Posts

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

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

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

Cross-Industry Infiltration of Machine Learning

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

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

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

Increasing Use of Chatbots

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

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

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

Deepening Interactions between Humans and Machines

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

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

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

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

Want to experience the power of AI and machine learning for yourself?Start your free 30 day trial of Ayehu today!

Free eBook! Get Your Own Copy Today

How to Successfully Implement a Chatbot Strategy in 5 Steps

Chatbot technology is disrupting almost every industry, with everyone from Verizon and Capital One to NASA jumping onboard. But while artificial intelligent is certainly not a new concept, developing and implementing chatbots in a practical and profitable way is still in its relative infancy. Unlike other, more established technologies, there aren’t necessarily any real standards for using bots. Thankfully, there are things we can learn from those already paving the way. Here are five real-world tips to help your company bring a chatbot strategy to fruition.

Identify audience and need.

For bots to produce ROI, they must solve a specific problem (or set of problems) and/or deliver real, measurable improvement (such as with staff efficiency or productivity). As such, the initial phase of your chatbot strategy should involve identifying who you are trying to help and exactly why. The narrower you can get with this step, the better the outcome. Keep in mind you may have multiple iterations of the same engine, based on the user you are targeting.

Select a platform.

Once you have a clearer picture of your target user and target problem, the next step should involve choosing a platform through which the bots will be built and managed. This is the phase of the project that can overwhelm some decision makers. The good news is, there are platforms (like Ayehu) that are so easy to use and quick to implement that you can be up and running in mere minutes – no coding or scripting required. Even if you have a highly talented IT team, this would be the best case scenario.

Define your measure(s) of success.

One of the biggest challenges of chatbots (and artificial intelligence in general) is proving financial value. The easiest and most straightforward way to approach this is to determine as early as possible which metrics matter the most. What type of ROI do those in the C-suite and/or other stakeholders expect out of this initiative? Bear in mind, also, that some measures of success aren’t as easy to quantify, but are just as – if not more – important, such as end-user engagement levels.

Start fast – don’t wait for perfection.

Many people make the mistake of trying to make things perfect before rolling out their project. Instead, the focus should be on building fast and executing fast, even if that involves some degree of failure in the process. Take, for instance, NASA, which approaches each chatbot initiative as a small startup with the goal of launching as quickly as possible. If you cannot iterate that fast, optimize the process as much as possible. For example, while Verizon was developing their Mix and Match bot, the consumer plan was being developed simultaneously. This made the actual rollout more seamless and successful.

Adjust and learn continuously.

A chatbot strategy isn’t something you set and forget. There is also the need for continuous adaptations and ongoing training to consider. Artificial intelligence is a fluid technology, which means your bots should continue to learn and improve over time. There will almost always be something to add, whether it’s a new term or a tweak in “personality” to better serve end-users. The main thing to remember is that chatbot development is an ongoing process and must be treated as such if it is to be successful.

Want to give our intelligent automation a test drive? Try it free for 30 days. Click here to launch your trial today.

Free eBook! Get Your Own Copy Today

The Human Element of AI Implementation

The benefits of artificial intelligence for business are widely acknowledged and understood. So, why are so many organizations still holding back when it comes to adoption? While it may seem logical to blame technical issues for the holdup, in reality what’s standing in the way is far more likely to be human in nature, whether it’s uncooperative employees, confusion over what AI means, unrealistic expectations of executives or something else. The key to navigating these roadblocks is addressing this human element.

Coming Down to Earth

Surprisingly, one of the biggest misconceptions people have about artificial intelligence is that it can solve any problem the business is experiencing. Have an issue? Just throw some intelligent automation at it. But the truth is, as amazing as the technology is, AI simply cannot fix everything. It’s essential that this message is clearly communicated and sufficiently understood. To set more realistic expectations, begin with a specific business objective and then determine holistically how you’re going to align everything to accomplish that goal.

Network to Gain Buy-In

If the human issue you’re struggling to overcome is resistance, networking can do wonders (and no, we’re not talking about computer networking). Once you’ve identified a good problem to solve, work on developing a few proof of concepts and then begin socializing with those throughout the organization. This can raise the level of awareness and help people gain a clearer understanding of what AI is, how it works and what it can help them accomplish. Identifying early adopters and internal champions is also important. These individuals can help explain artificial intelligence in a language that others understand.

