Preparing for the Future of Work: Transitioning to Intelligent Automation

These days, a growing number of organizations are making the shift toward integrating intelligent automation as a critical component of their business model. But it should never be about automating just for the sake of automating. That’s not going to help you win the AI race. The future of work will involve more of a hybrid approach that balances artificial with human intelligence for a “best of both worlds” kind of environment.

From the top down, it’s important to identify and address the challenges companies will face when implementing initiatives around critical areas, such as analytics, intelligent process automation, digital and AI. There is no shortage of lessons to be learned and common themes from which to gain knowledge. For those charged with preparing their organizations for what the future of work will inevitably become, here are five key insights to keep in mind.

Expect the unexpected.

While it’s true that business leaders can learn from others who have gone before, the fact is, every hybrid AI initiative is unique. As such, it’s important to design fluid systems that are capable of accommodating requirements, expectations and business challenges that are often unexpected. To some degree, the future of work is a moving target. Systems that can adapt and evolve will be the ultimate key to success.

Mistakes will happen.

It’s been said that failure is the key to success. This is an important mantra to keep top of mind when preparing for the future of work. Remember that when it comes to any type of change process, mistakes are inevitable. When and if you do fail, the key is to fail fast and bounce back by reflecting, regrouping and iterating your subsequent attempts with a greater understanding of what you’ll need to do in order to succeed. Decision-makers must also recognize that change is a necessary investment that requires the right communication and resources at the right time.

Start with small, measurable wins first.

Automating at scale isn’t something that takes place overnight – at least not if it’s done correctly. As you move toward the future of work and strive for digital transformation, it’s wise to start with smaller wins that can quickly generate ROI. To begin, focus on the tasks already being performed by the organization that are menial, repetitive and mature. Capturing those quick wins early will gain you buy-in and provide a solid foundation upon which to build out an organization-wide automation strategy.

Identify and communicate the ‘hows’ and ‘whys’ across the enterprise.

When it comes to good governance, it’s critical that executives carefully develop their strategic plans around intelligent automation. More importantly, they must openly and consistently communicate the hows and whys behind their decisions to everyone across the organization. As mentioned, incorporating the valuable skills of humans in with the benefits of automation and AI is the ideal scenario. As such, proactively reskilling, retraining and reorganizing employees will become essential over the coming months and years.

Automate accordingly to address business problems.

Some organizations find it necessary to enlist the help of consultants or outsourced companies to help them identify the best processes to begin the automation journey. Don’t be afraid to admit if this assistance is something that could benefit your organization. Either way, the goal is to gain a deeper understanding of business priorities so you can identify quick successes. Ideally, the automation strategy should be one that is a joint initiative between the IT department and the rest of the business.

Ultimately, what these five insights have in common is that they require executive buy-in, AI investment that is strategic and a shift toward a business model that involves a convergence of innovative technologies. Master these five steps and your organization will be much better positioned to be successful in the future of work.

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4 Tips for Successful Adoption of AI at Scale

Utilizing artificial intelligence on a smaller scale is relatively simple in nature. At the enterprise level, however, it isn’t always so straightforward. This may be a contributing factor to the recent survey results from Gartner indicating that while 46% of CIOs have plans for implementing AI, only a mere 4% have actually done so. Those early adopters no doubt have faced and overcome many challenges along the way. Here are four lessons that you can learn from that will make adopting AI at scale easier.

Start small.

Desmond Tutu once said that the best way to eat an elephant is “one a bite at a time.” Just because your end goal is to have enterprise-wide adoption of AI doesn’t mean you have to aim for that large of an outcome right off the bat.

Most often, the best way to initiate a larger AI project is to start with a smaller scope and aim for “soft” rather than “hard” outcomes. In other words, rather than primarily seeking direct financial gains, focus instead on things like process improvement and customer satisfaction. Over time, the benefits gained by achieving these smaller “soft” goals will lead you to your larger objectives anyway.

