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6 Steps for Bringing Your AI Project from Concept to Reality

There is often a disconnect between proof of concept testing of AI, which typically occurs in a controlled environment, and applications that occur in the real world. External forces, like variable conditions, integrations with existing workflows and actual time requirements commonly lead to a breakdown of these proof of concept solutions. In fact, one recent study by the International Institute for Analytics revealed that fewer than 10% of artificial intelligence pilot projects actually reach full-scale production. To avoid this same disappointment with your own AI projects, here are a few expert tips.

Have a plan for data collection.

In order for artificial intelligence and machine learning to deliver measurable value, it must have access to quality, relevant data. Without this, the project will inevitably fail. An important point to keep in mind, also, is that the more diverse and closer to actual real-world conditions your dataset is, the greater your chances of success. Dedicate an adequate amount of time and resources to this step, as it will give your project a solid foundation.

Anticipate risks and dependencies in advance.

In order to bring your AI project to life, you must thoroughly and as accurately as possible identify the various conditions the system will encounter. It’s unlikely you’ll be able to solve for every one of them, however, there will be at least some that you can prepare to overcome in advance. Make a list of all the risks and potential issues you can foresee and then rank those risks in order of priority, focusing on the most impactful first. The earlier you can remove a potential roadblock, the smoother your project will go.

Determine your milestones and metrics for success.

One of the biggest reasons AI projects fail is because they don’t effectively solve the target problems. This can stem from misunderstandings and miscommunications, and can result in a tremendous waste of time and money. To avoid this, make sure that there is a clear and accurate definition of exactly what the goals are. Set specific milestones and metrics that you will use to measure progress. Include relevant stakeholders in this step to ensure that everyone is on the same page and nothing is ambiguous before moving forward.

Don’t try to reinvent the wheel.

Avoid getting caught up in the trap of trying to solve problems that have already been solved. While the goal is certainly to adopt AI at an organization-wide level, that doesn’t mean every task, process or workflow is a good candidate for automation. Start instead with low-hanging fruit that can produce quick and measurable wins and focus on a solution that will allow you to use what’s already available to create a harmonious, interconnected infrastructure. Remove silos wherever possible.

Emphasize value over accuracy.

While maximum accuracy is always the goal, 100% is rarely achievable. It can be helpful to go into the project with the right focus: on delivering as much business value as possible, as opposed to attempting to achieve perfection. Understand that you will be able to tweak and make improvements along the way, so it’s ok to go from test environment to live environment, even if the solution isn’t one hundred percent perfect. If you’re not realistic in your goals and expectations, you’ll never get off the ground.

Don’t leave humans out of the loop.

Despite the incredible advancements in AI technology capabilities, some things are still better left to humans. Avoid being lulled into the idea that your workforce is suddenly expendable just because you’ve got some robots waiting in the wings. To the contrary, successful AI projects integrate a balance of human and digital workers. Besides, who better to identify areas of opportunity where intelligent automation could add value than the people who are working in the trenches day in and day out.

The last point we will leave you with is that developing and implementing an AI solution is a process. If you want to achieve long-term, sustainable success, you need to think of it more as a marathon than a sprint.

Your journey to a self-driving enterprise begins here. Claim your free 30-day trial of Ayehu today.

The Secret to Unlocking Maximum Return on Efficiency and Cost-Savings

The Secret to Unlocking Maximum Return on Efficiency and Cost-Savings

Artificial intelligence technologies have already begun to change the way we live and work. Yet, still far too many businesses remain caught up in the trap of wasting tremendous amounts of valuable time on routine, repetitive tasks. Automating as many of these mundane tasks and workflows can not only have a massively positive impact on efficiency and productivity, but it can also dramatically improve morale. But it’s not just about adopting these technologies on a case-by-case basis that will reap the greatest rewards. It’s doing so in a way that automates business processed from end-to-end. That’s the real key.   

Why End-to-End?

In order to optimize business operations and gain competitive advantage, IT leaders must focus on integrating intelligent automation into processes at every level. Without this holistic approach, you will inevitably end up with automation silos, which can actually impede progress rather than facilitate it.

Using purchasing as an example, the goal should be to embed automation from supplier selection through invoice payment. Ultimately, you want intelligent technology to become a seamless part of normal daily work, from the start of every task or workflow through completion and beyond. Keep in mind that this may (and very likely will) involve incorporating automation through multiple teams and departments.

