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Leveraging AI to Level-Up Your CIO Career

Leveraging AI to Level-Up Your CIO Career

If you look up “stressful career choice,” the role of CIO would probably be at the top of the list. Not only is there the task of overseeing current day-to-day IT activities, but today’s IT executives are also facing mounting pressures to consistently identify and deploy cutting-edge, game-changing innovations. It’s enough to drive even the strongest of individuals over the brink. Thankfully, there’s one technology that could easily become the secret weapon for sustainable career success. That technology is AI. Here’s how to get started.

Recognize the key difference that AI brings to the table.

The first thing that needs to happen in order for a CIO to take full advantage of what AI can do for them is to take on the right perspective. Specifically, unlike a survey or file-sharing tool, AI isn’t simply a tactical technology. Instead, it’s strategic – particularly in that it’s capable of not only enhancing the current way a business operates, but it’s also capable of paving the way for new revenue streams.

Provided it’s fed an adequate amount of data that is both relevant and of high quality, AI can provide targeted predictions and support complex business decisions that can shape the direction a company moves in.

It’s also important not to fall into the trap of viewing AI as solely a solution for everything that’s going wrong in an organization. Rather, this technology can and should also be used to identify vulnerabilities that may have otherwise gone undetected. AI is capable of sifting through massive amounts of data, prioritizing it and even exposing unknown biases that might have caused issues down the road.

These important disparities are not mere nuances. If leveraged properly, they can become key differentiators, both for the company as well as the CIO’s career.

Start small, win quickly.

With so much pressure weighing on their shoulders, it can be incredibly tempting for an ambitious CIO to attempt AI adoption on a grand scale. Go big or go home, right? Not necessarily – at least not as it relates to being successful with artificial intelligence.

Because the technologies that drive AI are constantly evolving, it’s best to focus primarily on experimenting and learning. This enables a more close alignment with the underlying business needs that are being addressed. It also allows greater control over the scope and results of the AI initiative.

The most effective way to get started with AI is to target opportunities that are the most ripe for optimization. Because these are likely to be smaller initiatives, they are also more likely to quickly produce measurable results.

These initial projects will have the best chance of succeeding if you:

  • Experiment on smaller issues with the potential to produce higher ROI
  • Start with existing workflow templates rather than building your own model (i.e. resist the urge to “reinvent the wheel”)
  • Use data that is of the highest quality and relevant
  • Incorporate AI into existing business processes where disruption will be minimal
  • Maximize productivity by automating highly repetitive and well-defined decisions

Bottom line is this: quick wins will help build confidence and gain traction for larger initiatives that have greater impact and visibility.

Think like a CEO.

As mentioned, artificial intelligence is a strategic technology. Therefore, to get the most out of it, there must be strategic thinking. The path to widespread permeation of AI is paved with many challenges. Taking more of a CEO-like approach to these initiatives can help CIOs become more proactive in recognizing and addressing evolving priorities, misaligned strategies, and the obstacles that stand in the way of true and effective collaboration.

Furthermore, because the goal will inevitably be to deploy AI across the entire organization, developing a deeper understanding of all business departments (like a CEO would have) is critical. Working with each business segment to identify those smaller issues that represent the highest and fastest return will make enterprise-wide adoption of AI much easier to achieve. 

A great way to start is to approach each LOB and pose a simple question, like “If we can do X, then we can accomplish Y.” In other words, for the sales department, this question might look something like, “If we can score leads better, we can make our sales team more efficient.” In customer service, it might be, “If we can automate commonly asked question, we can improve customer response rate and optimize our support staff.”

With this information in hand, the CIO can then determine how AI can be applied as a solution to as many of these scenarios as possible and then begin tackling them one by one, ultimately delivering value across the entire organization.

Accept that the time is now.

The tech industry is notorious for tossing out buzzwords and fly-by-night concepts that gain instant notoriety but then never really seem to go anywhere. AI is not one of these terms or concepts. In fact, it’s become abundantly clear that artificial intelligence will soon become an integral part of global business operations in every field and industry.

Don’t be the last one to jump on the bandwagon. Find out what AI is capable of doing for your organization and your career by starting your free 30-day trial of Ayehu today.