Combat Fear of Change

Innovative tech solutions – especially as they relate to automation – are typically marketed on the premise that they’ll streamline efficiency and cut costs. But from an end-user’s perspective, AI can feel like a looming threat ready to inch them out of a job. Will intelligent automation eliminate some jobs? Of course. But that doesn’t mean those human resources can’t still be retained through more strategic allocation. If fear of change is hindering adoption of AI, repurpose your message to present it as a solution that will make their lives better, whether that be reducing their day-to-day drudgery or giving them an opportunity to focus their talents on more meaningful work.

Ultimately, the best strategy for successful AI implementation is to align your systems, process and people. Without the latter part of the equation, you simply will not achieve complete success. By recognizing and addressing the human element, adoption should be smooth sailing.

If you’re interested in starting small and experiencing the quick and measurable wins of intelligent automation, good news! We’re now offering a free 30-day trial of Ayehu. Give our fully functional platform a test drive today!

New Call-to-action

How IT Service Management Can Be Transformed With Intelligent Chatbots

In today’s digital landscape, organizations are facing increasing demands to do more with less, keeping expenditure at a minimum and efficient output at a maximum. In response, more and more enterprises are turning to artificial intelligence to bridge the gap. In fact, a recent report by Oracle revealed that 80% of brands either already use or plan to implement AI — specifically chatbot technology — to better serve customers by the year 2020.

But what about internal customers? Couldn’t they, too, benefit from chatbots? The fact is that the IT help desk has become an indispensable component of business success. With increasing pressures to cut costs and a growing demand to drive efficiency, however, IT technicians and administrators often find themselves struggling to keep their heads above water. As a result, delays and bottlenecks impact end-user productivity, and IT talent is wasted.

I believe that intelligent chatbots have the potential to revolutionize the way the service desk is run, transforming inefficient, manual-laden workflows into a streamlined, self-driving operation.

What Are Chatbots?

Chatbots are essentially computer programs that are powered by artificial intelligence and machine learning technology to facilitate automated, digital conversations with people. If you’ve ever used the online chat feature of a website, it’s highly likely that you were interacting with a bot – and chances are, your issue was resolved entirely without the need for any human intervention.

Intelligent chatbots are capable of understanding language, both written as well as spoken, and contextually interpreting that information to a significant degree in order to produce an appropriate response. In addition to pre-programmed data, intelligent bots also have the ability to extract data from various sources, such as wikis, best practices and user guides to help end users resolve issues quickly without having to open help desk tickets.

The Role Of Chatbots In IT Service Management (ITSM)

Some experts estimate that anywhere from 30% to 50% of all Level 1 help desk support functions are repetitive in nature (password resets, anyone?). Not only are these tasks time consuming and monotonous, but they are also quite costly from a human resource perspective.

Paying skilled IT personnel to perform laborious elemental work day in and day out isn’t just a waste of money. It’s a waste of talent. And when the work isn’t meaningful, the risk of employee turnover also goes up.

Meanwhile, from an end-user perspective, sending help desk tickets and waiting for responses impedes productivity. So, not only are IT agents bogged down by tedious requests, but the entire workforce can potentially be impacted.

A Better End-User Experience

Introducing chatbots into the IT service management process enables organizations to shift the regular and repetitive tasks and workflows away from human agents and toward AI-powered software. Intelligent bots are capable of answering simple user inquiries, troubleshooting issues and providing self-service remediation options. When an end user has a problem that they need IT’s assistance to solve, they can get their answer or resolution via a quick chat using a conversational electronic interface — just as customers do when using a live chat.

As a result, end users no longer have to wait for resolution. In fact, in many cases, employees can be empowered to use self-service options to resolve issues entirely on their own.

Cutting Costs

Simply requests like password resets are time-consuming and costly. Consider the time it takes for the end user to get locked out, open a ticket to the help desk and wait, as well as the time it takes the IT agent to manually process the request. Surely there are better ways for talented IT professionals to spend their time and energy.

Shifting simple but essential tasks like this from human to chatbot can save tremendously, both in time and in end-user productivity levels. And this is just one example. Take into account the aforementioned 30% to 50% of other repetitive Level 1 help desk functions, and you’ve got something you can really take to the bank.

