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7 Steps for Getting Started with AIOps

Today’s IT teams are dealing with a growing mountain of data. What’s more, they’re finding themselves having to use a multitude of tools in order to monitor and manage that data. In situations of technical outages, this can make it incredibly difficult and time-intensive to identify and resolve underlying issues. Anyone in business knows that even just a tiny amount of down-time can have a serious and costly impact on the bottom line. And it’s the IT team that bears the brunt of the burden.

As Padraig Byrne, Senior Director Analyst at Gartner put it:

“IT operations is challenged by the rapid growth in data volumes generated by IT infrastructure and applications that must be captured, analyzed and acted on. Coupled with the reality that IT operations teams often work in disconnected silos, this makes it challenging to ensure that the most urgent incident at any given time is being addressed.”

Take, for example, the two largest supermarket chains in Australia. Last year, both experienced severe technical issues which forced them to shut down several stores while they worked on fixing the problem. Not only did those companies lose revenue during the shutdown, but they also suffered a serious blow to their reputation. In other words, customers were not happy.

To better and more quickly identify, resolve and prevent outages and other problems, organizations are turning to artificial intelligence for IT operations (AIOps) – the long-term impact of which Gartner’s Byrne predicts will be nothing short of “transformative.”

What is AIOps

In simplest of terms, AIOps combines data science and machine learning functionality to enhance and/or replace the majority of IT operations functions. This includes performance and availability monitoring, event analysis and correlation, ITSM and automation. To put it even more simply, AIOps platforms gather and analyze all of the data produced by IT to extract what’s of value and present meaningful insights.

And AIOps is quickly gaining ground. Gartner predicts that by 2023, the exclusive use of AIOps to monitor infrastructure and applications will reach 30% – up from just 5% in 2018.

“IT leaders are enthusiastic about the promise of applying AI to IT operations, but as with moving a large object, it will be necessary to overcome inertia to build velocity,” comments Byrne. “The good news is that AI capabilities are advancing, and more real solutions are becoming available every day.”

How to Get Started with AIOps

Step 1: Don’t put it on the back burner.

If you really want to reap the benefits of AI for your IT operations, the time to jump on the AIOps bandwagon is now. Don’t make this an afterthought or push it out as some far-off future initiative. Even if the actual deployment isn’t imminent, start preparing yourself and others within your organization by becoming familiar with artificial intelligence and machine learning capabilities today. This way, in the event that priorities shift and you need to implement sooner, you’ll already be a few steps ahead of the game.

Step 2: Be careful when choosing your initial test case.

The concept of AIOps at scale may seem overwhelming, but keep in mind that truly transformative initiatives almost always start small. Focus first on capturing knowledge, testing frequently and iterating as needed. You don’t need to be an expert right out of the gate, and not every project you spearhead will be a resounding success. Just be mindful of what you’re starting with and work your way up from there.

Step 3: Work on developing and demonstrating your proficiency.

If you are leading the AIOps charge in your organization, you’ll inevitably be the go-to subject matter expert, at least initially. It will be up to you to communicate and convey the value of the technology to your colleagues and others in leadership. Wear your role with pride and start assembling a team of others who can champion the cause alongside you. Start by identifying gaps that exist in skills and experience, and then create a plan to address those gaps together.

Step 4: Don’t be afraid to experiment.

There are already many AIOps platforms on the market that are incredibly complex and subsequently cost-prohibitive. As with any tech product or solution, it’s wise do experiment and test the waters. Keep in mind that more features doesn’t necessarily equate to a better product. Your organization may not need all those bells and whistles. If possible, take advantage of product demos and free trials. This will enable you to evaluate AIOps uses and applications specific to your business needs without having to invest too heavily or commit to one particular solution.  

Step 5: Expand your vision beyond the IT department.

Data management is a massive component of AIOps. Take a step back and examine your organization. Chances are very high that your existing teams are already skilled in this area and that there are data and analytics tools already present within your organization. Resist the urge to reinvent the wheel and be willing to expand your vision to look beyond the IT department. It could save you tremendous time, effort and money.

Step 6: Standardize whenever possible and modernize wherever it makes sense.

You can prepare your existing infrastructure so that it is capable of supporting an AIOps implementation in the future by developing a consistent automation architecture, immutable infrastructure patterns and infrastructure as code (IaC).

