, AI is still often viewed in a negative light. To change this, we’d like to dispel three of the most common misconceptions as follows.

Artificial intelligence is a distant dream.

Many people believe that AI is a technology that won’t be readily available and practically applied until many years into the future. The truth is, widespread adoption of AI, both in our professional and personal lives, is much closer to becoming a reality than you may think. In fact, given that so many organizations across all industries and around the world are already employing automation to some degree, the idea that AI could be worked into the mix isn’t all that far-fetched.

Artificial intelligence isn’t really going to make that much of an impact.

The idea that AI is somehow inapplicable in the business world stems largely from the technologies complexity. People tend to discount things they have difficulty understanding. The reality is that AI is not only practical for business use, but it’s incredibly beneficial. The machine learning component of AI means that computers will have the ability to learn without the need for programming. It also has the capability of mining and analyzing big data to extract valuable insights which can then be put into action to achieve better results. These are things every organization can benefit from.

Artificial intelligence is going to eliminate the need for human workers.

While it’s certainly true that AI will make human workers redundant to some degree (think routine, repetitive tasks like reporting and data entry), this technology will not fully replace humans. This is particularly true in certain fields that require high-touch interactions, like HR, health care and consulting.

Likewise, while intelligent automation will streamline and optimize operations for many organizations, it cannot and will not replace the need for the development and nurturing of customer relationships. AI can, however, leverage data to provide human workers with the insight they need to deliver better, more personalized service.

And because implementing and managing new technology will always require some degree of human input, new roles and responsibilities will naturally evolve, which means that for many, AI will present great opportunities.

Like it or not, AI isn’t going anywhere. In fact, 61% of businesses are already implementing artificial intelligence to some degree. By addressing and overcoming the biggest misconceptions about AI, companies can harness the power of intelligent automation to streamline operations and provide competitive advantage.

Want to see AI in action? Click here to request a demo. Or better yet, claim your free 30-day trial today!

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Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations – Red Hat’s Alessandro Perilli

 

Oct 30, 2018    Episodes

 

 

Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations

In today’s episode of Ayehu’s podcast we interview Alessandro Perilli, General Manager, Management Strategy at Red Hat

How can senior IT executives best deal with the increasingly complicated nature of managing IT operations?  The ever-growing demand for computing resources, the expanding complexity of computing environments, and the critical shortage of experienced talent are all seemingly conspiring to derail the C-Suite’s best laid strategic plans.

Alessandro spends a lot of time working on these issues as part of his role at Red Hat.  He believes that the proper alignment of automation, public cloud infrastructure, and shadow IT are the key to solving this 21st-century challenge.  Alessandro also has a unique recommendation for CIOs, CTOs, & CISOs on the #1 thing they should do to prepare their personnel for this rapidly shifting landscape.



Guy: Welcome everyone. We have another great guest for this edition of Intelligent Automation Radio. Joining us today is Alessandro Perilli, the general manager of Management Strategy for Red Hat, who are, of course, best known for the Linux distribution of the same name, but they do lots of other things too. Alessandro is focused on long term strategy for the company’s efforts in automation, artificial intelligence, and IT security among other things. All of these are topics this podcast is very focused on as well. He is a highly regarded expert on cloud management and virtualization, and is a frequent speaker at major industry events.

Alessandro, welcome to Intelligent Automation Radio.

Alessandro: Thank you. Thanks for having me. It’s a pleasure.

Guy: Your name really rolls off the tongue, and it’s fun to pronounce, so I may be saying it quite a few times today.

Alessandro: That’s fine. No problem.

Guy: Alessandro, before you became general manager of management strategy for Red Hat, you were a Gartner analyst in charge of cloud computing and automation for over three years. During that time, you no doubt had numerous conversations with high level IT executives from large enterprises around the world. Could you please share with the audience what you would tell organizations are the top 3 reasons they should consider automating their IT service, Cybersecurity, and DevOps operations?

Alessandro: When I was with Gartner, I started almost seven years ago, and that time was very different. The kind of environment that we are was quite a different situation compared to now. The public cloud computing was starting to emerge and now it’s a reality, well-established one, and so the kind of advice that I have for top executives in large enterprises at that time is kind of different than the one that I would have for them today. If this is a question for today, as I think it is, the answer is there is just one answer, which is you technically have no choice but to automate, to cope with the scale and complexity of very large environments that the environment that exists today.

I’m not talking just about public cloud environment. The facilitating large scale deployment or workloads because the infinite elasticity that they offer at the relatively cheap price, but also because even when you are on premises in private cloud infrastructure or in a hybrid cloud IT environment, you start to shift from traditional monolithic application architecture to more aggregated ones, and so you start to go for microservices architectures and cases supported by virtual machines, but then containers and then eventually [inaudible 00:02:51]. So even within the same single application, you start to have a lot of moving parts and there are a number of complexities that are related to provisioning those parts and then be sure that those parts are properly configured and updated and patched and retired and replaced and so on.

And then you need to multiply that single application architecture that has become so complex for all the other applications that you have in a public, or a hybrid cloud environment. To give a sense of the scale, that this is something that any CIO in a large enterprise knows already, the average size of an application portfolio in a large end user organization like the ones I used to consult for when I was in Gartner, is of over 1,000 applications. Now, this over 1,000 applications used to have a monolithic architecture with just three peers, right? The web frontend, the middleware, the backend services, the database, and that was it.

Now is that you move from those three tier architecture to seven, eight, 9, 10, 20 containers in a microservice architecture. There’s an explosion of components, and then there is the infinite scalability I mentioned before that forces the use of automation. There is no chance that a human operator, no matter how skilled, no matter how well paid, can possibly cope with that level of complexity. This is the number one, the only piece of advice that I feel it’s really necessarily [inaudible 00:04:39].