Finally, though equally as important, introducing intelligent chatbots into the service desk system can take much of the pressure off of IT personnel. Enter artificial intelligence and machine learning, which, according to Gartner, Inc., will free up to 30% of support capacity for IT service desksby the year 2019. Rather than wasting time and energy on mundane, tiresome tasks, IT workers can use their creativity and cognitive abilities to perform work that interests and challenges them.

Getting Started With AI And Chatbots

If your organization decides to invest in chatbots, maximize your investment by looking for quick wins that solve specific ITSM issues, or tasks that can be automatically performed by a bot. These are typically relatively easy to automate but will produce a fast and measurable return on investment.

A good place to start is with a simple IT service desk chatbot that can create and assign tickets, escalate tickets to real agents, assist end users with questions and provide important updates on critical incident IT and security.

Intelligent bots can take that a step further. In my experience, here are a few good places to start:

• Ticket handling: Categorization, prioritization and assignment of tickets.

• Level 0 support: Leveraging artificial intelligence to provide 24/7, self-service support.

• AIOps: Use of advanced analytics technologies to proactively detect, diagnose and address problems.

• Decision support: Utilization of the predictive capabilities of machine learning algorithms to make better, more data-driven decisions.

Simply put, intelligent bots have the potential to supercharge the IT help desk, skyrocketing the productivity of both the support agents and the end users. This ultimately results in greater efficiency, lower operational costs, improved retention and the opportunity to innovate at a much faster rate. And in today’s digital age, this is what will separate the success stories from the failures.

This article was originally published in Forbes Technology Council. To see the original publication, click here.

Free eBook! Get Your Own Copy Today

Have you fallen for these 3 common AI misconceptions?

Artificial intelligence has been around for decades, though it just recently became a hot topic in the business world. During this time, many individuals have confused AI with automation, sometimes going as far as using the two terms interchangeably. The reality is, while the general concept may be similar, the two are distinctly different. Furthermore, this confusion has led to a number of other myths and misconceptions. We’d like to clarify a few things, beginning with the difference between AI and automation.

IT process automation involves programming technology to perform routine, manual tasks based on a prescribed set of instructions. Artificial intelligence takes this concept several steps further by using intelligent machines which are capable of displaying human behavior, thought and decision processes. Where automation is essentially set in stone (unless manually modified), an AI machine increases its own intelligence and can adapt its actions automatically, based on information it receives.

From a business perspective, artificial intelligence has the power to help organizations make more informed decisions. It can extract valuable information from mountains of data, analyze and organize it in a logical manner and essentially close the gap between insight and action. Given its complexity, however, AI is still often viewed in a negative light. To change this, we’d like to dispel three of the most common misconceptions as follows.

Artificial intelligence is a distant dream.

Many people believe that AI is a technology that won’t be readily available and practically applied until many years into the future. The truth is, widespread adoption of AI, both in our professional and personal lives, is much closer to becoming a reality than you may think. In fact, given that so many organizations across all industries and around the world are already employing automation to some degree, the idea that AI could be worked into the mix isn’t all that far-fetched.

Artificial intelligence isn’t really going to make that much of an impact.

The idea that AI is somehow inapplicable in the business world stems largely from the technologies complexity. People tend to discount things they have difficulty understanding. The reality is that AI is not only practical for business use, but it’s incredibly beneficial. The machine learning component of AI means that computers will have the ability to learn without the need for programming. It also has the capability of mining and analyzing big data to extract valuable insights which can then be put into action to achieve better results. These are things every organization can benefit from.

Artificial intelligence is going to eliminate the need for human workers.

While it’s certainly true that AI will make human workers redundant to some degree (think routine, repetitive tasks like reporting and data entry), this technology will not fully replace humans. This is particularly true in certain fields that require high-touch interactions, like HR, health care and consulting.

Likewise, while intelligent automation will streamline and optimize operations for many organizations, it cannot and will not replace the need for the development and nurturing of customer relationships. AI can, however, leverage data to provide human workers with the insight they need to deliver better, more personalized service.

And because implementing and managing new technology will always require some degree of human input, new roles and responsibilities will naturally evolve, which means that for many, AI will present great opportunities.