Step 7: Consider build-vs-buy.

Understand that there are a number of variables involved in making a shift to AIOps. Likewise, the platforms available on the market today will continue to evolve, as will the infrastructure and applications for which you are responsible currently. Be mindful of this as you weigh whether to purchase a solution or build one of your own. Ideally, the best answer will likely be a combination of the two, so be prepared to figure out which approach best applies where and by how much.

Over the past few years, AIOps has developed from an emerging category to an IT necessity. Successful companies are beginning to leverage AIOps to automate and improve IT operations by applying machine learning to their data. Furthermore, forward-thinking organizations will use AIOps to draw valuable insights from their IT data that will help drive strategic business decisions.

If AIOps is on your to-do list (and it certainly should be), the steps outlined above should help you to, at the very least, lay the groundwork so that when the time comes to implement, the process will go faster and much more smoothly.

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3 Ways AI is Revolutionizing ITOps

It’s hard to imagine that while just a short time ago, people were asking what AI was all about and whether it was something worth investing in, yet pretty soon we’ll be asking how we ever lived without it. Artificial intelligence and machine learning have radically improved the lives of many, in particular, IT managers, enabling them to optimize their precious time and add legitimate value to their organizations. Here are three specific ways AI is redefining the role of ITOps.

Reduction/Elimination of Time-Consuming Tasks

Each and every day, IT managers are burdened with tasks. Some of those tasks are complex, tedious and mission-critical. Others are menial, mundane and time-consuming – administrative tasks, such as scheduling, setting deadlines and alerts, establishing priorities, directing daily operations, coordinating project activity, managing and analyzing workflow…the list goes on (and on, and on).

Here’s where AI is already making a remarkable impact on the lives of ITOps managers. By shifting most or all of these time-sapping administrative issues to intelligent automation, these leaders are freed up to allocate their skills and expertise to what’s most important. AI is particularly beneficial in terms of managing any process that is repeatable, such as preparing reports (and we all know how much IT managers adore reporting). Many organizations worldwide are already taking advantage of AI’s quantitative data analysis capability to generate analytical reports.

Increased Knowledge/Skill/Judgment Work

Only an IT manager would understand how a so-called promotion can actually be more of a headache and disappointment. Think about it. You’re awesome at what you do – ITOps work – so you get moved up the ladder, into a role that is filled with endless administrative tasks (as mentioned above). Feels more like a demotion than anything else. Many IT managers in this position would much rather be focusing their time, energy and expertise on things like:

  • Developing standards and best practices
  • Overseeing complex workflows
  • Identifying duplication and waste, quantifying outcomes and providing analysis
  • Coordinating and managing operational budgets and initiatives
  • Analyzing data
  • Developing departmental and interdepartmental goals
  • Evaluating proposals to determine requirements and feasibility
  • Consulting with users, stakeholders, technicians and vendors to determine needs and requirements

Artificial intelligence has gifted IT managers with the ability to perform more of the knowledge, skill and judgment work that they love, not only because it frees up time, but because the technology is inherently designed to support enhanced decision-making within ITOps (and beyond). That’s not to imply that human expertise and insight will be replaced by AI. To the contrary, cognitive skills and critical thinking will become even more prevalent because IT managers will have more time.

More Room for Creativity

The flood of demanding day-to-day tasks that ITOps manager face leaves little to no room for the creative thinking that is necessary to drive innovation. Some of the areas where these leaders can add value include brainstorming to improve future IT initiatives, strategizing on organizational goals and objectives, keeping up with tech developments, acting as champion for the IT department, just to name a few.

Integration of artificial intelligence is facilitating more creative thinking by enabling better experimentation and collaboration. When IT managers are able to spend more time strategizing, the human element of creativity will flourish for the betterment of ITOps and the organization as a whole. What’s more, IT managers will be able to take on more advisory roles thanks to AI’s presence. The ability to hone social skills will continue to open up new and exciting opportunities.

Conclusion

ITOps managers across the globe are already experiencing drastic changes with the growing adoption of AI technology. The relief from administrative tasks alone have made it well worth the investment, with the promise of even more widespread benefits that will change the scope of everyday life for the better.  