Guy: Yeah, that’s something that we talk about all the time here is that people don’t scale very well, and that’s why automation is really the only practical alternative to dealing with the complexity, the explosion in demand for computing resources, et cetera. What are the big challenges you see today in automating IT and Cybersecurity environments?

Alessandro: Cyber security is a very special, I would say, layer or corner of the whole IT organization and the computing stack. There are at least two major issues that I see today, and in my role, I talk to a lot of organizations about automating security. The number one is that if you look at the security ecosystem as it is today, you see that there is a massive, unprecedented amount of security solutions in the market, not just from established vendors, but also from startups that they merge in waves every year.

The amount of capital that is invested by venture capital firms into the security industry is reaching unprecedented peaks. We’re talking about almost four billion, according to the last research by CB Insights. This amount of capital to build new solutions corresponds to an enormous amount of spending on the end-user organization side. We’re talking about something close to $100 billion spend on security solutions. Now, I used to be in security when I was very young at the beginning of my career, almost 20 years ago. You would expect that since then, a lot of the problems that existed at that time has been solved, it’s been addressed, and are pretty much solved problem from an engineering standpoint, but actually, it’s not the case.

You would expect that the ecosystem would have consolidated compared to those times, and instead, no, the ecosystem has grown and grown and grown, and it’s exploding in size. You will lead to think that, “Okay, there is this explosion of vendors. This is the injection of capital. This is a massive amount of spending. These solutions are all for new problems that emerge as we got to deal with new technologies, but it’s not even the case. Quite the opposite.

The problems that we’re trying to solve with this new wave of solutions are always exactly the same that existed 20 years ago. There is an inherent inefficiency in the way the security industry is doing things, that it’s not being fixed by any of these new wave of startups that promise to disrupt the space. Quite the opposite. If you look at Gartner surveys or IBM surveys or all sorts of … [Silent 00:07:38] surveys, all sorts of companies, from all different corners of the IT industry, they all confirm that a chief information security officers are more and more concerned about their capability to secure, to protect the environment, to respond to attacks. This is getting worse. A lot of them complain that they don’t have enough security personnel to address this.

A lot of them lament that the intensity of the attack increased, and the time to respond to the attack increased as well. Why is all of this? There’s always a number of concurrent factors like in a very complicated situation, but I personally believe, and this is the first, of the two main problems that we have today in cybersecurity in terms of automation, is that when you look at the ecosystem, these vendors, the solutions don’t integrate with each other. They just don’t. They don’t talk to each other in any way.

Yes, there are minor connection, integrations between one or two solutions provided by the same vendor or there might be integration between two different vendors at the site to get to win a partnership before a limited amount of time because it’s a marketing effort, but that isn’t [inaudible 00:09:05] not universal integration like … And the standards that are being provided in the past didn’t have any market traction to the point and now we have a new wave of standards that are trying to solve the problem. This is a never ending cycle of attempting to solve the problem, which is clearly not working. This is number one problem. The biggest one problem is that even if you want to automate the security industry, those tools don’t integrate with each other. The solutions don’t integrate with each other. That is the first problem to solve.

The second problem is not technical, it’s not standards, it’s nothing to do with the industry per se, but it’s cultural. Security professionals, and I come from that world, so it’s a very familiar to me, they’re just very, very, against automation. There is a general mindset, that is we’re not gonna automate security because if things can be blocked, mission critical services and systems could be just stopped and somebody is gonna complain, and we don’t wanna get into the sort of liability responsibility and so on, which is insane. It will be like AWS, Amazon saying, “We don’t run automation with AWS. We prefer to do things by hand because we don’t trust automation.”

They will never reach the scale that they reach. But Amazon.com, in terms of warehouses, for example, for the Red Hat part of the business, and in terms, of course, of cloud computing. This is just untenable, so the mindset to the security professional has to change and has to evolve to accept and embrace the fact that at this scale, at this level of complexity, the only way is to automate the security layer just like all the others have been automated. Compute, storage, networking, all of them, security is the last one, and that has to change.

Guy: I think with the others, there were also some resistance at the outset but I think with security, there is a more pronounced problem and that is that according to various surveys and studies by 2021, there is gonna be somewhere around three and a half million unfilled positions in security, and you’ve just … In the next three years, less than three years, you’re simply not gonna find enough people to get trained on the complexities of security in that time period, so the only solution is to automate a lot of the work that those people need to do.

Alessandro: Absolutely, but even if we would have enough skilled personnel that is available to do those things, you will still not be able to cope with the speed. So far, I’ve been talking about scale and complexity, but there is a third element, a third dimension, that we’re getting into play very soon in the near future, which is the speed. What happens when artificial intelligence is used to drive these hacking attempts? These attacks. At what speed are the attacks and variations of the same attacks all around the world are executed if it’s an artificial intelligence that is driving that kind of effort? How a human, no matter if there are enough humans, but how a single human can cope with that speed? That is beyond the possibilities that any of us have, and so the only possibility here is that we go for automation, regardless of the personnel availability.

Guy: Yeah, that’s another thing that we tell people as well is that the attacks being launched against you are usually automated, so shouldn’t your defenses be as well?

Alessandro: Mm-hmm (affirmative), absolutely.

Guy: What do you feel then are the top skills a CIO or CTO or chief information security officer should encourage their staff to acquire in preparation for implementing automation in their environment?

Alessandro: There are at least a couple of aspects that are connected to each other. The first one is that in my experience at least, a lot of the security professionals, but also the traditional IT operation people, that might or might not be involved in security, don’t have a sense of operations at scale. I have a certain size of data center to deal with but it’s nothing even remotely close to the size of an AWS or an Azure or Google Cloud and even the smaller public cloud service providers.

A top skill to acquire for all these professionals is to start to understand how things change at scale. What does it mean to rethink an operational framework or a security framework at the scale that we are about to face or we’re facing already. That is number one.