If decision-makers in your organization require a financial target in order to start an AI initiative, Gartner VP and distinguished analyst Whit Andrews recommends setting the target as low as possible. He suggests the following: “Think of targets in the thousands or tens of thousands of dollars, understand what you’re trying to accomplish on a small scale, and only then pursue more-dramatic benefits.

Focus on augmentation vs. replacement.

Historically, significant tech advances have often been associated with a reduction in staff. While cutting labor costs may be an attractive benefit for executives, it’s likely to generate resistance amongst staffers who view AI as a threat to their livelihood. A lack of buy-in from front line employees may hinder progress and result in a less favorable outcome.

To avoid this, shift your approach to one that focuses on augmenting human workers as opposed to replacing them. Ultimately, communicating that the most transformational benefits of AI lie in the technology’s ability to enable employees to pursue higher value and more meaningful work. For instance, Gartner predicts that by 2020, 20% of organizations will have workers dedicated to overseeing neural networks.

Make an effort to engage employees and get them excited about the fact that an AI-powered environment will enhance and elevate the work they do.

Prepare for knowledge transfer.

The majority of organizations are not adequately prepared for AI implementation. In particular, most lack the appropriate internal skills in data science and, as a result, plan on relying heavily on external service providers to help bridge the gap. Furthermore, Gartner predicts that 85% of AI projects initiated between now and 2022 will deliver erroneous outcomes due to inaccurate or insufficient data and/or lack of team knowledge/ability.

In order for an AI project to work at scale, there must be a robust knowledge-base fueled by accurate information and there must be adequately trained staff to manage it. Simply put, relying on external suppliers for these things isn’t a feasible long-term solution. Instead, IT leaders should prepare in advance by gathering, storing and managing data now and investing in the reskilling of existing personnel. Building up your in-house capabilities is essential before taking on large-scale AI projects.

Seek transparent solutions.

Most AI projects will inevitably involve some type of software, system, application or platform from an external service provider. When evaluating these providers, it’s important that decision-makers take into account not only whether the solution will produce the appropriate results, but also why and how it will be most effective.

While explaining the in-depth details of something as complex as a deep neural network may not always be possible, it’s imperative that the service provider be able to, at the very least, provide some type of visualization as to the various choices available. At the end of the day, the more transparency that is present, the better – especially when it comes to long-term projects.

For more information on how to incorporate artificial intelligence into your strategic planning for digital transformation, check out this resource from Gartner. And when you’re ready to move forward with your AI initiative, give Ayehu NG a try free for 30 days. Click here to start your complementary trial.

Your Top Artificial Intelligence Adoption Questions, Answered



Is a business case necessary for AI?










Practical advice for organizations just getting started with AI:



A few more considerations:



Need Scalability? Intelligent Automation is the Answer

Imagine how much your company could accomplish if you had a veritable army of employees at your disposal. More importantly, what if these employees were perfectly happy waiting in the background for the next time you needed them? Believe it or not, that’s precisely what you’ll get with intelligent automation. Let’s take a look at the surprising way artificial intelligence can provide your business with the scalability you need to stay on top of your game.

Instant Access

With human workers, it’s not feasible to dramatically increase your workforce whenever the need arises, nor is it easy to decrease your numbers when things get slow. There’s a complicated process behind all of this and time is not on your side. With intelligent automation, however, you have a team of robots who are ready, willing and able to get the job done at any given moment.


Bringing different employees up to speed via on-boarding and training can be challenging and time-consuming, especially in today’s fast-paced, digital age. Not to mention the fact that you have to initiate the entire process over again every time someone new joins the team. Robots, on the other hand, can be “trained” in groups of any size with the outcome being routine and perfect consistency across the board.

Cost Savings

Recruiting, hiring, training and retaining talented employees costs money. In addition to intelligent automation providing the ability to scale up or scale down instantly as well as train and deploy thousands of bots while maintaining complete consistency, all of this can be done at a reduced cost to the business.