One of the biggest problems with dedicated (isolated) automation projects is that the organization misses out on valuable insights along the journey. For instance, automating just a piece of the customer experience process could result in a failure to effectively capture feedback data. Without this information, business leaders cannot fully understand behaviors, buying decisions and reasons for churn. As a result, they miss out on the opportunity to hone and improve their product or service.

The Self-Driving Organization

Many similarities can be drawn between intelligent process automation in the workplace and autonomous vehicles. In particular, artificial intelligence and machine learning technologies have the potential to adapt and either recommend certain actions based on data, or carry out those actions independently, without the need for human intervention. Does this mean people will suddenly stop driving? No – at least not for the foreseeable future.

Likewise, humans will still be needed to oversee the intelligent technologies that are being utilized in the workplace. (This is why we recently posted an article about the importance of reskilling the workforce.) Someone still has to define algorithms, decide what rules should be followed and determine which priorities present the most value.

That being said, there is plenty of opportunity now to start making strategic decisions and laying the foundation for a more autonomous future. A great first step is to help human workers gain a better understanding of the technology, its capabilities and the potential ways intelligent process automation can bring tremendous benefits to their daily lives. Better understanding will foster trust, which will make it much smoother sailing as more and more processes are moved to automation.

At the end of the day, in order to remain profitable in an increasingly digital world, business leaders must take a holistic approach to their automation initiatives, working together across the entire enterprise to incorporate intelligent technologies across the board. Only then will they be able to achieve the highest return on their investment.

Did you know that Ayehu NG integrates with dozens of the top software, platforms and applications to help facilitate seamless automation process across the entire infrastructure? Check out our full integration list here and then download your free trial to take Ayehu for test drive today!

Rule-Based vs. AI-Bots – What’s the Difference?

Rule-Based vs. AI-Bots – What’s the Difference?

Up until relatively recently, the only option end-users had for receiving IT support were phone calls, tickets or emails. Now, thanks to rapid iterations of artificial intelligence and machine learning technology, IT departments are able to leverage the power of intelligent bots to offer round-the-clock, automated (read: agentless) support.

But not all bots are created equal. One of the biggest differentiators is whether they are rule-based or true AI. Understanding the key differences here will help organizations make more informed decisions when adopting a virtual support agent (VSA) model.

Rule-Based Bots

Rule-based chatbots are capable of answering end-user questions based upon a predefined set of rules that they have been programmed for. This isn’t to say they’re necessarily basic. In fact, with the right programming, rule-based bots can be built to be relatively complex (at least, to some degree). And because they are built on if/then conditions, they are much easier to train than AI bots, which means they can be implemented extremely quickly. That being said, they are far more cumbersome to maintain over time, as every new piece of information must be programmed as it’s needed.

Where these chatbots fall short, however, is in their inability to understand context and learn on their own. As such, there is often a disconnect between the end-user and the bot, which can lead to frustration and delays. For more complex issues, bots can hand over the conversation to a human agent who can provide a higher level of service and support. This means that rule-based bots cannot operate completely autonomously. They must rely on human intervention whenever anything outside of their database arises.

AI-Based Bots

While the human/computer interface of rule-based vs. AI bots is relatively the same, the major difference between the two technologies is their self-learning capabilities (or lack thereof). AI bots are programmed with machine learning (ML) and natural language processing (NLP) so that they can read and comprehend context and continuously learn and improve on their own. The key to success with AI bots is access to rich, relevant data.

While there is certainly an investment of time, resources and money upfront, AI-bots are generally much more cost-effective in the long run, because they require far less ongoing maintenance than rule-based bots. They are also more resource-efficient, since they can handle highly complex support needs without requiring any human input. This enables organizations to optimize their staff numbers, either trimming down or reallocating human resource to more meaningful, revenue-generating projects. Meanwhile, end-users receive the on-demand support they need, maximizing satisfaction levels.

Which Type of Bot is Right for You?

The best way to determine whether rule-based or AI bots are the right fit for your organization is to map out your needs. Generally speaking, AI-bots offer the most “bang for your buck,” because they can do everything a rule-based bot can do, along with much more complex and valuable functionality. This is especially important for IT operations. The good news is, you can experience AI bots in action free for a full 30 days. Simply download your trial of Ayehu NG today to get started.