The second aspect is that connected to this, is that I saw a lot of security professionals looking at automation as a very tactical tool, as a system that can in a very small pockets and limited fashion, try to be used to solve a minor task in the security analysis process. That is, I believe, limiting the possibilities that automation offers in security. My recommendation will be to shift in thinking from thinking security as a tactical tool and thinking more in terms of strategy. Automation, part of the security framework being used systematically and in a pervasive way throughout all the different operations that a security team performs during the day, could really make a difference in terms of the approach and the posture that the team has towards the discipline.

Guy: In kind of a related question to that, what’re your thoughts about general purpose automation platforms versus function specific automation platforms? Specifically for IT process automation, specifically for cybersecurity automation, specifically for DevOps?

Alessandro: This is a topic I’m extremely passionate about because I saw through two decades of career with Gartner, before Gartner, now after Gartner, I saw exactly what happens with customers, no matter how skilled they are, are put in front of general purpose automation tools or platform or frameworks, call it the way you want. What happens is that when these tools, and not just these tools by the way, any sort of IT tool kits that has general purpose capabilities suffers the same kind of issue in my experience, and it’s this.

When customers are put in front of those general purpose tools, and they come to the table with a very specific use case or two, three use cases in mind, and they’re being offered something that in theory will solve all those use cases because the general purpose nature of the platform is such that it can be adopted to solve different issues, but in practice this general purpose platform is not excellent at any of those use cases, and requires quite a lot of effort from the end user organization side in terms of crafting and adapting into the specific the business needs that they have with certain use case A, B, or C.

Customers struggle to see the immediate return on the investment, and the actual value of general purpose platform. They very much prefer, even if in theory it’s counterintuitive that when they ask logically what they prefer, of course they prefer a general purpose platform because they think that they can return on investment in a lot more use cases. There’s a bigger return, but in practice, they always go for point solutions. They tend to prefer point solution. This is the same kind of approach, if you think about it, that you would have in your home repair on a Sunday morning at home kind of routine.

If you’re doing some sort of home fix of any sort, you have two choices. You go for a Swiss Army knife, that is a general purpose toolset or you go for highly specialized tools that are more efficient to solving a problem. A hammer, a screwdriver, and so on. Why does it that humans always go for the specialized tool rather than just buy and use a single general purpose platform? The reason is that we tend to think in terms of what is the most efficient tool to get the job done? No matter if that fills the drawer and takes all the space and it costs probably 10 times more than a general purpose platform, we tend to go in that direction. I saw over and over and over in my career in IT, general purpose technologies and approaches failing over a long time for a lack of market traction for what I believe is this reason.

Guy: Touching upon the issue of the talent gap and the skills shortage, I wanna change gears a little bit and ask you about chat bots, which have become very popular lately as a new channel for IT organizations to deliver automated self-service. What do you think the future looks like for automated self-service versus the traditional way of delivering support via service desk?

Alessandro: This is an interesting question, and I have very strong opinion about chat bots in general, not necessarily popular opinions, but these are also two questions in one. One is the future of self-service provisioning and another one is what the chat bots, what kind of market opportunity is there for them? We saw an explosion in the industry regardless of automation, regardless of cyber security or IT operation in general chat bots had quite the momentum in the last few years, but then now we’re seeing a lot of companies that were offering these solutions just stopping it, so I think Facebook is one of them. There were a number of news in the market recently about the fact that chat bots didn’t create that kind of strong momentum as was initially expected.

What’s the reason for that? In my opinion, chat bots are just frontends. They’re not really solving the behind the scene problem, which is how do I automate a number of processes in the most efficient way, that it’s not complex. That it’s manageable. That it’s documented in a way that doesn’t require extraordinary amount of efforts in terms of integration & customization. They are frontends. They leverage artificial intelligence to do natural language processing, and they are in theory meant to simplify the interaction with the customer, but the problem is that the level of technology maturity that we have today is far, far, far away from what it’s supposed to be.

I am an Amazon Echo customer, and so I use Alexa all the time to do all sorts of tasks, and I’ve been doing for quite a few years, and I tried all the other assistants that exist on the market. I have to say that there is a massive gap between what the state-of-the-art solution are doing today in terms of natural language processing versus what is in our mind after watching series like Star Trek: The Next Generation, or movies like Her, for example. It is so far away. The chat bot per se is not yet going to give you that extra help that we hope it will in one day, in terms of simplifying the interaction with the automation layer for the provisioning of whatever we’re trying to provision. This is first part of the answer.

The second part of the answer is, “Okay, what is the future of self-service in provisioning the orchestration & all the other things?” I see, and I’ve been seeing this for quite a long time, a shift in terms of power, control, autonomy, that moves from central IT to line of business. The line of business are gaining more and more autonomy, control over the budget, selection of technologies that they want to use, and they tend to think in terms of, “Okay, how can I get as fast as possible to the business outcome I’m hoping to have?” Because they are measured by completely different metrics compared to the central IT. Central IT has a completely different mindset from line of business.

In this trend that I see accelerating and in part is fueled by this DevOps methodology kind of approach, a giant methodology, the capability for engineer to be completely independent, all of this is just accelerating this autonomy. The need for self-service is increasing, and it’s driven by, I would say a frustration of the line of business that being depending by the IT operation team for way too long. The IT operation team, the central IT has been too inefficient for way too long, and so there’s now there’s demand to let me do whatever I can in a fully automated way. When that is not delivered by central IT, what happens is that, and I saw this so many times in the last 10 years, then the line of business simply circumvents all the rules that exists in terms of compliance, in terms of security, and then just go and use public cloud service providers often in the form of software as a service to just get the job done as fast as possible.

I think that the future is gonna be completely automated in so many more ways than the ones we see today. I don’t know if the frontend for that automation will be chat bots, because I don’t see enough progress, but certainly we will have a way more automated future.