5 Mid-Year Artificial Intelligence Trends to Watch For

We’ve officially reached the mid-way point of 2020, and what a year it’s been so far! Between political turmoil and the worldwide health pandemic, the economy has seen its share of ups and (way) downs. One thing that has remained constant through all the uncertainty is technology – in particular, artificial intelligence. In fact, AI has quickly emerged as a versatile and viable solution to almost all of the problems businesses are facing currently. Let’s take a look at what our experts believe will take place in the AI sector over the next six months.

An increase in availability and accuracy of data will make AI even more useful.

We don’t mean to beat a dead horse, but we simply cannot state it enough: artificial intelligence is only as good as the data it is fed. Because of this, many organizations that have tried to adopt AI in the past have failed, primarily due to a lack of relevant and accurate data. As technology continues to improve at a lightning pace, however, more and more quality data is becoming available. In particular, today’s technology is now capable of simulating real-world scenarios, which reduces risk and cuts costs, resulting in AI that is even more powerful, accurate and ultimately more valuable.

Collaboration between human and digital workers will continue to increase.

Let’s face it. Artificial intelligence is here to stay. And as we’ve learned over the past decade or so, it’s not here to displace human workers, but rather make their jobs and their lives easier. This trend will continue as we wrap up 2020 and move into 2021. As people get comfortable with the idea of working alongside intelligent bots, more processes and workflows will be transitioned from human to machine, skyrocketing productivity and enabling organizations to maximize the human skills that AI isn’t quite capable of just yet. For many, this will require learning new skills, so prepare accordingly.

AI will play a more prominent role in cybersecurity.

They say the best defense is a good offense, and this is certainly true in the area of cybersecurity. The fact is, cybercriminals are leveraging the most up-to-date technology to carry out their nefarious plots. The most effective way to combat these criminals and ward off their attacks is to utilize the same advanced technology against them – essentially, fight fire with fire. AI-powered intelligent automation will increasingly be used to autonomously and continuously monitor systems and infrastructures, identifying areas of concern and raising alarm before breaches occur and preventing sensitive data from becoming compromised.  

Interactions with AI will become more mainstream and far less detectible.

In recent years, despite tremendous advancements in technologies like natural language processing (NLP), interactions with robots vs. human agents were relatively easy to spot. With NLP algorithms becoming increasingly capable of understanding context, distinguishing between humans and machines will become much more challenging. And even though recent numbers indicate that the majority of people prefer to receive support from humans than robots, as technology continues to advance at a rapid pace, there’s a very good chance that will change. In fact, there’s a good chance that over the next several months, we’ll begin engaging with intelligent bots without even realizing it.  

Remote work and augmented workforces will become part of the norm.

Over the past several months, thanks to a global health crisis, many organizations around the world were forced to make sudden changes to their workforce. One of the biggest shifts was toward a remote work environment. Technologies like AI and intelligent automation have made this transition much more feasible for many. However, as the dust begins to settle, business leaders are discovering that, with the right technology and approach, these types of arrangements are not only possible, but are actually more favorable for the long term. As such, many will continue operating either partially or entirely remotely, leveraging artificial intelligence to augment and balance their workforce.

Are you behind the curve when it comes to AI, machine learning and intelligent automation? Get up-to-speed and in the game quickly by downloading your free 30-day trial of Ayehu NG today. Click here to get started!

5 Common AI Pitfalls that Trick Unsuspecting CIOs

If there’s one thing CIOs are good at, it’s ignoring the hype and extracting the value out of technology. Except, however, when it comes to artificial intelligence. Whether it’s all the pomp and circumstance that clouds their reason or the lofty promises that tend to distract them, for some reason, a surprising number of IT leaders seem to fall into similar traps. It can be a costly lesson filled with delays and missteps. To avoid heading down this path in your organization, here are five risks to watch for.

Forgetting the importance of data.

We’ve said it time and time again, but an artificial intelligence solution is only as good as the data it has to work with. It’s sort of like having a Lamborghini and using subpar fuel. If you haven’t given adequate attention to ensuring that your AI platform is being fed data that is both accurate as well as relevant, then you will not realize much of any return on your investment (and you’ll probably end up holding the bag for it at the end of the day). A good strategy is to first identify which datasets are needed for each desired outcome and then building from there.