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Pros and Cons of IT Chatbots

When IT chatbots were first introduced, admittedly, they were less than impressive. They were slow, clunky and in many cases, it was painfully obvious that a robot was on the other end. Advances in artificial intelligence technology, however, have addressed these concerns and the virtual agents of today are becoming more human-like by the minute. And their popularity is growing, with Gartner predicting that by next year, 50% of medium-to-large enterprises will be using chatbots.

Should you be one of them? Let’s take a look at a few of the ups and downs of using virtual support.

Pros of IT Chatbots

Frees Up Humans Resources – The first and most obvious benefit to deploying IT chatbots for the helpdesk is that it shifts a significant portion of the workload from human to machine. This frees up human agents to be able to focus their high-level skills and cognitive talents on more complex and important business initiatives. This is a much more optimal allocation of resources.

Enables 24/7 Support – Most organizations can’t afford to pay for round-the-clock IT support, and for those that do have the budget, justifying it can be a challenge. IT chatbots are available 24/7, which means if a problem arises at 2am, there’s a good chance it can be automatically addressed and resolved without human intervention. A higher level of support without having to pay live agents? Yes, please.

Advanced Interaction – With the right software solution, IT chatbots can be fully customized. Furthermore, thanks to advanced AI technologies like machine learning and natural language processing, virtual agents can be so “intelligent” that the end-user doesn’t even realize they’re interacting with a robot and not a fellow human.

Cons of IT Chatbots

Volume – The overarching goal of any IT chatbot implementation is to automate routine, manual and recurring tasks. Logically, if the volume of recurring activities for your IT team is low, the benefits of introducing virtual agents may not outweigh the cost and effort it takes to implement.

Time/Resources – While it’s true that chatbots free up existing IT staff, the technology isn’t something you simply plug and play. It requires oversight and maintenance by skilled human workers who can make sure the software has all the information it needs, can add new services, applications and processes for the end-user as needed and that the bots are properly tested.

Fear/Resistance – Lastly, as with most automation technology, chatbots often elicit feelings of fear and resistance from human workers who may be concerned that they are being replaced. Additionally, if the technology is not up-to-par, the end user may push back against the idea of working with virtual agents vs. human help desk support.

These issues can be overcome, provided the right people, technologies and policies are in place. In fact, if you take your time to fine-tune your chatbot platform, it can easily become an effective and realistic channel for supporting end-users, making it well worth the time and investment.

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7 Key Business Benefits of Intelligent Automation

Intelligent automation is being adopted and implemented in businesses of every industry. Still, there are some decision makers who are on the fence about whether it’s worth the investment. If you are among those who aren’t 100% certain, let’s take a look at a few of the quantifiable benefits AI-powered automation can provide to your organization.

Cost Savings

One of the biggest advantages of intelligent automation is the immediate and significant reduction in expenditure it can deliver. When work is automated, not only is it completed faster, but it also can be performed round-the-clock at a much lower rate. So, you get greater output for less, which results in a better bottom line.

Quality, Accurate Work

Let’s face it. Even the most careful human can and will make an occasional mistake. Multiply those errors by the number of people you have performing routine tasks for your company, and you could be looking at a pretty costly problem. With artificial intelligence, the work is performed error-free. Better quality means higher satisfaction rates, which – again – is good for your company’s profitability.

Enhanced Cycle Time

How long does it take a human worker to perform a given task such as completing a web form? Even if it’s mere minutes, an intelligent robot could shave that time down to just a few seconds. Over time and multiplied by dozens of tasks and several staff members, this savings really begins to add up.

Employee Empowerment

Intelligent automation does not require any special technical skills. That’s why it’s an ideal application for the end-user. The ability to deploy robots to perform certain tasks without having to enlist the help of someone from IT empowers the end-user to get their jobs done more efficiently and effectively. Meanwhile, it frees up IT to focus on more important tasks and projects.

Simplicity and Flexibility

Automating tasks and workflows through Ayehu’s AI-powered automation does not require coding or script-writing. That means even complex processes can be transferred from human to machine with little effort. The faster these tasks and workflows can be automated, the sooner your organization will begin reaping the benefits. In other words, intelligent automation delivers quick returns.

Better Control

Many companies choose to outsource so-called busy work to external parties. This, of course, comes with inherent risk. Intelligent automation can provide a better solution and since the work remains in-house, the business maintains maximum possession, control and visibility.