Guy: I think that Shadow IT, which is kind of a catch all term for what you just described, is definitely something that we’re seeing more and more of, and it’s been enabled by the public clouds like AWS, Azure, and Google Cloud. With that emerging trend and with the move towards an inevitable automation future, what is the one piece of advice you would give the CIOs, CTOs, CISOs considering whether or not to dive into automation?

Alessandro: Well, as I said in the beginning of this conversation, I don’t think that any of the persona have any choice. They’re forced to at least understand what does it mean to operate at scale, to do IT operations or to do security at scale. The professionals that report to them and need to develop that kind of awareness, if not the skills to just cope with the kind of speed that we see today in the market in the world. The one piece of advice is certainly to invest a lot in education. I am amazed, this is a small thing or it sounds so. I’m amazed by how many executives in very large enterprises never went to attend an Amazon Reinvent Conference, and they never saw in person what we’re talking about here.

A lot of people read about this in press articles or in news outlets but they don’t quite understand or develop the awareness that is necessary. Training is for the executives in the underline is critical to understand there is no other option. This is one thing to focus on. I’m a big believer in education, so I believe that training is fundamental to progress in any kind of IT management or enterprise endeavor in a large organization. This is certainly one thing.

The other thing is, as I said before, to start considering automation, not as a tactical tool, that can kind of shave off some of the time that you spend in doing a number of tasks, but reconsider it completely as a strategic tool to drive IT operations. There is a reason why public cloud providers like AWS, that started from scratch, are getting so massive and so popular and so efficient. It can drive the cost down to the level that it is today. That reason is that they design from scratch, the entire IT architecture to be automated. That was first thing that was part of the design guidelines. The IT operations, but in general the central IT as an organization today, faces that sort of competition, faces the competition of public cloud service providers that offer a better service, a faster service, a more automated service to their own line of business compared to what is offered within the corporate boundaries.

We’re really talking about an existential risk today. For the CIO, for the CTO, for the Chief Information Security Officer, there is all of them are at risk of losing their audience, and the audience as well validates their presence in the enterprise because they simply cannot think in the same way a public service provider is thinking. The mindset has to change before anything else in terms of processes, in terms of technologies can change.

Guy: Alessandro, we’re running low on time but I can’t let you go without asking about the H+ project you’re the founder of. Can you please tell our audience a little bit about what that is and the kinds of things you’re working on?

Alessandro: Sure. First of all, I need to say that that is not in any way related to my work in Red Hat. It’s a side project. I’m very interested, and I’ve been studying a lot for years a number of different disciplines that are related to human body augmentation or human announcement technologies as the industry calls them, and they go from neural interfaces to bionic prosthetics to genetic engineering, precision medicine, nano robotics and so on and on and on. The reason why we’re patient about this thing I question from neuroscience and genetics and cognitive psychology, is that I believe that we are a fundamental point of change for the way humans process information today. The scale of information is so massive for us to process, and you can tell by just looking at how people are glued to their phone when you go on a tube, when you go on a train, when you just stepped at an office, and everybody is looking at the phone rather than talking to each other.

The amount of information that must be processed are so massive, and there is such a social pressure to be sure that this information is processed in the most efficient way, and so you’re hyperreactive to what the world is saying around you that there is no other way eventually, than the one to augment yourself. I strongly believe that just like traditional prosthetics that exist today in the world, including things like, very simple like contact lenses or pacemakers, and so on, as those things became the norm & are perfectly accepted from a societal perspective, so the augmentation in the sense of blending together technology with the biology to increase human capabilities, and process more information and being faster in making decisions and better in making decisions, computer system, if you want to send this play is gonna be a mandatory step for the humankind. I don’t see any possibility for the future, so I’m very interested in that, and I’m interested in understanding what startups are doing what in the space and what kind of new academic research comes out.

H+ is an open research initiative that basically collects in a completely open way so anybody can access completely free, can access to all the things that I collect in my free time that talks about all these different technologies. Basically, it’s a way to track how we’re going in terms of the next stage, what I believe will be our evolution.

Guy: That’s great. All those issues that you’re covering. They just prove that there’s no longer anything such as science fiction. It’s just science.

Alessandro: Absolutely.

Guy: All right. It looks like that’s all the time we have for today. Alessandro, I’ve really enjoyed our conversation, and thank you again for being our guest.

Alessandro: Likewise. It was great. Thank you.

Guy: Alessandro Perilli, General Manager of Management Strategy for Red Hat and founder of the H+ project. Thank you for listening everyone, and remember – don’t hesitate, automate.



Alessandro Perilli 

General Manager, Management Strategy at Red Hat

Alessandro Perilli leads management strategy at Red Hat, including company efforts in cloud management, automation, predictive analytics, and self-healing IT. Alessandro also develops the vision behind new management initiatives in multiple areas (artificial intelligence, IT security, etc.).

Prior to joining Red Hat, Alessandro was a Research Director at Gartner, leading the private cloud research program in Gartner’s Technical Professionals division. Alessandro also spent time consulting for large end-user organizations and cloud vendors, advising enterprises on how to develop a cloud adoption strategy and writing acclaimed research papers, including “Climbing the Cloud Orchestration Curve” and “Market Profile: Cloud Management Platforms”.

In 2014, Alessandro was listed in Business Insider’s Top 39 Most Important People in Cloud Computing. He has been a keynote speaker for 18 years in a row.

Alessandro started his career as a practitioner in cybersecurity, creating one of the first ethical hacking courses in the world, authoring a book, and speaking at dozens of conferences about attack methodologies used by the hacking community.

Today, Alessandro is also fully dedicated to studying human enhancement technologies like neural interfaces, augmented reality, biohacking, bionic prosthetics, genetic engineering, nanorobotics, and wearable technology. He tracks advancements in these disciplines through H+ (https://h.plus), an open research project that he launched in 2017. 