Like it or not, AI isn’t going anywhere. In fact, 61% of businesses are already implementing artificial intelligence to some degree. By addressing and overcoming the biggest misconceptions about AI, companies can harness the power of intelligent automation to streamline operations and provide competitive advantage.

Want to see AI in action? Click here to request a demo. Or better yet, claim your free 30-day trial today!

New Call-to-action

Have you fallen for these AI myths?

artificial intelligence AI mythsArtificial intelligence has been around for decades, though it just recently became a hot topic in the business world. During this time, many individuals have confused AI with automation, sometimes going as far as using the two terms interchangeably. The reality is, while the general concept may be similar, the two are distinctly different. Furthermore, this confusion has led to a number of other myths and misconceptions. We’d like to clarify a few things, beginning with the difference between AI and automation.

Intelligent automation involves programming technology to perform routine, manual tasks based on a prescribed set of instructions. Artificial intelligence takes this concept several steps further by using intelligent machines which are capable of displaying human behavior, thought and decision processes. Where automation is essentially set in stone (unless manually modified), an AI machine increases its own intelligence and can adapt its actions automatically, based on information it receives.

From a business perspective, artificial intelligence has the power to help organizations make more informed decisions. It can extract valuable information from mountains of data, analyze and organize it in a logical manner and essentially close the gap between insight and action. Given its complexity, however, AI is still often viewed in a negative light. To change this, we’d like to dispel three of the most common misconceptions as follows.

Artificial intelligence is a distant dream.

Many people believe that AI is a technology that won’t be readily available and practically applied until many years into the future. The truth is, widespread adoption of AI, both in our professional and personal lives, is much closer to becoming a reality than you may think. In fact, given that so many organizations across all industries and around the world are already employing automation to some degree, the idea that AI could be worked into the mix isn’t all that far-fetched.

Artificial intelligence isn’t really going to make that much of an impact.

The idea that AI is somehow inapplicable in the business world stems largely from the technologies complexity. People tend to discount things they have difficulty understanding. The reality is that AI is not only practical for business use, but it’s incredibly beneficial. The machine learning component of AI means that computers will have the ability to learn without the need for programming. It also has the capability of mining and analyzing big data to extract valuable insights which can then be put into action to achieve better results. These are things every organization can benefit from.

Artificial intelligence is going to eliminate the need for human workers.

While it’s certainly true that AI will make human workers redundant to some degree (think routine, repetitive tasks like reporting and data entry), this technology will not fully replace humans. This is particularly true in certain fields that require high-touch interactions, like HR, health care and consulting.

Likewise, while intelligent automation will streamline and optimize operations for many organizations, it cannot and will not replace the need for the development and nurturing of customer relationships. AI can, however, leverage data to provide human workers with the insight they need to deliver better, more personalized service.

And because implementing and managing new technology will always require some degree of human input, new roles and responsibilities will naturally evolve, which means that for many, AI will present great opportunities.

Like it or not, AI isn’t going anywhere. In fact, according to IDC research, worldwide spending on artificial intelligence is expected to reach $19.1 billion this year – an increase of more than 54% over last year. By addressing and overcoming the biggest misconceptions about AI, companies can harness the power of intelligent automation to streamline operations and provide competitive advantage.

Want to see AI in action? Click here to request a demo.

Free eBook! Get Your Own Copy Today

5 Ways the Service Desk can Use Chatbots

Pull up any IT related website and you’ll undoubtedly see dozens of headlines dedicated to artificial intelligence, machine learning and chatbots. Some of what’s being published relates to the threat of job replacement. And while that’s certainly true to some degree, AI isn’t something to fear – even for those who work in IT support. To the contrary, the service desk is ripe with opportunity to leverage chatbots to benefit both the end user as well as the support team. Let’s take a look at a few ways this technology can be used in tandem with the service desk.

Human Resource Optimization

Whether it’s resource planning or the redirection of work away from the service desk, AI can be used to make smarter use out of service desk personnel. For instance, machine learning algorithms are capable of analyzing patterns to predict future workload and plan staffing needs accordingly. Routine IT support tasks, such as password resets and remote restarts, can be shifted to chatbots, essentially supplementing (not replacing) help desk workers.