A Surprisingly Simple Solution to Avoid Being Crippled by Coronavirus

Global Industries Being Crippled by the Coronavirus (and a Possible Solution)

Since its initial outbreak in China, the COVID-19 (a.k.a. coronavirus) has begun rapidly proliferating across the globe. Italy is on lockdown, Iran is teetering on the brink of crisis and the United States is bracing itself for a widespread and potentially devastating national outbreak. And this pandemic situation is spreading more than just sickness and death. It’s also disseminating a pervasive sense of panic that’s enough to send the global economy into a nosedive.

The impact this outbreak is having on businesses simply cannot be understated. Some organizations are being directly affected by things like mandatory quarantines and worldwide travel bans. Others are realizing the trickle-down effect that comes with things like international trade restrictions and disruptions to the global supply chain.

The unfortunate and downright bleak reality is that this health crisis isn’t going anywhere anytime soon. In the meantime, business leaders across just about every industry are facing difficult decisions about things like production and staffing. Talks of layoffs are undoubtedly on the table, ultimately impacting the livelihood of everyday workers and, subsequently, pushing the world further toward another recession.

The good news – if there can even be “good” news at a time like this – is that there is a solution that could potentially prevent business disruption and keep organizations (even those hit hard by the epidemic) afloat, despite the dire external circumstances. That solution is intelligent automation. Here are just a few ways:

  • Workers on mandatory quarantine can continue to perform their daily duties from their home offices.
  • Organizations in high-risk areas can improve their odds of avoiding exposure and also reduce further spread of the disease by voluntarily allowing employees to work from home.
  • Companies that rely heavily on travel can utilize virtual technology to continue “business as usual,” slashing travel expenditure at the same time.
  • IT teams can leverage intelligent automation to balance the workload so they can either operate on skeleton crews or manage their normal workload remotely.
  • Advanced technologies, like machine learning, natural language processing and artificial intelligence can be employed to enable end-users (either on-site or working remotely) to self-serve a wide variety of their IT support needs, such as password resets and system restarts.

Is intelligent automation the be-all and end-all solution? Of course not. Some industries, such as travel and tourism, will undoubtedly feel the brunt of this pandemic outbreak. For most industries, however, the scenarios outlined above can help keep things operating on schedule, thereby limiting business disruption. Not only does this help organizations avert financial loss, but collectively, it could help to keep the economy more stable, preventing or at least minimizing the impact of a widespread downturn.

The best way to prepare for the coronavirus? Wash your hands. Avoid touching your face. And if you’re a business decision-maker, implement intelligent automation as soon as possible. Get started today with your free 30-day trial of Ayehu NG.

How AI is Revolutionizing the IT Support Role

Over the past several decades, the role of IT support has evolved from basic plug-and-play transactions to handling much more complex tasks and workflows. Unfortunately, the pace of technological change and demand for faster, more accurate and more seamless service has also evolved – in many cases, beyond what human agents are capable of. Furthermore, support teams are being hindered by antiquated processes and technology silos, preventing them from realizing their true value.

That’s why more and more organizations are turning to emerging capabilities, like machine learning and artificial intelligence, to help supplement and enhance the IT support role. AI tools, like intelligent chatbots and virtual support agents, have already proven highly effective in facilitating greater efficiency and superior end-user service.

IT Support’s Greatest Challenges

To truly recognize the impact AI can have, it’s important to understand just what today’s IT support agents are up against. Research has shown that L1 and L2 IT support personnel waste hundreds or even thousands of man hours each year simply due to time-consuming manual labor and inefficient infrastructures. Often times, agents find themselves having to switch between multiple systems and platforms just to accomplish a simple end-user support request.

Another major hurdle modern IT support teams face today is a lack of adequate access to data. Or, perhaps we should clarify this to lack of access to quality, usable data. Agents (and their managers) need access to insights like this in order to analyze and improve performance. Unfortunately, these insights are not always readily available in many organizations, crippling the support desk and ultimately impacting service levels.

When these issues occur, either individually or compounded, not only does the end-user become frustrated, but so do the IT support desk agents. And if they’re feeling unhappy, overworked and unfulfilled, they’re far more likely to churn, leaving organizations with the burden and cost of recruiting and training. It’s a never-ending cycle.