Alessandro can be found at:

E-Mail:               alessandro@alessandroperilli.com

Twitter:             @giano

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

Quotes

“…you technically have no choice but to automate, to cope with the scale and complexity of very large environments that…exists today.”

"What happens when artificial intelligence is used to drive these hacking attempts?"

“A top skill to acquire for all these professionals is to start to understand how things change at scale. What does it mean to rethink an operational framework or a security framework at the scale that we are about to face or we're facing already.”

“…and I've been seeing this for quite a long time, a shift in terms of power, control, autonomy, that moves from central IT to line of business. The line of business are gaining more and more autonomy, control over the budget, selection of technologies that they want to use, and they tend to think in terms of, "Okay, how can I get as fast as possible to the business outcome I'm hoping to have?"

“I think that the future is gonna be completely automated in so many more ways than the ones we see today.”

“There is a reason why public cloud providers like AWS, that started from scratch, are getting so massive and so popular and so efficient……That reason is that they design from scratch, the entire IT architecture to be automated.”

 

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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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

Reskilling Your IT Team for Digital Transformation

The number of job openings for data scientists is steadily on the rise, with IBM predicting a 93% growth rate in data science skills, followed by 56% predicted growth for machine learning skills. Without question, artificial intelligence experts, machine learning developers and data scientists are in high demand, and as that demand rises, the number of qualified candidates to fill open roles will dwindle.

In fact, according to the 2018 State of the CIO report, 36% of respondents cited difficulty filling roles for business intelligence and data analytics. AI roles also made the top 10. Rather than hiring new employees, many organizations are instead looking to reskill existing staff to prepare them for the roles needed to achieve digital transformation.

Let’s take a look at how some companies across various industries are preparing their existing personnel for the AI era of tomorrow.

Back to School

There is no shortage of formal training programs available at higher education institutions across the globe where those interested in gaining expertise in the way of AI, machine learning and data science can pursue their professional development. The most advanced training typically takes anywhere between a year to a year and a half to complete. It also requires basic programming skills and a solid understanding of programming. There are also a variety of online courses and programs to consider.

Forward thinking companies looking to transform their existing workforce can offer tuition reimbursement and flexible work schedules in order to encourage employees to go back to school. The promise of a newer, better role at a higher pay grade can also be great incentive.

Formal In-House Training

Another way organizations are getting existing employees prepared for digital transformation is to create in-house training centers. These will often include test environments in which trainees can experiment with AI and other disruptive technologies. As employees learn and skills are mastered, the training can then be extended to other teams and departments, including the C-suite.

For those companies that don’t have the capacity to create learning centers, availing themselves of vendor-provided training can be the next best thing. For instance, Ayehu offers a free Customer Success Program as well as free Webinars each month aimed at accelerated training of various AI and machine learning applications.

Peer-to-Peer, On-the-Job Training

As companies begin to build up a pipeline of skilled internal talent, they can then begin investing in peer-to-peer mentoring opportunities to further spread knowledge and education. For instance, a department might attend a starter course to familiarize themselves with the concepts of AI, machine learning, etc. and then transition to a mentoring strategy thereafter.

This approach begins by incrementally exposing employees to smaller areas where the use of disruptive technologies can have a large-scale impact. Once comfortable, they can then move toward improving workflows and tackling other, more complex projects – all under the supervision of experience mentors. Many business leaders utilizing this approach feel that it’s much more effective and that employees learn, absorb and build upon critical skills much faster than they would in a traditional classroom setting.

Keeping Pace with Change

The challenge of reskilling to facilitate digital transformation is that technology is evolving at an incredible rate. Keeping pace with the rate of innovation is the key to success. That means developing and fostering new skills on an ongoing basis.

To address this, some organizations invest in regular educational sessions and AI-related training held either ad hoc or at specified intervals. Access to routinely updated educational resources, like online tutorials, onsite training and industry/sector conferences is another option. The thing to remember is that, given the rapid rate of change, you simply cannot overeducate your employees.

With a staffing shortage that’s growing by the day, business leaders must compensate by reskilling existing employees. Otherwise, they risk losing ground in the race to digital transformation.

Give your team a solid foundation by investing in top-of-the-line, Next Generation Automation and Orchestration. Give it a try free for 30 days. What do you have to lose?

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Managed Service Providers: Could this be hindering your growth?

Making the transition from basic IT support to a full-fledged Managed Service Provider isn’t necessarily easy. There will inevitably be a number of obstacles to overcome along the way. Thankfully, many have gone before and essentially paved the way for newer players to enter the field. Learning in advance what challenges you can expect and the best way to meet those challenges head on will help you avoid potential pitfalls that might otherwise become a barrier to growth. Let’s take a closer look at the three most common issues today’s MSPs struggle with.

Fear of Change

Let’s face it. Making a major change to your business model is scary. What if things don’t work out? Will you be able to recover? The reality is, however, that success requires a certain degree of risk. If your team is feeling particularly leery of making the shift to Managed Service Provider and/or pursuing aggressive growth initiatives, the key will be communication. Be open, honest and transparent. Acknowledge the uncertainty many of your staff members are experiencing and take the time to address those concerns and put them to rest.

Additionally, there may also be an underlying fear that switching to managed services will result in the loss of business. Chances are very good that this will, indeed happen, as not everyone is suited for an MSP level of support. Understand, however, that while you may very well end up saying goodbye to a small portion of your customers, over time you will gain others to replace them. It’s just part of the shift.

Lack of Differentiation

Without question, the Managed Service Provider field is highly saturated. The organizations that thrive are those that have found a way to stand out from the competition. This is especially critical for those just entering the marketplace. If potential clients can get the same service from an established player that they already know and trust, why would they take a chance on you? It’s up to you to convince them otherwise.