Now, let’s take a look at a few real-world applications of these benefits.

Scenario 1

Your business is launching a new product and, as a result, will incur a substantial increase in transactions. Your current workforce is already maxed out and you don’t have the time or the ability to hire any additional employees. Intelligent automation can step in and bridge the gap, handling the influx of work at any capacity necessary without the major hassle and expense of staffing. Then, once things settle down, you can scale back down to normal as needed.

Scenario 2

Business has been particularly lucrative as of late and you’ve had to increase output significantly to meet the increased demands of your customers. Suddenly, the market takes a turn for the worse and your numbers start to rapidly decline. With intelligent automation in place, you won’t have to face the possibility of laying employees off. Rather, you could just scale back the number of robots.

Scenario 3

One of your biggest competitors has launched a new product or service and you’re scrambling to develop and implement something similar. Chances are you can’t afford to hire a slew of new employees to help bring your comparable product or service to market and doing so would take too long. Conversely, putting too much pressure on existing team members could result in costly mistakes and QA issues. AI, on the other hand, is available at the ready to take on whatever is necessary for you to remain competitive.

Without question, intelligent automation has the potential to bring your business to the next level. Are you ready? Give us a call today or download your free 30 trial now to get started.

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5 Things to Avoid for a Successful Intelligent Automation Rollout


Focusing on tools and tasks instead of people.


Failing to adequately calculate and communicate ROI.


Not setting appropriate expectations.


Automating broken processes.


Not using the right platform.


Thinking about trying automation but not sure where to begin?


eBook: 10 time consuming tasks you should automate

And the Employee of the Year Award goes to: A robot?

Imagine: you’re in the annual company meeting and the CEO announces who has been the busiest, most productive employee over the past 12 months. Now, imagine if he completes that statement not with the name of you or any of your co-workers, but instead points to your intelligent automation platform. In other words, a robot.

Can a robot really take the place as employee of the year? The answer is an emphatic yes. Here’s why.

It’s no secret that the IT department is continually being asked to do more with less. In other words, be as productive and efficient as possible while simultaneously limiting the amount of resources being used to do so. As a result, IT leaders have to find a way to maximize output while also minimizing the time and costs associated with producing that output. With humans, this simply isn’t possible without either extending the hours worked or hiring additional staff, neither of which will achieve the goal of keeping expenditures down.

Another area of pressure IT leaders experience is that of user satisfaction. Internal service levels and external customer expectations are increasing at a rapid rate, and if you can’t meet those demands effectively, you will lose your competitive advantage. In other words, your bottom line will suffer. Yet again, in order for human agents to achieve these goals is to either work more or hire additional team members.

Enter intelligent automation, or a team of artificially intelligent robots who can basically take on all the time consuming day to day tasks that the help desk currently handles. Whether it’s password resets, system monitoring, incident management or some other complex workflow, intelligent automation can be leveraged for it all. As a result, the work will be completed faster, with fewer mistakes, driving productivity and efficiency up while also bringing costs down.

Many IT professionals erroneously view these robots as a threat to their very livelihood. After all, if a machine can be used to do all these tasks, what’s the point of keeping humans on staff? Why not automate the entire operation? Well, for starters, many automated processes still require some type of human input.

Secondly, while intelligent automation may take some of the work away from humans, it will inevitably free those humans up to apply their skills to more complex and important business matters. So, it’s not a replacement, but rather a shift in responsibility. Furthermore, experts predict that AI will actually create 58 million new jobs by 2020. As such, it should be embraced rather than feared.

So, when the big boss stands up and hails automation as the company’s busiest employee, that doesn’t necessarily mean bad news for the people who work there. As long as the technology is leveraged properly and viewed as the powerful and innovative tool it truly is, its role as employee of the year is something that will drive the ongoing success of the organization and make the lives of human workers easier and/or more meaningful.