How AI Can Help

How AI is Revolutionizing the IT Support Role

To answer the call of these costly and frustrating challenges, organizations across the globe are turning to AI technologies. In particular, they are leveraging the power of intelligent chatbots to handle lower-level support needs. Imagine how much more valuable your skilled IT workers could be if they weren’t wasting half their day resetting passwords or restarting systems. Not only do virtual support agents resolve issues faster and improve customer satisfaction, but they free up the IT team to focus their efforts and skills on more value-added business initiatives. This is good for everyone involved.

Artificial intelligence can also assist with building out additional content resources, helping higher level agents resolve issues faster and providing invaluable insight to management to facilitate data-driven decision-making. Machine learning algorithms can automatically and continuously analyze past cases to provide real-time guidance for best next steps as well as identify and make suggestions on areas of potential improvement. It’s like having a consulting firm working on your behalf, 24/7/365, only without the hefty price tag.

When IT support agents have access to the most up-to-date tools and innovative capabilities like AI, they’re jobs will be made infinitely easier. Trained workers will be able to apply their skills to more meaningful work, end-users will receive faster and better service, while at the same time, organizations will realize improved satisfaction levels, higher productivity and efficiency, and lower costs overall. That’s what we call a win-win-win!

Want to experience this kind of breakthrough for your IT support team? It’s as easy as downloading Ayehu NG. Click here to try it free for 30 days and put the power of AI to work in your organization.

3 New Roles AI Will Create for Humans

What if we were to tell you that robots are not coming to steal your job, but instead, they’re coming to give you a promotion? Would that change your perception of artificial intelligence? Probably. Thankfully, in most cases anyway, it’s the truth. While AI will, inevitably, make some roles obsolete, it will simultaneously be creating newer and even more lucrative opportunities for humans. In fact, we’ve pinpointed at least three distinct job categories intelligent automation will open the door for. Let’s explore each of these below.

Trainers

Artificial intelligence is just that – artificial. Yes, it is capable of improving autonomously, but someone still has to be there to tell the program what to do and ensure that everything is moving along as it should be.

For example, before you can tell your virtual assistant Amazon Alexa that you want her to call your spouse, you first have to “teach” her who your spouse is and what phone number should be used. Once AI tools and platforms have the basic understanding of what’s expected of them, they can then continue to self-learn, but just like any student, they need to be taught those basics first.

Evangelists

Like it or not, artificial intelligence isn’t going anywhere. In fact, according to Gartner, 70% of organizations will assist their employees’ productivity by integrating AI in the workplace by as early as next year.

Yet, despite this looming proliferation, not everyone is quite comfortable with the concept of AI. Fear of the unknown is still a very real problem for many organizations. That’s where AI evangelists come in. These are human experts whose role, at least in part, is to explain computer behavior to others.

Having champions of intelligent automation will enable the enterprise to overcome fear and resistance, clearing the pathway to successful digital transformation.

Managers

As smart as AI is, it’s not necessarily something you can simply set and forget. To the contrary, human oversight is still very much needed to ensure that systems are working properly, securely and responsibly.

The fact is, while chatbots have the capability of learning and communicating, they lack many of the characteristics that are innate to humans. One need only look back to the Microsoft Tweetbot debacle of a few years ago to understand this.

In March of 2016, the computer mega-giant introduced its interactive chatbot named Tay to the world of Twitter, with the goal of engaging 18-24 year olds with the concept of machine learning. The chatbot was taught to interact with other users like a real human through reading and processing actual tweets.

Unfortunately, within hours, savvy Twitter users had transformed the formerly innocent bot into something vile and offensive. Simply put, AI has the potential to run amok without adequate human oversight.

How Humans Can Prepare

Within these three categories there will be numerous positions and opportunities for human workers to future-proof their careers. The best place to start is through education. Learning new skills and gaining a fundamental understanding of intelligent automation technology can make you an invaluable asset and catapult your career possibilities.

Ayehu’s Automation Academy is designed to provide individuals of every level with the up-to-the-minute knowledge, experience and tools necessary to develop and expand their automation knowledge. Best of all, it’s available completely free of charge. Develop your skills today to become a trainer, evangelist or manager of tomorrow. Enroll for free today!

The Secret to Surviving the Tech-Led Revolution

The Secret to Surviving the Tech-Led Revolution

Automation has been at the forefront of the digital revolution for decades, primarily because it maximizes efficiency, reduces costs and accelerates service levels. But the cloud, mobile and other innovative technologies – coupled with an ever-growing volume of raw data – have led to dramatically more complex IT environments.