To do so, you must identify what new and better services your company can offer. For instance, if your prospects are seeking growth themselves, focus on services that help maximize efficiency and empower them to achieve those goals. If you’re unsure of what angle to take, tap into your sales team to find out what they’re hearing in the field. Or, better yet – ask your clients and prospects directly.

Underpricing

Finally, there is the challenge of how to appropriately price your services. In fact, making a switch from fixed price to a more profitable pricing model can be a difficult transition. This is often compounded by a mere lack of full understanding and a subsequent underestimation of the true value of the services you will now be providing.

At the end of the day, you want your customers to pay you what you’re worth. If you are undervaluing your services, chances are you are also underpricing yourself, which means you will not be able to achieve sustainable growth. Be honest and do your homework. Figure out what you are worth and what you will need to make in order to bring your business to the next level and then implement the necessary changes to make it happen.

Now that you’ve got a clearer picture of what may be standing in your way, it’s time to get to work turning things around. Here are a few helpful pointers, to overcome these common issues:

  • Evaluate your current business plan and strategy, as well as team member skills and abilities.
  • Utilize technology and tools, like intelligent automation, to make service delivery much more efficient.
  • Build technical credibility through key certifications and specializations.
  • Understand your pricing model to ensure that it properly supports your level of service.
  • Keep in close contact with customers to recognize and capitalize on trends and opportunities. 

Making the transition from basic IT support to full-fledged managed service provider may seem like a daunting task, but it doesn’t have to be. In fact, with a well thought out plan backed by a confident team and advanced technology, you will be well positioned to compete in today’s fast growing market.

Want to experience the power of intelligent automation backed by AI technology? For a limited time only, get a free 30 day trial of Ayehu by clicking here.

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Ayehu Announces Free 30-day Trial Availability of its Newly Enhanced Next Generation Intelligent IT Automation and Orchestration Platform

The Free Trial Version Featuring an Enhanced Workflow Designer and AI-Powered Automation Engine is Now Available for Download from the Ayehu Website

San Jose, CA –- October 16, 2018 Ayehu has enhanced its Next Generation Automation and Orchestration Platform powered by AI. This latest release is designed to deliver IT and security operations teams even greater productivity and ease of use. To give enterprise users the chance to experience the platform firsthand, Ayehu is offering a free 30-day trial.

Today’s enterprises are overwhelmed by a massive amount of system alerts, incidents, and user requests. This is further complicated by the IT and security skills shortage. The need for streamlined processes and fast, quantifiable results has never been greater.

Ayehu’s Next Generation Intelligent Automation Platform incorporates artificial intelligence to augment human ingenuity, in order to enable the creation of the next generation of intelligent applications. The platform delivers no-code, automated workflows that help enterprises save significant time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure.

The new version includes the following enhancements:

  • Productivity – For greater efficiency and results, the platform now features a full web-based GUI, includes power search capabilities, a library of over 500 pre-built activities and a codeless workflow designer. Out-of-the-box integration packs are also available, with advanced Rest API for rapid integrations with 3rd party applications
  • Scalability – Scaling to support a high volume of incidents and safe guard against a single-point-of-failure, the latest release features built-in automated load share, and the ability to run more workflows simultaneously
  • SaaS Ready – Ideal for hybrid deployments, the new version can run multiple instances on the same virtual machine, run different environments on the same station, and manage all environments from one place
  • Chat Bot Integration – Ayehu BOT platform is integrated with Slack, Microsoft Teams, IBM Watson, Microsoft Luis and other applications for the easy creation of a self-service interface

“Since we launched our intelligent automation platform, customers have realized that artificial intelligence combined with IT automation is a game changer,” said Brian Boeggeman, Chief Revenue Officer, Ayehu. “As we continue to make our solution even easier and more valuable, we are offering a free trial so that everyone can simply start automating today. IT professionals that experience it will immediately see a huge leap in productivity and efficiency.”

To experience Ayehu’s Next Generation IT Automation powered by AI, claim your free trial here. To learn more about the Ayehu Next Generation Automation and Orchestration Platform powered by AI, click here.

About Ayehu

Ayehu’s AI-powered automation and orchestration platform 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. For more information, please visit www.ayehu.com and the company blog.  Follow Ayehu on Twitter and LinkedIn.

How to Become an Intelligent Automation Leader in 4 Steps

Intelligent automation is rapidly transforming the global economy, delivering momentous gains to enterprises that adopt it at scale. One recent article by McKinsey revealed that some organizations have been able to automate 50 to 70 percent of their workflows, generating ROI that reaches into the triple-digits. In addition to cutting costs, intelligent automation can also deliver precision, speed and enhanced customer experience.

In order for organizations to enjoy the full value of intelligent automation, IT leaders must be willing to take a guiding role. Unfortunately, many IT executives find this challenging, whether due to the increased complexity of IT processes, lack of understanding and/or clarity, inconsistent or fragmented tools that hinder scaling, or the misconception that intelligent automation cannot be adopted without major re-engineering of existing processes.

How can these challenges be overcome? And how can IT leaders succeed in their automation initiatives? The answer to these questions lies in the following four key steps along the intelligent automation journey.

Step 1: Evaluate the high-level potential value

The first step in becoming an intelligent automation leader starts with the development of a clear business case. This involves assessing the potential high-level value of the company’s main IT activities. Some examples of what these areas of value might look like include:

Incident Response – A significant number of IT incidents are initiated through support desk requests. These typically result in tickets being created and assigned to Level 1 support agents. While these are the obvious candidates for automation, the portion of tickets that are escalated to specialized L2 and L3 agents are also ripe for the picking, thanks to the advanced technology behind intelligent automation. And since these activities are generally well-documented, categorizing and prioritizing them by automation potential should be relatively straightforward.