Improved Decision-Making

Decision support is another powerful way AI technology can aid the help desk. From low level automation of workflows to the prediction of future trends in the IT service realm, such as the demand for new or different IT services, the sky is really the limit with how this can be applied. Predictive analytics can even be used to forecast future customer satisfaction levels based on the impact of various factors that occurred in the past.

Self-Service IT Support

There are many different use cases, including intelligent search, through which machine learning algorithms apply meaning and context and draw from previous search successes to deliver more accurate search results. Intelligent autoresponders can provide automated resolution to service tickets without the need for human intervention. And, of course, the use of chatbots to provide a more engaging IT support interface using artificial intelligence and automated solutions. This not only takes much of the heat off of busy IT professionals, but it also empowers end-users and boosts productivity.

Proactive Service Improvement

In addition to identifying and addressing common IT problems that are occurring presently, predictive analytics can also be utilized to project possible high-impact issues that may occur in the future but have not yet been realized. This enables IT support staff to take proactive measures in reducing the risks of those possible future issues, often stopping them before they occur. And thanks to the technology’s advanced learning capabilities, it can improve on its own, getting better over time.

Improved Customer Experience

Each of the four points above contribute to a better customer – or in this case, end-user – experience. From better solutions to faster, more efficient support to self-service options (including chatbots and autoresponders) to proactive problem resolution and more. AI will undoubtedly continue to play a critical role in IT support’s customer experience journey, improving as time goes on.

These are, of course, just a handful of the many ways the service desk can leverage AI technology. There will be many other opportunities to use chatbots in the not-so-distant future. The most important thing to note is that artificial intelligence technology is already here and those in IT support that are currently using it will remain a step ahead of the competition.

Don’t get left behind. Schedule a free product demo of Ayehu today and learn how you can leverage chatbots to bring your service desk to the next level!

Free eBook! Get Your Own Copy Today

Innovation without Breaking the Bank. Yes, it’s Possible.

Innovation without Breaking the Bank. Yes, it’s Possible.In a recent survey conducted by IDC, 45% of CIOs and senior IT executives stated that one of their top three objectives is to “create competitive advantage for the business.” Today’s IT leaders are, perhaps more than ever before, being asked to deliver more. More reliability. Faster responsiveness. Greater flexibility. They are expected to leverage digital transformation to create disruption. And they are expected to do all of this while keeping financial impact at a minimum.

These IT leaders find themselves facing quite the challenge: finding a way to continuously innovate in the face of increasing budgetary restraints. The good news is, with the right strategy, this is – indeed – possible. Here’s how.

Leverage Your Data

Today’s forward-thinking organizations are increasingly driving business value and seeking to achieve competitive advantage through deeper data insights. This enables business leaders to uncover hidden value in existing services or products. With the right approach, innovation doesn’t have to be expensive. Simply prioritize the results of data discovery in order of those initiatives that require minimal risk and investment but have the potential for high returns.

Ultimately, the key to innovation lies in having a data-oriented mindset. Initiatives that focus on reducing costs and streamlining processes can be successful, but only when the right data is being used the right way to facilitate better decision-making. The ability to rapidly execute on those findings is also important.

Review Risks and Seek Out Greater Efficiency

Another critical key to cost-effective innovation is risk analysis and efficiency planning. Review the risks the business has and assess the impact and likelihood those risks may have on customers and operations. From there, you can prioritize and monetize, making more informed decisions about which areas budget cuts can be made while still meeting business needs.

Budget cuts enable business leaders to focus their efforts on maximizing efficiency. Establishing leaner teams, optimizing process management and improving the effectiveness of certain key elements, such as data storage, can all result in a better product or service at a lower cost. And, of course, adoption of technologies, such as intelligent automation (which we touch on in greater detail below), to help streamline processes and maximize efficiency.

Optimize, Optimize and Optimize Some More

The most innovative organizations – especially those on tight budgets – make a concerted effort to continuously optimize ongoing operations and costs. It’s never a “set it and forget it” kind of thing. It’s a never-ending battle – one for which technology can provide a leg up.

IT leaders must take advantage of targeted applications and cloud opportunities to extend and enhance their core capabilities. By leveraging the power of tools like artificial intelligence and machine learning, operations can be fully optimized. Not only does this create a more productive, efficient work environment, but it also frees up human workers to apply their creative, cognitive skills toward innovative business initiatives.