Insights and Analytics

Learning from the past can help your business leaders make better decisions for the future. Machine learning algorithms offer the ability to gather, organize, track, analyze, report on and store valuable data. That information can then be utilized to improve on current operations, address and correct issues in a timelier manner, accurately forecast and develop best practices.

Still not convinced that intelligent automation is a beneficial solution for your business needs? Why not try it for yourself? Click here to start your free trial of Ayehu NG today.  

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Is Intelligent Automation Really Replacing Human Workers?

When intelligent automation first hit the market, some thought it was too far-fetched to ever become a reality. But as more and more organizations began recognizing the many benefits – from increased productivity and efficiency to lower costs and fewer errors – people started worrying, wondering whether this technology would spell the end of the human workforce as we knew it. Would artificial intelligence really start taking over jobs? To answer that question, those asking it must look inward.

In reality, the impact automation has on the workforce will depend largely on how humans themselves respond. When faced with the rising adoption of AI, workers will likely take one of two paths. The first group will continue to focus on the type of work they’ve always done, but do so more efficiently thanks to the assistance of machine learning. The second will take this as a golden opportunity to pursue their ambitions, further their education to broaden their skill sets, put their creativity and innovation to work and move on to more value-added, meaningful work. In either case, the organization will benefit, as will most of the employees.

In particular, roles that have a primary focus on people, such as customer support and HR, have the potential to benefit greatly from intelligent automation. Instead of being bogged down by repetitive, menial tasks that can easily (and more quickly) be handled by software, agents will be freed up to tackle more complex issues requiring a human touch. Furthermore, the improved allocation of resources afforded by AI will enable agents to prevent issues from occurring in the first place. This can dramatically improve both customer and employee satisfaction rating.

This concept can also be applied to the IT help desk. Rather than waiting until system problems arise and scrambling to fix them in a timely and effective manner, help desk agents can use the extra time automation provides them with to monitor and proactively address technical issues before they occur. Imagine how impressed the CEO will be when he gets a call from IT letting him know his hard drive was about to fail, but it’s been taken care of.

In both of these scenarios, the human worker is enhancing their interactions with their colleagues and/or customers. And since intelligent automation is there to take on the routine, manual tasks, the human agents themselves are also able to improve.

The reality is, very few organizations are focusing on using AI to eliminate jobs. Instead, they are focused on automating tasks, which in turn will improve productivity, streamline how work is completed, eliminate errors and cut costs. In other words, companies implementing automation are not doing so to replace human workers, but rather to augment and make their lives easier. As a result, everyone benefits – from employees and management to clientele and ultimately the organization’s bottom line.

Still not completely sold on the idea of intelligent automation and the value this technology can bring to your business? Don’t take our word for it. Try it for yourself. Click here to download a free 30 day trial of Ayehu. You have nothing to lose!

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3 Business Areas that are Ideal for Machine Learning

At the current rate, AI systems worldwide are on pace to hit nearly $50 billion in revenues by the year 2020. The proof is in the pudding. And if you’re not yet leveraging the power of machine learning, you can bet your competitors are. The good news is, you don’t need a massive budget or a team of experienced data scientists to start putting machine learning to use in your business. In fact, to follow are three practical areas where almost any organization can get started with ML technologies.

Internal/External Support

If you have an IT help desk for employees or a support team dedicated to customer inquiries, you have a great opportunity to leverage machine learning technology. Chatbots can be trained to handle everything from the most basic FAQs to complex issues, working in tandem with human agents.

Not only will a chatbot strategy free up your support staff to focus on more important business initiatives, but it’ll also improve service levels, so it’s a win-win. (Not sure where to start? Here’s a step-by-step guide to implementing bots along with some tips for what not to do.)

Cybersecurity

According to research by Ponemon, the average cost of a single ransomware attack is $5 million. And that’s just one strategy hackers use. If you think cybersecurity is not a big deal, think again. The problem is, cyber criminals are becoming savvier and using more sophisticated methods by the day. Staffing enough people to handle the onslaught isn’t just challenging. It’s next to impossible.