Planned Activities – In addition to the one-offs and unexpected support tickets that crop up, IT is also responsible for performing a number of planned activities on a regular basis. These activities typically include things like backups, upgrades and patching. They may also involve more complex security audits. The amount of time and resources required to perform these duties can collectively add up to around 20 percent of the IT budget. Calculating this figure can help determine the potential savings intelligent automation can deliver.

Introducing New Applications – From a business perspective, this activity is often viewed as the one that produces the most significant value. It can also account for an additional 20 to 40 percent of the time and resources put forth by IT. These activities are not exclusive of application development, either. They also include such tasks as testing and hosting. This places increasing demand on both the application team as well as the infrastructure group.

Step 2: Dig deeper to identify which specific use cases are best suited for intelligent automation.

Determining how to effectively implement intelligent automation requires a deep dive to uncover the root causes of issues. It may also involve the untangling of complex systems and the development of an accurate picture of how to leverage automation to extract the greatest value. In other words, the process is a complicated one and requires a certain degree of commitment. Let’s take the three potential use cases above as an example.

Incident Response

Automating IR begins with identifying which incidents are the best candidates, which can be challenging. The goal should always be digging deep enough to uncover the “why” of documented incidents. Without this information, efforts are futile. Text-mining can help by automatically reading ticket descriptions and extracting the necessary insights to sort them into three categories:

  • Automatable
  • Requires machine learning
  • Highly cognitive/manual

This analysis should leave you with a prioritized list of incidents to automate and the type of automation best suited for the job.

Planned Activities

Most enterprise-grade IT departments rely on industry-standard tools to manage their infrastructures. Unfortunately, due to factors such as advanced customization, adjustments due to mergers and specific user requirements, managing these systems often requires a significant amount of manual effort, diminishing the overall value.

For instance, despite the widespread adoption of infrastructure and application monitoring tools, support teams are often unable to respond effectively to the logs being generated, either because there are too many of them or because of the many reasons why they are being generated in the first place. As a result, IT leaders are often unclear on how to approach intelligent automation implementation.

In situations such as this, machine learning technology can be “trained’ to identify the reasons behind alerts and then either recommend or autonomously make better decisions on which action to take. This eliminates much of the complexity for the IT team.

Introducing New Applications

Many IT executives fall into the trap of focusing solely on the reduction of manual labor. As a result, they fail to see and achieve the full value potential of intelligent automation. Faster and more accurate delivery of applications requires the development and design of a new operating model, with an emphasis on DevOps and agile.

Reviewing this entire process to gain an understanding of how to make the most use of this new operating model can result in entirely new approaches to work. Intelligent automation can facilitate some of these new ways of working. For instance, automating the testing process will enable applications teams to iterate more quickly. Likewise, developing a self-service model for things like automated server provisioning allows the operations team to become more responsive. The list goes on.

Step 3: Execute your proof of concept

In order to demonstrate the true value and validate your case for intelligent automation, the next critical step is executing a proof of concept. A great place to start with this is incident management. Organizations that have successfully deployed intelligent automation for incident management have been able to achieve substantial cost savings in a relatively short period of time.

Thankfully, there are many different incidents that can quickly and easily be automated to support your proof of concept, including such tasks as password resets and employee onboarding. In its most basic form, a proof of concept requires the following:

  • Collaboration with subject matter experts to identify where automation can best be applied and understand all the steps and systems involved in a particular process or workflow.
  • Careful selection of an intelligent automation platform. Look specifically for products that can be integrated with existing systems and applications and offers pre-packaged, no-code options. (This will enable rapid adoption and time-to-value.)
  • Obtaining necessary IT and overall business approvals with regard to regulatory constraints, security guidelines and access limitations.
  • Ongoing testing and monitoring to capture results and document value

This phase is also an ideal time to consider building stronger internal intelligent automation capabilities; for example, developing a team to spearhead a future automation center of excellence (CoE). This team will ultimately become the foundation and engine that drives all IPA initiatives.

Step 4: Build intelligent automation capabilities to scale

Achieving the full benefits of intelligent automation requires the development and nurturing of certain skills and capabilities, in addition to rolling out an entirely new company-wide culture. This is essential as successful adoption of IPA requires that automation become embedded into the very heart of the organization itself. There are plenty of ways to accomplish this, but generally speaking, companies that have been successful have done the following three things:

Build on success to expand into new areas of IT (and beyond).

Once the basic tasks and workflows have been automated, it’s time to move on to more advanced level-2 and level-3 activities. The IT team should be expanding beyond incidents to begin leveraging the AI and machine learning technologies to assist with things like analytics and decision support. The goal is to eventually roll out intelligent automation to as many routine and complex processes as possible.

Spread the word.

With a strong foundation of capabilities and experience, IT leaders can begin to position themselves as subject matter experts for the rest of the organization. This process involves continued outreach, such as connecting with other leaders across the enterprise to advise them of the specific benefits IPA can have for them. This outreach also provides the opportunity to identify additional areas where automation might be beneficial.

Explore the advanced elements of intelligent automation.

While the majority of organizations have thus far only focused primarily on simple process automation, the future belongs to those with an eye toward artificial intelligence and cognitive learning. These solutions are already making an impact on companies with forward-thinking leaders. The best way to break into this arena is to start working on small AI initiatives. From there, just like basic automation, you can continue to build, expand and grow.

Intelligent automation is maturing rapidly and quickly becoming a core component of the IT landscape. IT professionals who recognize the importance and understand how to develop their automation capabilities have the potential to become respected leaders in the process – a title that will serve them well throughout their careers.

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Have you fallen for these AI myths?

artificial intelligence AI mythsArtificial intelligence has been around for decades, though it just recently became a hot topic in the business world. During this time, many individuals have confused AI with automation, sometimes going as far as using the two terms interchangeably. The reality is, while the general concept may be similar, the two are distinctly different. Furthermore, this confusion has led to a number of other myths and misconceptions. We’d like to clarify a few things, beginning with the difference between AI and automation.