Give the employee of the year a test drive in your own company and experience the power and impact of intelligent automation for yourself by starting your free 30-day trial of Ayehu.

The Rise of Artificially Intelligent Service Management (AISM)

It’s been said that the best way to serve customers is to anticipate their needs, whether it’s a restaurant concierge offering to walk patrons to their vehicles with an umbrella overhead on rainy evenings or rolling out an update on a software product. The same concept can be applied in the IT realm, specifically in IT service management (ITSM).

The fact is, with today’s technology, it’s entirely possible to predict that certain situations will occur, from simple password reset requests to servers crashing. It’s not really a matter of if these things will happen, but rather when. And if you know what’s coming, you can be prepared to respond and, in many cases, even head problems off at the pass.

That’s where artificial intelligence comes into play. Thanks to AI and machine learning technologies, ITSM professionals can now predict potential problems faster and with a much higher degree of accuracy. As a result, the end user (or “customer”) enjoys a much more positive experience. In other words, everybody wins.

What is Artificially Intelligent Service Management?

The core principles of ITSM remain sound. The introduction of AI into the mix doesn’t change this. Instead, it enhances it. AISM simply takes the fundamental concepts and processes of ITSM – incident response, service request management, etc. – and leverages newer and better technologies to make them even more effective. In the context of IT service management, AI can be applied to improve, simulate and/or replace the work of a human agent.

You may be asking yourself, “Isn’t this really just automation?” The answer isn’t necessarily cut and dry. The truth is, we’ve been automating processes and workflows for decades, and ITSM is no stranger to this technology. The difference is that with AI, these processes and workflows become more intelligent and independent. Rather than just carrying out predefined or scripted instructions, AI is capable of identifying and carrying out required actions all on its own.

How does AISM work?

Now, let’s take a look at how AI can enhance the execution of ITSM activities.

Support Request Management

The basics of ITSM: an end user needs assistance. They either pick up the phone to call the help desk, send an email request, submit a support ticket or browse the self-service options (if available). The steps necessary to fulfill that incoming request are then followed and the user receives his or her desired outcome. The problem is, that outcome could potentially take hours, days, weeks or even longer.

Now, let’s look at that scenario with AISM at the helm. The end user initiates contact and immediately receives two-way support from an intelligent bot. They request what they need and the bot – relying on underlying technologies of machine learning, deep learning, neural networks and natural language processing – understands the request and responds accordingly. Rather than waiting for a human to take action, AISM can produce results for the end user within seconds.

Incident Management

The ability to react, respond to and correct an incident is one of the most basic components of ITSM. Traditionally, a form would be filled out. Perhaps the analyst might do a little research. Ultimately, the task is assigned to a team. There it might sit untouched for a while before it is either rejected, resolved or possibly even assigned to another team altogether. In the end, the incident is resolved, but after much back and forth and passing of the torch.

Enter AISM. The end user reports a problem via his or her self-service portal and an incident is immediately created. Thanks to artificial intelligence, however, that same end user may instantly be prompted with various suggestions that are pulled from the underlying knowledge base. This may result in resolution right away.

If not, it is turned over to a support analyst who is automatically provided with suggested resolution methods. The AI can even advise who the incident should be assigned to, what relevant implications may exist, the scope of the situation and more.

Problem Management

In a traditional ITSM setting, problem management would often involve a person taking the time to review prior incident patterns and trends and develop possible resolutions. Along the way, however, many twists, turns, delays and bottlenecks exist. For instance, let’s say a support agent grows weary of addressing the same incidents over and over. The problem may be investigated further. Perhaps some knowledge may be created and a change is even identified. But, given the chaotic nature of the ITSM environment, time passes and nothing really gets done.

Now, take that same scenario in the context of AISM. Instead of a frustrated human agent taking the initiative to identify and resolve problems, machine learning technology continuously scans patterns of data to pinpoint and present potential issues that should be investigated. What’s more, thanks to data processing and learning across multiple patterns of work, AI is even capable of proposing a solution, backed by data-driven risk and impact analyses. In other words, it takes the guess-work out of decisions.