Being too quick to choose a solution.

A lot of CIOs get so amped up over the promises of what AI can deliver to their organization that they fail to perform due diligence when selecting a platform. Not only are solutions different in quality and potential benefits, but vendors themselves can vary widely on the spectrum of trustworthy vs. fly-by-night operations. Don’t fall for lofty promises. They may be legit, but it’s up to you to verify that by asking to see tangible results before signing on the dotted line.

Solving for the wrong problems.

Just because an AI solution works, doesn’t mean it’s delivering value. Ultimately, the goal isn’t to simply deploy artificial intelligence technology for the sake of doing so, but to generate actual return on your investment. To do this, you must define realistic, achievable objectives and outcomes that can be effectively tracked and measured. Otherwise, you’ll just end up with a fancy automation tool that does nothing more than cost you money.

Being lured by bells and whistles.

There are some pretty amazing artificial intelligence solutions out there. Unfortunately, many of them are so complicated, they’re actually not worth the investment to begin with. In fact, when a system is too complex, not only does it become detrimental, but it can lead to ancillary problems, like a lack of experienced personnel to manage the technology. Again, the goal is to deliver value, not get the fanciest tool on the market. Instead, you want a solution that’s advanced but also intuitive and as easy to use as possible.

Equating price with worth.

The fanciest tool on the market may have far more features than your organization even needs. And, as mentioned, the more bells and whistles, the more complicated and challenging it will be to deploy. Don’t be fooled into thinking that a hefty price tag means you’re getting the best possible solution. To the contrary, the platform that most closely matches your business needs may not only save you money upfront, but may also be more valuable in the long run as well.

Artificial intelligence has the potential to bring your organization to the next level. But only if it’s implemented the right way. If you’re just starting out on your AI journey, be cognizant of the above pitfalls so you can avoid them for yourself. If you’ve already fallen into one or more of these traps, the good news is, it’s never too late to right the ship.

Ayehu NG lets you harness the power of AI in minutes with a code-less, drag and drop visual designer and over 200 ready-to-use workflow templates. Schedule a live demo or get started today with our free 30-day trial.

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!

The Importance of Reskilling Employees for the Future of Work

The Importance of Reskilling Employees for the Future of WorkA few months ago, nobody could have imagined a rampant virus shutting down the world and bringing the global economy to its collective knees. Yet, here we are, several months into the COVID-19 pandemic, and most of us still trying to adjust to this sudden and severe change to life as we know it. Organizations around the world have been forced to adapt to a new way of work, whether having to remain operational with a reduced workforce, quickly having to roll-out work-from-home strategies or some combination of both.

As the dust begins to settle, however, a new business need has begun to emerge. Business leaders everywhere are now recognizing the critical importance of being prepared and planning ahead. And one of the most effective ways to do so is to focus on reskilling employees to get them future-ready. Likewise, those individuals who find themselves unfortunately out of work due to the current crisis have the opportunity to position themselves as much more marketable and therefore more employable by learning and mastering new skills.

One of the biggest changes we are likely to see as the world returns to work is greater adoption of a hybrid workforce. That is, humans working alongside digital agents. Many organizations are expected to continue partial or possibly even entirely remote operations, especially after discovering that not only is work-from-home feasible, but it’s an incredibly efficient and cost-effective way to do business. Of course, this would not be possible without the right policies and technologies in place. That’s where reskilling comes into play.

Even before the current health crisis, innovative capabilities, like automation and artificial intelligence, were already causing a good amount of disruption to jobs and the skills human workers needed to know in order to remain employable. In fact, in 2017, McKinsey estimated that as much as 14 percent of the global workforce would either need to acquire new skills or change occupations by 2030 due to AI and automation. To put this into perspective, that’s some 375 million workers. Another recent McKinsey report revealed that 87% of executives said they were either expecting an increased skills gap in the near future or were already experiencing one.

