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Imagine a World With No IT Outages. Is It Possible? Yes! Here’s How.

Imagine a World With No IT Outages. Is It Possible? Yes! Here’s How.

Over the past few decades, the IT world has undergone what can only be described as a revolution. The recent COVID-19 pandemic has brought even greater awareness of these advances in technology, particularly as it relates to the ability for organizations to operate semi or fully virtually. IT teams across the globe have worked tirelessly behind the scenes, leveraging every tool and strategy at their disposal to ensure that critical support functions remain intact and service carries on uninterrupted.

Today, more than ever before, ITOps teams are focusing on ways to seamlessly identify and address incidents, not as they arise, but before end users are even aware there is a problem. Are we nearing a world in which IT outages are a thing of the past? It’s quite possible. Here’s the scoop.

Greater complexity demands more intelligent technology.

AIOps has become a widely accepted and generally celebrated approach to help organizations adapt and scale to modern complexity using the advanced capabilities of AI and machine learning. The goal is to transition IT monitoring and analysis from human agents to intelligent machines through automated detection and remediation.

Ticket overload and manual workflows have long burdened IT teams – that’s nothing new. Over the years, however, the rapidly evolving IT ecosystem has multiplied the challenges and increased the demands exponentially. Simply put, the traditional human-centric way of operations management is no longer sufficient.

Leveraging the innovative, intelligent technologies that are currently available to handle the workload is effectively equivalent to “fighting fire with fire,” if you will. Advanced AI/ML is capable of sifting through mountains of data in seconds, pinpointing anomalies and either alerting the appropriate human agent, or carrying out the necessary remediation steps entirely autonomously. This allows IT teams to stay ahead of the curve, actively preventing incidents and outages rather than scrambling to mitigate the aftermath.

Navigating the new “reality” using tech for offense vs. defense.

As the dust continues to settle and organizations across all industries begin to settle into their “new normal” of remote work, business leaders are beginning to shift their focus to ensuring operational continuity and establishing the necessary infrastructure that’s needed to sustain this new way of work indefinitely.

Companies already harnessing intelligent IT technologies will enjoy improved visibility, enhanced efficiency and greater competitive advantage. By using AI, ML and intelligent automation, these forward-thinking firms will achieve faster and more effective root-cause analysis and resolution, enabling them to maximize uptime by staying out in front of potential IT outages. In other words, they will take a proactive approach to ITOps rather than a reactive one.

When intelligent process automation is used to do the heavy-lifting, IT teams will be able to focus on other innovative and revenue-generating activities. In a world where IT outages are no longer an issue, everybody wins – the customer, the end-user, the IT worker, and ultimately the organization as a whole.

Would you like your organization to be a front-runner in this outage-less world? It’s as easy as adopting the right technology. Click here to start your free trial of Ayehu NG and put the power of AI, ML and intelligent automation to work for your business!

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.