According to Gartner, 90% of the IT budget is currently consumed by the support of legacy systems. These costs can be dramatically lowered through IT optimization. Adopting the right technologies – preferably ones that seamlessly integrate with legacy systems – can reduce expenditure, improve customer service and provide distinct competitive advantage. At the end of the day, innovation takes funding and resources. IT optimization can free up both.

Looking for a platform that can bring your legacy systems together, improve efficiency and help you harness the power of data for better decision-making support? Ayehu offers all of this and more. Experience it for yourself. Request a live demo today and get your organization on the path to affordable innovation.

Free eBook! Get Your Own Copy Today

Human Learning vs. Machine Learning – What’s the Difference

These days, artificial intelligence is all around us. If you’ve ever used Siri on your iPhone or the live chat feature of a website, you’ve interacted with AI. From a business perspective, the rise of AI can be both exciting and challenging. Furthermore, it’s a concept that isn’t necessarily easy for everyone to grasp. The most common question being asked by individuals who aren’t deeply involved with tech is, “What, exactly, is artificial intelligence?” Perhaps the easiest way to understand AI is to compare it to something that is already widely understood – human intelligence.

How Does Human Intelligence Work?

Generally speaking, human intelligence follows a simple, straightforward and typically predictable pattern. We gather information. We process that information. And we use that processed information to decide what to do next. These three basic steps can be summed up as follows:

Input —> Processing —> Output

Input occurs through sensing and perceiving the things all around us. The senses – eyes, ears, nose, etc. – gather raw input, such as the sight of light or the scent of a flower. The brain then processes that information and uses it to determine what action to take. In the processing stage, knowledge is formed, memories are retrieved, and inferences and decisions are made. Output then occurs in action based on the information processed. For instance, you might hear a siren, see an ambulance in your rear view mirror and subsequently decide to pull over to let it pass.

In order to safely navigate the world in which we live, we must effectively process all of the input we receive. This basic concept is the core of human intelligence, which can further be broken down into three definitive segments:

Knowledge/Memory

People gain knowledge through the ingestion of facts (i.e. the Pilgrims landed in 1620) as well as social norms (i.e. saying “Please” or “Excuse me”). Further, memory allows us to recall information from the past and apply it to present situations.

Inference/Decision

Inferences and decisions are made based on the raw input we receive, combined with our memories and/or built up knowledge. For instance, let’s say you tried a new food a few months ago that turned out to be way too spicy for your taste. The next time you’re offered that food, you politely decline.

Learning

There are a number of ways humans can learn, including observation, example and algorithm. With observation, we determine the outcome on our own. With example, we are told the outcome. Learning by algorithm, on the other hand, allows us to complete a task by following a series of steps. A good example of this would be solving a long division problem.

Human Learning vs. Machine Learninghuman learning vs. machine learning

The main aspects of human intelligence are actually quite similar to artificial intelligence. In the same way that humans gather information, process it and determine an output, machines can do this as well.

Of course, because machines do not have physical senses like people do, the way they gather input differs. For instance, rather than sight or smell, artificial intelligence gathers information through things like speech recognition, visual recognition and other data sources. Think about how a self-driving vehicle can sense obstacles in the roadway or how your Amazon Echo listens and recognizes your voice.

The processing piece of the formula also mimics how human intelligence works. Similar to the way people accrue memories and build knowledge, machines are capable of creating representations of knowledge and databases where information is stored. And, just as people draw inferences and make decisions, machines can predict, optimize and determine what the best ‘next steps’ should be in order to accomplish a particular goal.

Similarly, just as humans learn by either observation, example or algorithm, machines can also be “taught.” For instance, supervised machine learning is akin to learning by example: the computer is provided with a data set containing labels that act as answers. Over time the machine can essentially “learn” to differentiate between those labels to produce the correct outcome.

Unsupervised machine learning is like learning by observation. The computer recognizes and identifies certain patterns and subsequently learns how to distinguish groups and patterns on its own. Lastly, learning by algorithm is the process by which a programmer “instructs” the computer precisely what to do, line by line, using a software program. Ideally, the most effective form of artificial intelligence will utilize a combination of the above learning methods.