According to ESG’s IT Spending Intentions Survey from 2018, 68% of those surveyed said their IT infrastructures are significantly more complex than they were just two years ago. Furthermore, 39% of respondents listed automated IT operations as a critical component of survival in today’s digital age.

In response to this increasing complexity, organizations are beginning to make the shift toward the next generation of automation – from basic to intelligent. This new level of automation involves technologies like machine learning and artificial intelligence to orchestrate workflows across a multitude of tools, systems and processes.

In fact, with the right platform, it is now possible to fully automate L2 and L3 tasks – functions which have traditionally required the use of human judgment. Now, those insights lie within the data itself and can be extracted, interpreted and leveraged autonomously by AI.

Embracing intelligent process automation is also enabling enterprises to lay the foundation for AIOps, a focus area that experts predict will boom over the next five years or so.

AI and ML: Augmenting IT Operations

AIOps is helping IT teams manage the increasing challenges created by data and digital disruption, leveraging intelligent process automation and orchestration to gain competitive advantage. Thanks to the powerful processing capabilities of artificial intelligence, IT can sort through mind-boggling amounts of data points to find the proverbial needle in a haystack.

The role of humans in this increasingly tech-driven environment is still present, though it too is evolving. Rather than relying on error-prone employees to handle the bulk of the processing work, human cognition and advanced skillsets are being used to define that proverbial needle.

In response to this, more organizations are focusing their efforts on reskilling and upskilling their existing staff to bring them up to speed on ML and AI technologies.

Making the Switch to Autonomous Operations

Autonomous operations (AO) utilizes advanced AI to deliver unassisted responses to IT incidents across the entire infrastructure. Thanks to the self-learning capabilities of ML algorithms, AO is able to continuously improve its ability to identify patterns and carry out the appropriate actions.

Again, human workers are still needed in an AO-driven environment, but in the role of supervisor as opposed to operator. Yet as the software continues to evolve and improve, and as errors consistently decrease over time, full autonomy and a zero-touch IT operations environment will one day become a very real possibility.

The Role of Data

The key to success with intelligent automation is accurate data, as this enables users to write more impactful rules. There is little to no value in static data. These days, it’s all about dynamic information which comes from things like descriptive metadata as well as relational and behavioral data.

In order to harness this dynamic data and gain adequate insights from it, organizations need to develop software-defined IT environments. Intelligent process automation is about the ability to not only proactively identify anomalies, but to also remediate those issues automatically without causing any business disruption.

The Right Way to Automate Intelligently

In today’s competitive landscape, automation is no longer an option but a necessity. That said, there’s a right way and a wrong way to leverage this game-changing technology. Start by weighing the time, effort, complexity and frequency of a given task and then benchmarking these factors against the cost of transitioning that task to intelligent process automation. From there, create a prioritized list. This will help you maximize ROI and harness the full potential of intelligent IT operations.

Not sure where to start? Why not give intelligent process automation a test drive free for 30 full days? Click here to launch your Ayehu trial today.

5 Ways Intelligent Automation is Shaping the Future of Work

5 Ways Intelligent Automation is Shaping the Future of Work

In terms of disruptive technology, intelligent automation has gained tremendous ground. In fact, according to Statista, more than half of today’s business leaders say they expect to implement automation in the coming years. And for good reason. While technologies like traditional workload automation, cloud computing and Software-as-a-Service (SaaS) reduce costs and provide the flexibility to perform routine tasks and workflows, artificial intelligence (AI) brings these benefits to a whole new level with the capability of performing tasks that normally require human intelligence.

Intelligent automation software enables businesses to perform much more diverse and complex activities without the need for human intervention. Furthermore, thanks to machine learning algorithms, this type of platform is capable of learning and improving entirely on its own based on data from past experience. Artificial intelligence can also provide valuable insight and decision support for management. But how does all of this translate into actual, tangible return on investment? Let’s take a look.

Drastically Saving Time and Money

When a good portion of business processes are shifted from human to machine, the operation runs far more efficiently. Work is performed faster and more accurately, which equates to greater productivity and higher service levels. Fewer man hours results in tremendous savings for the organization. (In one recent case study, one global enterprise slashed man hours by 1,500 in less than a year simply by adopting intelligent automation. That reduction resulted in an overall savings of nearly $500k.)