Intelligent automation involves programming technology to perform routine, manual tasks based on a prescribed set of instructions. Artificial intelligence takes this concept several steps further by using intelligent machines which are capable of displaying human behavior, thought and decision processes. Where automation is essentially set in stone (unless manually modified), an AI machine increases its own intelligence and can adapt its actions automatically, based on information it receives.

From a business perspective, artificial intelligence has the power to help organizations make more informed decisions. It can extract valuable information from mountains of data, analyze and organize it in a logical manner and essentially close the gap between insight and action. Given its complexity, however, AI is still often viewed in a negative light. To change this, we’d like to dispel three of the most common misconceptions as follows.

Artificial intelligence is a distant dream.

Many people believe that AI is a technology that won’t be readily available and practically applied until many years into the future. The truth is, widespread adoption of AI, both in our professional and personal lives, is much closer to becoming a reality than you may think. In fact, given that so many organizations across all industries and around the world are already employing automation to some degree, the idea that AI could be worked into the mix isn’t all that far-fetched.

Artificial intelligence isn’t really going to make that much of an impact.

The idea that AI is somehow inapplicable in the business world stems largely from the technologies complexity. People tend to discount things they have difficulty understanding. The reality is that AI is not only practical for business use, but it’s incredibly beneficial. The machine learning component of AI means that computers will have the ability to learn without the need for programming. It also has the capability of mining and analyzing big data to extract valuable insights which can then be put into action to achieve better results. These are things every organization can benefit from.

Artificial intelligence is going to eliminate the need for human workers.

While it’s certainly true that AI will make human workers redundant to some degree (think routine, repetitive tasks like reporting and data entry), this technology will not fully replace humans. This is particularly true in certain fields that require high-touch interactions, like HR, health care and consulting.

Likewise, while intelligent automation will streamline and optimize operations for many organizations, it cannot and will not replace the need for the development and nurturing of customer relationships. AI can, however, leverage data to provide human workers with the insight they need to deliver better, more personalized service.

And because implementing and managing new technology will always require some degree of human input, new roles and responsibilities will naturally evolve, which means that for many, AI will present great opportunities.

Like it or not, AI isn’t going anywhere. In fact, according to IDC research, worldwide spending on artificial intelligence is expected to reach $19.1 billion this year – an increase of more than 54% over last year. By addressing and overcoming the biggest misconceptions about AI, companies can harness the power of intelligent automation to streamline operations and provide competitive advantage.

Want to see AI in action? Click here to request a demo.

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Adopting Intelligent Automation: Managing Resistance to Change

Intelligent automation offers a variety of benefits to organizations, including improved efficiency, enhanced productivity, greater accuracy and output and an overall cost savings. For companies that have yet to employ this technology, however, the biggest hurdle to overcome in doing so is often resistance from employees. For some, this contention comes from fear of becoming obsolete, while others simply don’t like change. Whatever the reason, having the right strategy in place can help make adopting automation a smooth, painless and positive experience for everyone.

Change Management is About People

On the surface, managing change while implementing a technological advancement such as intelligent automation may seem to be all about the systems and processes being automated. In reality, however, change management is about understanding the fears, needs and desires of your company’s most valuable asset: your people. By addressing the human side of change, you can overcome the roadblocks and obstacles in your way and effectively change the outlook of even the strongest opposition.

Generally speaking, people tend to fall into 3 distinct
categories when it comes to adopting something new:

  • Those who vehemently oppose the proposed change
  • Those who are tentative about change
  • Those who are change champions

When planning your intelligent automation project, your strategy should incorporate the appropriate actions to address those individuals who fall into the first two categories. The ultimate goal is to change how your employees view the new technology being rolled out so that the process becomes a positive initiative that is driven forward by support rather than bogged down by resistance. That said, here are some proven best practices for effectively managing change in the workplace.

Conduct a readiness assessment. This can be done a number of ways, from holding focus groups to conducting a survey amongst all users. The purpose of a needs assessment is to identify the risks, benefits and potential obstacles that you may encounter when rolling out your intelligent automation initiative. It can also be helpful in determining areas of greatest resistance as well as the reasons behind the contention. Remember the old adage, you can’t fix what you don’t know is broken.

Sell the benefits. People aren’t going to jump on your intelligent automation bandwagon unless and until you’ve convinced them that it’s worth their while. They want to know what’s in it for them. Address this by identifying, documenting, communicating and reiterating the specific benefits that adopting automation will have for each individual and team.

Make communication a priority. One of the biggest reasons people resist change is because they don’t understand what is being done or why it’s happening. This lack of knowledge naturally breeds fear, which can derail your intelligent automation initiative. To avoid this, keep the lines of communication open and make sure everyone knows not just what the big picture is, but also their important role in contributing to that big picture goal.

Lead by example. Leadership at every level and in every department should be on-board with adoption of intelligent automation. Excitement and positivity can be very powerful tools in effecting change across an organization. Make sure you have complete buy-in from all executives prior to launch and that they understand the importance of solidarity across the board.

Identify and leverage change champions. These are the individuals who are most excited about the adoption of intelligent automation and the many benefits it will provide. By identifying these key employees, you can begin to leverage them to influence their peers who may be feeling a bit less enthusiastic about the proposed change. These individuals can help bridge the gap between front-line employees and management and become a voice for those directly impacted by change.

Intelligent automation can dramatically improve your organization’s overall performance, but rolling out such an initiative can rarely be achieved without some type of resistance. By taking a proactive approach and developing and implementing an effective change management strategy, the experience will be much more positive for everyone involved.

Nervous about how your intelligent automation project will be received by your employees? Ayehu is designed for fast and seamless implementation, so you can focus your efforts on what’s most important: investing in the happiness of your employees. Experience it for yourself by clicking here.

 

 

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