The output that results sums up how machines interact with the world around them, whether it’s speech generation, navigation, robotics, etc.

Take, for example, the business use case of cybersecurity threat detection. Artificial intelligence can scan enormous amounts of data and monitor an entire infrastructure in real-time. It can then, through a combination of unsupervised and algorithmic learning, pinpoint anomalies that could potentially represent data breaches. It can then use that information to investigate and test, automatically determining what the next steps should be, whether it’s escalation to a human agent or automatic remediation.

The Future is Now

We have, undoubtedly, only seen the tip of the iceberg as it relates to artificial intelligence and its potential impact on our lives – both personal and professional. As technology continues to evolve and improve at a breakneck speed, AI and machine learning capabilities will also evolve. Why wait? Get ahead of the curve and experience the next generation of automation and AI by taking Ayehu for a test drive today.

Free eBook! Get Your Own Copy Today

How Intelligent Process Automation is Revolutionizing the Financial Field

How Intelligent Process Automation is Revolutionizing the Financial FieldJust as robots have been performing routine, repetitive tasks on the floors of factories for decades, that same concept is now being applied to the financial industry with tremendous results. Intelligent process automation (IPA), powered by AI and machine learning technologies, promises to revolutionize how financial organizations operate, maximizing efficiency, cutting costs and ensuring optimal service levels.

This advanced technology has the potential to transform just about every area of the finance function. In particular, IPA will enable finance professionals to make the critical shift from transactional to strategic.

When rote, manual tasks are automated, skilled finance experts will spend less of their time running reports and performing provisional data analyses. Instead, they will be able to quickly and easily gather and analyze the essential data they need to enhance performance and deliver better support. No longer bogged down with busy-work, these experts will have the time to engage with other lines of business and deliver the forward-thinking guidance that leadership needs to pursue new opportunities.

Let’s take a look at a few real-life examples of how intelligent process automation can be applied in financial institutions.

Account Reconciliations

A good portion of today’s accounting teams spend far too much time performing manual reconciliations across a variety of systems. At the enterprise level, this can involve thousands or tens of thousands of individual transactions across multiple systems, both internal and external.

In reality, many of the mismatches found in reconciliations actually follow similar patterns. For instance, an entry was made twice in error or someone accidentally keyed in a negative sign instead of a positive. Intelligent process automation is capable of not only recognizing these patterns, but also identifying the issue at hand and correcting it. In many cases, this can be done without the need for any human input.

Some estimates indicate that up to 80% of these simple reconciliation tasks can be automated, freeing up skilled staff to focus their efforts on the smaller percentage that are more complex or require human judgment.

Closings

For most corporations, the end of the month or quarter is a stressful time that requires all hands on deck to handle the financial close. This process typically involves a number of different systems, multiple finance teams and several lines of business, there are a multitude of dependencies that require tracking and management. For instance, certain accounts cannot be closed until all related sub-accounts are closed by the subsidiaries.

Intelligent process automation can alleviate much of this complexity by:

  • Automatically tracking the status of completed tasks across multiple systems
  • Automatically initiating close processes upon completion of dependent tasks
  • Updating the close calendar to provide visibility into the status of the financial close process

Financial Planning & Analysis

FP&A is another complex but necessary process eating up a significant portion of time, particularly for senior executives. It involves creating and approving budgets, analyzing spend, managing those budgets, etc. With IPA, routine budget requests that follow a common pattern don’t need to be signed off on. Instead, only unfamiliar or unusual requests will require review and approval.

Prior to submitting a request for executive approval, the intelligent process automation platform can analyze the pattern (i.e. dollar amount, similar requests that were made in the past, etc.). If it determines that similar requests received 100% approval in the past, the software can automatically process the approval without the need for human intervention. If an anomoly is detected, it can reroute to an executive for manual review.

PwC predicts that by 2020, financial services organization will begin to ramp up their AI adoption, streamlining operations and re-shoring jobs. And given the tremendous benefits intelligent process automation has to offer, it’s obvious why.

Want to position your financial organization for future success? Jump on the IPA train! Click here for a free, interactive product demo and get started on the path to digital revolution today.

IT Process Automation Survival Guide