AISM – From Reactive to Proactive and Beyond

Getting back to our original point – that the best customer experiences are anticipatory in nature – AISM enhances service management by facilitating the shift from reactive (meeting needs when they occur) to proactive (predicting and preventing issues from happening in the first place). There are three key ways AISM can do this:

  • Guidance – The end user has a need and AISM uses a connection with endpoint tools to identify and make suggestions based on that need.
  • Learning – Building a knowledge base used to be a hassle. Not with AISM. Thanks to machine learning and AI tracking systems, the knowledge base can naturally grow based on issues encountered over time.
  • Strategy – AISM is capable of identifying and recommending both changes to existing core services as well as new innovations to improve for the future.


As you can see, AISM follows many of the same principles, processes and best practices of ITSM. It’s just faster and more accurate. And with AI being leveraged to intelligently automate complex tasks at just about every operations level, IT professionals will be freed up to spend more time innovating and evolving to help achieve business goals.

Buckle up folks, because AISM is poised to be a true game-changer.

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7 Steps for Getting Started with AIOps


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




What is AIOps




How to Get Started with AIOps

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


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


Step 3: Work on developing and demonstrating your proficiency.


Step 4: Don’t be afraid to experiment.


Step 5: Expand your vision beyond the IT department.




Step 7: Consider build-vs-buy.





Making the Case for Artificial Intelligence in Your Organization

Recent statistics published in Forbes revealed that while 82% of IT and business decision makers agree that company-wide strategies to invest in AI-driven technologies would offer significant competitive advantages, only 29% said their companies have those strategies in place.

Why such a big divide? In many situations, it’s a simple lack of buy-in. In fact, Forbes Insights research also revealed that while 45% of IT stakeholders express “extreme urgency” regarding the application of AI within their organizations, only 29% see that same sense of urgency among their C-suite. Among the board of directors, that percentage drops down to just 10%.

Leaders who want to reap these benefits and advance AI within their organizations must overcome these odds by making a strong, solid business case around how artificial intelligence will deliver in terms of business benefits, such as operational efficiency, competitive advantage and revenue growth. Here are a few recommendations on how to accomplish this goal.

Illustrate success through real-life case studies.

There’s nothing more powerfully persuasive than a real-life story. C-suite executives and board members don’t want to hear about hypotheticals. They want to see numbers – quantifiable proof of ROI – before they’ll be willing to sign on the dotted line and invest in AI. After all, it’s pretty hard to argue against benefits like lowered costs, improved service levels and other key business advantages.

Demonstrate AI’s decision-making support.

One of the hardest parts of an executive’s job is making critical business decisions. If you can show them how artificial intelligence can address and resolve this major pain point, you’ll make believers out of even the biggest skeptics. Simply put, AI provides the ability to digest, process and analyze data to unlock invaluable insight and boosting confidence through data-driven decision support.

Position AI as the cornerstone to successful digital transformation.

These days, everybody’s talking about digital transformation. In fact, it’s widely believed that moving to digital operations and offering digital services will be absolutely essential in order to remain competitive in the modern economy. If you can position AI as the catalyst for making this happen, you’ll get emphatic yesses across the board. And since analytics is the core to what drives digital experiences, the connection to AI shouldn’t be too difficult.

Link AI with the power to innovate.

40% of IT leaders list driving innovation and implementing new tech as one of their top concerns. In today’s rapidly changing landscape, staying in-step is no longer enough. To remain competitive and achieve sustainable success, organizations must find a way to stay a few steps ahead. Easier said than done? Not when you have artificial intelligence in your corner. AI offers business leaders the opportunity to garner engagement from all levels of the organization, creating a truly collaborative environment where ideation and innovation thrive.

Reinforce the power of AI for optimizing client experience.