Distinct Edge Over the Competition

Staying a step ahead of the competition is the key to success – especially in today’s global marketplace. Every company is chasing digital transformation and hoping to claim their spot at the head of the pack in their respective industry. The use of intelligent automation can facilitate this transformation, not only be streamlining processes, but by empowering human workers.

When the mundane tasks and workflows no longer require human input, employees are able to apply their skills, time and effort toward more important business initiatives. The freedom to be creative breeds innovation which can provide the competitive advantage companies are striving for.

Agility and Scalability

The ebb and flow of business has long been a challenge for organizational leaders. Scaling up as needed based on sudden changes in market demand is not only difficult, but it’s also quite costly. Conversely, in situations when finances are lean, such as during economic recessions, the ability to maintain an expected level of production on a limited budget is incredibly problematic.

The deployment of intelligent automation resolves both of these issues by enabling businesses to scale up or down at a moment’s notice. Seasonal or other business influxes can be met seamlessly thanks to the ability of software robots to take on some of the workload. And when it comes time to tighten the belt, automation can help skeleton crews operate as if they were fully staffed. Every business leader understands the importance of agility like this.

Maximizing Uptime

Another way intelligent process automation can deliver tangible benefits to a company is through improved system operability. According to Gartner, the average cost of IT downtime is $5,600 per minute. Due to variations in how businesses operate, experts estimate that on the low end, downtime can cost as much as $140k per hour, while at the high end, can run upwards of $540k per hour.

Regardless of which end of the spectrum a business happens to fall on, system outages can be, without question, downright disastrous. Enter intelligent automation and suddenly there’s an army of robots monitoring the infrastructure 24 hours a day, 7 days a week, 365 days a year. Furthermore, artificial intelligence is capable of identifying threats that could take days, weeks or longer for humans to spot. When incidents can be pinpointed quickly and the platform itself is capable of addressing and remediating those issues, downtime can be dramatically reduced and, in many cases, prevented altogether.

Data-Driven Decision Support

Because intelligent automation is powered by AI and machine learning, it is inherently capable of analyzing massive amounts of data and extracting value. Furthermore, AI-powered automation can then turn that data into actionable insights that can be utilized by business leaders to make better decisions.

Incorporating advanced business automation technology into the mix enables the analysis of overall organizational performance. With these intelligent analytics, business leaders can more effectively identify and implement the right approaches to achieve improved performance over the long-term.

Could your organization benefit from any of the above? If so, adopting intelligent automation should be on your list of priorities for the coming year. Get a jump start by taking Ayehu for a test drive today.

How Automation Levels Up AIOps

automation levels up AIOps

In today’s increasingly complex digital environment, the ability to pinpoint, resolve and mitigate potential IT problems has never been more critical. And with a hybrid blend of public and private cloud, on-premises and virtual servers, a growing variety of mobile devices and a skyrocketing volume of network and application traffic, it’s also never been more challenging. To address this significant concern, organizations are turning to artificial intelligence for IT operations – or AIOps for short.

The term AIOps encompasses the use of advanced data analytics technologies, such as AI and machine learning, to automate the process of identifying and remediating performance issues. AIOps leverages the colossal volume of data generated by IT services and systems to proactively monitor the infrastructure and gain complete visibility over all system and application dependencies. These advanced capabilities enable AIOps to manage and address potential problems, often before they occur.

Organizations put AIOps in place to gather and analyze all IT operational data and simultaneously automate all main IT operations. The AIOps system then organizes and prioritizes that data, presenting it to IT managers so they can react accordingly. In short, AIOps provides IT decision-makers with the insight they need to stay a step ahead of IT operations. Gartner predicts that by 2023, the use of AIOps will increase from 5% to 30%.

The Key is Automation

The most critical component to a smooth and efficiently run AIOps is automation. This technology helps AIOps to perform ongoing monitoring while adhering to predetermined policies and dependency mapping and quickly and effectively carry out the steps necessary to resolve events or failures.

With all of these technologies operating in tandem, and automation at the center, AIOps can ultimately help to reduce the volume of potentially damaging events, provide proactive alerts to issues that could cause an outage, pinpoint the root cause of those issues and apply intelligent process automation to autonomously remediate.

AIOps is capable of increasing the effectiveness of infrastructure resources, streamlining and expediting service requests and problem resolution, and ultimately generating consistent, measurable value from its ability to support current and future business initiatives.