The good news is, machine learning can be used to augment your IT security team, providing an added layer of protection against potential breaches. Intelligent automation can work around the clock, constantly monitoring and analyzing mountains of data and identifying/addressing anomalies before they have a chance to wreak havoc.

Human Resources

While there are certainly areas of the human resources function for which a human touch is still needed, such as discussing sensitive matters with employees, the reality is, the vast majority of today’s HR processes and workflows can easily be automated.

For instance, machine learning algorithms can be used to weed through job applicants, saving recruiters time and aggravation, while intelligent automation can handle new employee onboarding far faster and more efficiently than a human agent could. To get you started, check out these 5 tips for optimizing HR with automation.

Of course, none of these things will be possible without the right technology. Thankfully, you don’t have to be an AI guru to leverage machine learning, nor do you have to hire a team of experts. In fact, you don’t even have to know how to code. Experience the power of plug-and-play intelligent automation by requesting an interactive demo of Ayehu or jump right in with your free 30-day trial today!

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5 Surefire Ways to Derail Your Machine Learning Project

The process of implementing something new typically involves making mistakes, heading in the wrong direction and then figuring out a way to right those wrongs and avoid those risks in the future. Adopting machine learning is no exception. If you aren’t careful, the mistakes you make can become encoded, at least for the time being, into your business processes. As a result, these errors will occur at scale and will be difficult to control.

On the other hand, when you proactively detect errors and take the steps to address and correct them right away, you’ll have much more success with the technology. To follow are five common pitfalls that can wreak havoc on your machine learning project so you’ll know what to watch for.

Lack of clear understanding.

Simply put, you cannot adequately solve a problem that you don’t fully understand. The same can be said for machine learning initiatives. If you don’t completely understand what problem you are actually trying to solve, the risk of errors goes up exponentially.

To avoid this, begin with a hypothesis statement. Ask what the problem is that you are trying to resolve and which models you plan on using to address that issue. This is key, because if it’s not done correctly from the start, things can go wrong very quickly.

Poor data quality.

The old adage, “garbage in, garbage out” can easily be applied to machine learning projects. If the quality of the data you are supplying isn’t up to par, the outcome will inevitably suffer. In fact, poor data quality is one of the top concerns of data managers, as it can impact analytics and ultimately influence business decisions in the wrong direction.

The result of these poor decisions can negative affect performance and make it difficult to garner support for future initiatives. Exploratory data analysis (EDA) can help you proactively identify data quality issues so you can prevent problems before they occur.

No specific purpose.

Another common contributor to machine learning failure is implementation without a clear purpose. In order for machine learning to produce ROI, it must be applied properly – not simply because it’s the cool thing to do. In fact, using machine learning when it’s not the best solution to a problem and/or not completely understanding the use case can ultimately cause more harm than good.

In addition to addressing the wrong problem, doing so can involve wasted time and resources, both of which come at a cost. To avoid this, identify the precise problem and desired outcome to determine whether machine learning is the appropriate solution. 

Insufficient resources.

It’s easy to underestimate the amount of resources required to do machine learning right, in particular as it relates to infrastructure. Without adequate processing power, successfully implementing machine learning solutions in a timely manner can be a difficult, if not impossible feat. And without the resources in place to allow for its deployment and use, what’s the point?

To address the expense and complexity of deploying a scalable infrastructure, leveraging a cloud service that can be provisioned on-demand may be the better option. Those wishing to keep things in-house should look for a lightweight, plug-and-play solution that doesn’t require coding and can be deployed across on-premises and private cloud platforms.

Poor planning and lack of governance.

It’s not unusual for a machine learning project to start off with tremendous enthusiasm only to lose momentum and ultimately end up grinding to a halt. When this happens, poor planning and lack of governance is most often to blame. For those projects that don’t cease, a lack of guidelines and limits can result in an exorbitant expenditure of resources without the beneficial end results. 

To keep things moving in the right direction, machine learning initiatives must be continuously monitored. In the event that progress begins to wane, it can be wise to take a break and reevaluate the effort. Keeping people engaged in the process is the key.

Machine learning can be a tremendous asset to an organization, but only if it’s planned, implemented and managed properly. By avoiding the five common pitfalls listed above, you can place your company in a much better position and improve your chances of long-term, sustainable success.