In business, you’re only successful if your customers are happy. Leveraging machine learning and artificial intelligence can help businesses to become far more responsive to their clients, ultimately delivering a better experience overall. And it’s a win-win, because not only do customers receive a higher level of service, but because AI frees up employees to focus more on high-value initiatives, the organization benefits from greater productivity. Happier clients + more efficiency = a better bottom line.  

It’s important to point out that AI, just as with any technology, shouldn’t just be implemented for the sake of it. It should be leveraged because it’s the best and most effective solution to a specific business problem or opportunity. When presenting your case, be sure to tie the technology and its capabilities directly to these problems and/or opportunities, and demonstrate exactly who will benefit and how. This will make your case far more compelling and improve your chances of success.

Want to really wow those key decision-makers? Download your free trial of Ayehu, and you’ll have a full 30 days to create a use case of your own that will demonstrate quantifiable ROI within your own organization. Click here to get started!


3 Ways Virtual Assistants are Transforming the Service Desk

A few years ago, the chatbot phenomenon swept the consumer world. Today, people are becoming more and more at ease using conversational AI and virtual assistants to do everything from set their doctor appointments to planning travel. Yet, despite this consumer-driven craze, one area that seems to have been left largely in the dark is the IT help desk. Surprisingly (and frustratingly) enough, for many organizations, even something as basic as requesting more storage and resetting your password still requires opening and waiting for a ticket to be serviced.

The truth is, what once began as an innovative service to help employees has somehow evolved into more of a costly distraction. Budget-conscious executives have come to view the IT service desk, not as a core component of the business, but as an expensive necessity. As such, the help desk has long been the target of cost-cutting reductions. Yet, despite these efforts, one recent report indicates that the expenses surrounding service desks are actually on the rise. Today, a typical help desk is massively overloaded and majorly underfunded.

Enter the virtual assistant. Unlike the many other “solutions” CIOs tried in the past, chatbot technology has the potential to dramatically disrupt and ultimately transform the modern service desk in a way that is both positive and sustainable. This will happen in three distinct ways, as follows.

Automating the humdrum.

According to Gartner, password resets account for 40% of all service desk requests. In this way, help desk support agents can feel like mere robots, repeatedly responding to the same requests over and over (and over) again. Why not transition these mundane, repetitive tasks to actual robots? AI-driven virtual assistants can handle everything from simple tasks to complex workflows. This frees up human agents to focus on higher-level initiatives.

The best part? Chatbots are available 24 hours a day, 7 days a week, 365 days a year. They work weekends and holidays and they don’t require overtime. This means not only can you offer round-the-clock support, but scaling to higher volumes will not require an increase in headcount. The tremendous value this promises has led many large, global enterprises to begin deploying virtual assistants.

Removing the human from intuitive tasks.

Under normal circumstances, a typical service order can take more than a full business day to resolve. This process generally includes several interactions between support analysts and often requires escalation to subject matter experts. Next generation chatbot technology is now capable of using historical interactions – such as voice transcripts, prior transactions and other preexisting data – to learn, engage, suggest and recommend resolutions. Even complex troubleshooting can be handled almost, if not entirely by virtual assistants.

Revamping the user experience.

The IT industry has spent a fortune in an attempt to improve employee self-service. Yesterday’s setup was centered on the creation and maintenance of an institutional knowledge base where users could log in and search for answers to their questions in lieu of opening a help desk ticket. The results of these queries were often mixed. Today, thanks to advances in artificial intelligence technology, a user can type, text or even speak their question and a virtual assistant can engage in a meaningful exchange to resolve the issue.

Despite getting off to a markedly slow start, large enterprises around the globe are beginning to recognize the value that conversational AI brings to the table. As such, we are seeing a rapidly growing number of organizations “hiring” virtual assistants to help transform their service desks into the highly effective, cost-efficient and innovative business benefits they’ve always dreamed of being.

Get started with virtual assistant technology and see how it can revolutionize your help desk by downloading your free 30 day trial of Ayehu today.