The Benefits of AIOps

Harnessing the power of automation in combination with AIOps delivers a multitude of benefits for IT. Firstly, it can dramatically enhance and improve the effectiveness of existing tools and services. And since it saves time while also increasing efficiency and productivity, organizations employing AIOps can also realize a decrease in overall expenditure.

Likewise, AIOps can also reduce the amount of time and effort currently required to manage service requests and remediate performance issues and outages. All of this adds up to improved service levels, a significant reduction in risk, and a quicker time-to-market for new initiatives.

Automated AIOps runs on a 3-phrase approach:

  • Identify
  • Analyze
  • Respond

In other words, it monitors the environment to detect any potential anomalies or concerns, then analyzes, validates and prioritizes those potential events before finally determining the best course of action to take to address the issue at hand. While this last step may involve escalation to a human decision-maker, in most cases, these steps can all be carried out without the need for human intervention. Therein lies the true value of AIOps.

To learn firsthand how AIOps can help position your organization for future stability and sustainable success, try it yourself for 30 days. Click here to start your full-feature trial of Ayehu NG today.

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Harnessing the Cognitive Capabilities of Intelligent Automation

In order for business leaders (and ultimately their teams) to meet the growing demands of maximum operational efficiency, organizations across the globe and in just about every industry have been turning to automation for decades. We have reached a time, however, in which basic automation is no longer sufficient. In response to this, enterprises are taking things a step further by utilizing the power of AI and cognitive technology through intelligent automation to address the increasingly complex challenges they’re facing.

The Next Generation of Automation

In its simplest form, machine learning is a technology through which machines (software robots, if you will) are capable of learning from data and applying what they’ve learned to either provide insight to key decision-makers or resolve problems independently. Rather than being programmed to follow a specified series of steps, intelligent bots can now complete tasks without the need for human intervention. The results have been impressive, particularly in terms of efficiency gains.

Logically speaking, automated tasks that are carried out by basic automation are fastest when they are repetitive. With non-intelligent automation bots, workflows that follow a set of predefined rules are most effective at producing effective results immediately. For instance, employees who waste hours a day manually copying and pasting data would realize instant value by moving that task to basic automation.

There are instances, however, when data is incomplete, requires multiple sources or needs to be enhanced in order to carry out a particular task. For example, resolving a single issue for a customer may require accessing half a dozen different systems and data sources. To bridge this gap, organizations need intelligent tools. AI-powered automation ties together siloed systems and provides independent resolution while reducing errors and ensuring compliance.

The key to this? Cognition. Leveraging automation tools that feature advanced cognitive abilities that are similar to humans, organizations can create a more unified infrastructure, improve business-related outcomes and dramatically accelerate and enhance customer service. In addition to basic automated tasks and workflows, companies can deploy virtual support agents to further automate processes, including those that require context and conversation.

What Should Be Automated?

To determine what to automate, decision-makers should begin by evaluating whether or not the tasks, workflows and processes could be improved or possibly even eliminated prior to introducing automation into the mix. Some things will be obvious – the mundane, repetitive and low-value busywork, such as data management or reporting. These things can (and should) be easily transitioned from human worker to automation robot.

Looking past these rote tasks, however, some work is currently considered to be more suited for humans. For instance, activities that require understanding of text, complex decision-making or matching of patterns. Additionally, tasks that rely on emotional intelligence and/or require interaction and collaboration with other human workers have previously been considered too difficult, if not impossible, to automate. That’s where intelligent cognitive automation technology has become a game-changer.

This type of advanced automation incorporates machine learning to facilitate decision-making, natural language processing for understanding and contextualizing written and verbal communications, and state-of-the-art predictive analytics and pattern matching to handle process exceptions.

Collaborative Process Optimization

Of course, even with all of these technological breakthroughs, humans are still required to choose, apply and manage automation – at least for the time being. One area where artificial intelligence and humans are already working in tandem is in the way of decision-making support. For instance, next generation tools like Ayehu combine cutting-edge automation and cognitive technologies to determine how processes are configured and/or currently operating. From there, automatic suggestions can be made to further improve workflows and optimize processes.

While many still worry about intelligent bots taking over human jobs, particularly due to the rapid evolution and development of artificial intelligence, a more accurate reality will be humans and intelligent bots working side by side to add value and collaboratively achieve optimal business outcomes.

Experience the power of intelligent automation for yourself by starting a free 30-day trial of Ayehu. Click here to get started!

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