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5 Ways Machine Learning is Transforming the Business World

Today’s forward-thinking organizations are leveraging the power of artificial intelligence to automate the decision making process. In fact, corporate investment in AI is predicted to reach $100 billion by the year 2025. As a result of this rapid digital transformation, many changes are underway in the workplace. In particular, there are a number of ways that machine learning is already making an impact for companies in every industry. Here are a few to consider.

Personalizing the customer experience.

One of the most exciting benefits machine learning can have for businesses is the fact that it can help improve the customer experience while also lowering costs. Through things like deep data mining, natural language processing and continuous learning algorithms, customers can receive highly personalized support with little to no human intervention. And people are warming to the idea. In fact, 44% of US consumers say they actually prefer chatbots to human agents.

Improving loyalty and retention.

With machine learning, companies can do a deep dive into customer behavior to identify those who are at a higher risk of churning. This enables organizations to develop and implement next steps designed to target and retain those high-risk customers. The more proactive a company is in this area, the more profitable it will be over time.

Enhancing the hiring process.

When asked about the most difficult part of their job, corporate recruiters and hiring managers almost unanimously list the task of shortlisting qualified candidates for job openings. With dozens and sometimes even hundreds of applicants, sifting through and narrowing down the options can be a monumental task. Machine learning is fundamentally changing the way this process is handled by letting software do the dirty work, quickly identifying and shortlisting those candidates that are the best fit.

Detecting fraud.

Did you know that the average organization loses up to 5% of their total revenue each year due to fraud? Machine learning algorithms can be used to track data and apply pattern recognition to identify anomalies. This can help risk management detect fraudulent transactions in real-time so they can be prevented. This type of “algorithmic security” can also be applied to cybersecurity, leveraging AI to quickly and accurately pinpoint threats so they can be addressed before they are able to do damage.

Streamlining IT operations.

Another way AI and machine learning are revolutionizing how organizations operate is through intelligent automation. Powered by machine learning algorithms, agentless automation and orchestration platforms become force multipliers, driving efficiency and helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure.

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What will 2019 have in store for AI and machine learning?

There’s been plenty of hype about machine learning and artificial intelligence and that buzz isn’t expected to slow down anytime soon.As we prepare for another new year, it’s always a good idea to consider what’s in store for technology and all indications point to 2019 being a major year for AI and ML.

What might we expect to unfold over the coming months? Well,for starters, next year is poised to be one in which those who have been teetering on the fence about adopting machine learning are likely to finally take the plunge. Let’s take a closer look at a few other trends to watch for in 2019.

Cross-Industry Infiltration of Machine Learning

To put it plainly, there simply isn’t a single industry that would not benefit in some way from machine learning technology. As more decision-makers begin to recognize this, more widespread adoption will occur alongside the ideation of newer and more innovative ways to use ML.

A great example of this is the U.S. Army. Over the next year, they will be rolling out the use of machine learning sensors to predict when combat vehicles are in need of repair. The health care industry is another field that is finding new uses for AI. For instance, algorithms now exist that can predict – with 95% accuracy – the probability of a patient’s death. Physicians can use this data to literally save lives.

It’s safe to say that as we ramp up adoption of AI and ML,forward-thinking companies will continue to discover new ways to leverage these technologies to read, interpret and apply data for greater success.

Increasing Use of Chatbots

Most of us utilize AI assistants on a daily basis, whether it’s asking Alexa to play our favorite song list or checking with Siri to see how traffic will be for the commute home. These basic interactions are really just the tip of the iceberg.

In 2019, development of chatbots will snowball, making AI assistants an even bigger part of our everyday lives. Not only will they be in our pockets and in our homes, but chatbot technology will continue to make its way into the business world.

For instance, in the IT service management realm, chatbots will be used increasingly to enable end-users to self-remediate while simultaneously freeing up human talent to be focused on more complex projects and business initiatives.

Deepening Interactions between Humans and Machines

The concept of AI being a robot merely capable of performing repetitive, mundane tasks has become antiquated. To the contrary, more and more organizations are recognizing artificial intelligence as an integral part of their workforce, working alongside their human employees and playing a pivotal role in their success. This relationship will only continue to evolve as we push onward into2019 and beyond.