This latest pandemic has brought this need to the forefront and made it much more urgent. Employees across almost every industry must find a way to adapt to the rapidly evolving conditions and organizations must figure out how to transition those workers into new roles and responsibilities. While the two go hand in hand, the “new normal” will ultimately be more about the role of AI and automation than it will about remote work. It will be about how business leaders across the board are able to retrain or upskill their existing workforce to prepare them for the post-pandemic reality.

To rise to this change, organizations must develop strategic talent strategies that include advancing and honing employees’ skills from a holistic standpoint. That means strengthening their digital capabilities as well as their cognitive, emotional and social skills. If there’s ever been a time for companies to commit to and invest in the education of their workers, it’s now. Focusing on this, along with investing in the right tools and technologies, will help bolster a company’s posture against future business disruptions.

Likewise, employees themselves should be taking this opportunity to further their skillsets and adapt to the changing landscape. Whether their employer is resistant to the topic of reskilling or they are one of the millions currently unemployed, individual workers would be wise to seek out available learning opportunities on their own. At a time when job security is virtually non-existent and the skills gap is widening, embracing intelligent automation will undoubtedly create opportunities for new positions in the future of work.

Whether you are an organization seeking to get ahead of the next potential crisis and strengthen your position in the marketplace of tomorrow or an ambitious individual looking to future-proof your career, Ayehu Automation Academy is a great place to start. Find out more about the academy and enroll yourself or your team today by clicking here. 

eBook: 10 time consuming tasks you should automate

The Secret to Creating an AI-Powered Organization (Hint: It’s Not Technology)

The Secret to Creating an AI-Powered OrganizationAsk most companies that market AI products what the key is to successful digital transformation, and chances are, the knee-jerk reaction of far too many will be “technology.” We’re certainly not going to say that technology doesn’t play a pivotal role. To the contrary, it’s essential. What we are proposing is that creating a self-driving, AI-powered organization takes much more than just cutting-edge tech. To position your business for success, here’s what else you’ll need to do.

Expand your knowledge base.

Technology is evolving at such a rapid pace, if you’re not mindful, it can be remarkably easy to become stagnant and suddenly realize you’ve been left behind. Do you have to become an expert in every product, app or platform out there? Of course not. But, you do need to know just enough to be dangerous. What we mean by that expression is, you need to gain enough insight to be able to identify where and how technology will be most useful. From there, you can determine which technologies make the most sense from a logistical standpoint.

How should you expand your tech know-how? There are dozens of ways, and many of them are convenient and free. Take, for instance, the Ayehu Automation Academy. With this free online course, you can quickly comprehend and cultivate practical skills through a variety of interactive learning activities and develop a foundational understanding of automation technology.

Focus on soft-skills.

Recruiting for technology positions isn’t easy – especially when it comes to finding candidates skilled in the field of artificial intelligence. The good news is, tech skills aren’t the only qualifying factors for being successful. In fact, they’re not even in the top 5.

Think about it. If you’ve got intelligent automation to handle the grunt work (simple as well as complex), you don’t need the human equivalent to robots. You need people who are not only tech-savvy, but also possess the soft-skills that cannot be replicated by AI. Skills like empathy and creative thinking. You want right-brained individuals who can think outside the box and find new ways to extract value from the technology that’s available to them. This is true innovation.

Avoid tech overload.

With so much available tools, it can be tempting to use as many as possible. But while it’s entirely possible, and in many cases wise, to utilize a wide variety of tech tools for their various capabilities, doing so without a plan can actually harm, rather than help your organization.

For instance, if each department is using their own systems and these systems do not connect, you’ll end up with silos that work against instead of with one another. This can cause costly delays and errors. It can also overload your IT team and lead to burnout.

It’s fine to avail your company of technology, but be sure to do so in a measured, strategic manner that includes a plan for connecting everything onto one centralized dashboard. Specifically, seek out only tools that can be easily and seamlessly integrated so that you can maximize the benefits of all.

Building an AI-powered organization will become central to success in the digital age, but as with anything else, there’s a right way and a not-so-right way to go about it. Be careful not to get tunnel-vision and focus solely on technology as the solution. The ideal approach is one that marries digital with human workers and celebrates the unique and valuable capabilities of each.

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!

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