As AI technology advances further, we can expect features and functionality that mimics human behavior in much greater detail. Imagine a chatbot that not only recognizes what a human is saying, but the tone and nuances behind those words. The possibilities are virtually limitless.

And as AI continues to become ingratiated into the fiber of how organizations operate, the fear and uncertainty that clouded human workers in the past will begin to dissipate. In its place will be a newfound respect and an optimism for the new opportunities these innovative technologies will create.

Without question, 2019 will be a critical year for both machine learning as well as AI. The three predictions above may very well just be scraping the surface of what’s truly in store. One thing’s for certain:these technologies are here to stay and they’re changing our world in ways beyond what we ever thought possible.

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Using Intelligent Automation to Cut Costs and Skyrocket Service

Using Intelligent Automation to Cut Costs and Skyrocket ServiceFor several decades now, IT automation has been developed,refined and continuously improved to help streamline operations and take on the manual, repetitive tasks that nobody wants to complete. It’s becoming more widely accepted that most of these work duties can be handled by software. Beyond these simple, basic tasks, however, enterprises across the globe are now leveraging artificial intelligence to do even more. It’s called intelligent automation and it’s helping organizations of every shape, size and industry cut costs, improve service and remain a step ahead of the competition.

Intelligent automation is being leveraged as a solution to many common issues large businesses face, particularly those in the financial sector. One such area where intelligent automation is proving to be significantly beneficial is in meeting compliance requirements. Big banks,telecom companies, insurance firms and other businesses that deal with a high number of transactions, especially those that are sensitive in nature, are under increasing pressures to remain compliant. Relying on human workers to achieve this is not only expensive, but also more prone to costly error.

Another critical area where intelligent automation is having a positive impact is in the very volume of data itself. These days,there is so much information flowing into an organizations, from inquiries and transactions to authentications and a whole host of other business processes that businesses are finding it challenging to keep up. With smart technology,much of this data can be gathered, analyzed, sorted and prioritized without the need for human intervention, saving the organization time, money and a ton of aggravation.

Think Smarter, Not Bigger

In reality, even larger enterprises rarely have the luxury of increasing staff levels to the degree that is required to keep up with the rising demands being placed on them. Not only does this equate to increased costs, but it also opens the door to increased risk as well. C-suite executives, board members and other key decision makers are often too focused on other critical business initiatives to worry about growing the IT department.

The good news is, today’s intelligent automation software provides the opportunity to develop into a more efficient, highly productive,error-free environment without the need to beef up personnel. It’s providing organizations a way to work smarter instead of bigger while also lowering risks and keeping costs at a minimum. Unlike the rudimentary technology of just a few decades ago, today’s automation solutions are fully capable of analyzing,learning and responding to a mountain of data in real-time.

In reality, with the right strategy and intelligent automation technology, a business can successfully transition up to 90% of all IT functions from human to machine. This includes everything from repetitive, labor-intensive activities to complex workflows. IT automation is also playing a key role in helping companies establish and maintain a much more effective defense against cyber-attacks, providing the added protection of round-the-clock detection, analysis and response.

How Does Intelligent Automation Work?

Once an intelligent automation solution is adopted and implemented, the IT department determines which tasks are to be automated. Essentially, the software is “taught” what to do, when to do it and how each function should be carried out. Beyond the basics, like robotic process automation, intelligent automation is designed to deal with situational data and use that information to perform appropriate contextual functions. The software essentially uses relevant knowledge to decide on how to proceed in much the same way humans do.

Furthermore, intelligent automation also creates complete documentation of the entire decision-making and execution process, providing the ability for IT personnel to view, track, analyze and evaluate the automated process, both during as well as after the fact. This documentation contains all of the necessary details, including the relevant background and contextual information that was used in the decision-making process. Best of all, this information is stored and can be easily accessed in one centralized location.

The Benefits are Astounding

By adopting intelligent automation, organizations are able to achieve significant cost savings while also improving overall operation and service levels at the same time. When the majority of IT service management functions are shifted from human to machine, skilled personnel can focus on more important business initiatives. This promotes an IT environment that is much more efficient, agile, flexible and compliant, all of which can be translated to improved quality and satisfaction. The more complex the IT system, the greater the benefit automation can provide.

Is your organization taking advantage of these and the many other benefits that intelligent automation can offer? Get started today by downloading your free 30 day trial.

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