The Role of AI in Human Resources

Author: Kim Coombs, Talent Director, EMEA at Riverbed Technology

Artificial Intelligence (AI) is improving human resources (HR), streamlining processes and empowering employees to perform better. Employee data that was once banished to the archives can now be combined with the huge volume of data running through a business’ network to identify talent gaps, learning and development initiatives and provide recommendations to HR professionals and managers.

It is becoming clear that the future success of businesses will be defined by how well they are able to optimise the combination of human and automated work.

There have been some controversial headlines surrounding automation in the workplace and earlier this year, the World Economic Forum projected that the demand for ‘unique’ human skills will grow. While its research suggests 75 million current jobs will be displaced as artificial intelligence takes over more routine aspects of work, 133 million new jobs will be created. This report concludes that skills in both emotional intelligence and technical intelligence – like technology design and programming – will be essential for the future workforce.

HR needs to help employees strengthen their core skills and capabilities through targeted training or development initiatives. On top of this, they are responsible for proactive candidate selection as part of the recruitment process, which involves an excessive amount of time, resource and admin. AI is opening up new opportunities to enhance the human experience and is expanding the remit of the HR function within a business. It is important for business leaders to consider the introduction of AI-led infrastructure as an opportunity to improve existing, outdated, and sometimes archaic processes and message the benefits of these changes down to their managers and employees.

Kim Coombs, Talent Director, EMEA at Riverbed Technology

The human experience

With the introduction of AI, businesses are positioned better than ever to improve their employees’ human experience. In the modern enterprise, AI is already beginning to streamline admin heavy tasks to free up time for employees to focus on adding value to the broader business.

For example, team leaders and middle management are often required to make the same decisions over and over again, including approving time off requests, approving timecard exceptions and scheduling staff. If you speak to managers performing these tasks, you will often find their perspective is the same: they are repetitive, time-consuming, and while relevant, deliver little value. These are precisely the tasks that AI can tackle first —  the routine, daily, difficult processes that will free up the manager to handle more strategic management matters.

With less time spent on the high touch, low value tasks, managers can be far more aligned with their employees’ needs, boosting employee wellbeing and increasing staff retention. In addition to the general alleviation of admin, AI is also making huge strides in the realms of learning and development.

 

Training talent

There is no “one size fits all” approach to learning and development. As the war on talent grows ever more competitive, organisations that can provide their employees tailored opportunities to grow will set themselves apart. Traditionally doing this has involved significant manual workforce auditing and data analysis before programmes can be put in place. However, with the latest developments in predictive and prescriptive analytics, this heavy lifting no longer falls within the remit of the HR team.

AI has the power to monitor business performance and create bespoke suggestions around talent management and recruitment. This technology feeds off data so unfortunately this is redundant if HR does not engage with the technology and embed AI into the workforce’s natural workflow. The more HR engages with the technology and nourishes it with use cases; the more mature the artificial decision making will become. Supporting use on this scale requires a significant cultural shift. Once this shift occurs, HR can begin to embrace more creative and engaging ways to implement learning and development, with actionable data points already provided for them.

 

Combined intelligence

It will be a combination of human and artificial intelligence that will ultimately drive success for the future enterprise. For an AI implementation to demonstrate its full worth, businesses need to first fully embrace digital change in every aspect of their business. Any system is only as fast as its slowest link, and the goal of using AI to free up managers to solve more substantial organisational challenges will never be achieved if manual, high-touch processes and policies remain.

Staff must be onboarded and reskilled effectively. The IT infrastructure should be able to support higher volumes of data, and senior management needs to ensure digital transformation initiatives are given adequate funding and support.

As AI alleviates admin heavy tasks, roles and responsibilities will begin to shift, enabling the workforce to add a significant layer of additional value to their business. More importantly, workers will be able to focus on tasks that are far more engaging and fulfilling. This can only be achieved if HR teams begin to adopt this technology and implement new processes to support AI adoption in the wider business. The winner in all of this will ultimately prove to be the human experience.

New ServiceNow Research Highlights What Employees Really Want

Perks at work have become a source of pride and a competitive differentiator for companies vying for top talent. Stocked fridges, catered meals, on‑site fitness facilities, laundry services and complimentary transportation are just a handful of popular perks companies offer to lure new employees. But according to new research by ServiceNow, an effective way to build an engaged and productive workforce is giving employees a better employee service experience during big moments and even small ones in between.

ServiceNow’s “The Employee Experience Imperative” Report, which studies the service experience at work, reveals that employee enthusiasm for work peaks at the start of a new job, but wanes by 22% shortly thereafter. Where are employers missing the mark? The findings tell us that employers aren’t supporting employee’s basic needs on a day‑to‑day basis during the employee lifecycle: 41% still struggle to obtain information and answers to basic questions, like finding a company policy or resolving an issue with their equipment. Furthermore, only 41% believe their employers make it easy to select their equipment before their first day and only 51% of employees believe their employers make it easy to receive equipment necessary to perform their job responsibilities at the onset of their job.

Employees today – regardless of their role or generation – want to be heard and valued, and they want an employee experience that suits their needs throughout their career with an organization,” said Pat Wadors, Chief Talent Officer at ServiceNow. “If an employee’s experience is lacking at the onset of their new job, the impact for some employees can likely be felt until the employee’s last day. By creating beautiful and meaningful experiences and an environment where work gets done efficiently, employers will benefit from a more engaged and productive workforce.”

Pat Wadors, Chief Talent Officer at ServiceNow

Where Can Employers Improve? Mobile Work Experiences

One‑third of our lives is spent at work. And, employees want their experiences at work to be more like their experiences at home – like having mobile technology at their fingertips to make finding information and accomplishing tasks simple, easy and convenient. In fact, more than half (54%) of employees expect their employers to offer mobile‑optimized tools at work. Yet, the majority (67%) report not finding it easy to complete necessary paperwork on a mobile device before their first day and only about half (52%) of employees have been allowed to use a smartphone or tablet to access employee tools from HR or other departments. However, those who do have such access self‑report higher productivity than those without these mobility tools. This is a miss for employers who haven’t yet introduced mobile self‑service to their workforce, especially for those aiming to retain and attract millennials, as over half (59%) expect employers to provide mobile‑optimized tools.

A Generation Gap? It’s Smaller at Work Than You’d Think

Baby boomers and millennials aren’t so different at work, after all. Across the four generations that comprise today’s workforce – baby boomers, Gen‑Zs, millennials and Gen‑Xs – employees want a better experience at work. The research found that, across generations and departments, employees are losing faith in their employers to deliver positive employee experiences:

• Less than half (48%) of employees believe that employers are invested in improving the employee experience;
• More than half (61%) of employees rate their employers poorly based on a negative experience with personal leave;
• Less than half (45%) of employees feel that their opinions and perspective matter to their employer. However, millennials (43%) are more optimistic that employers will address feedback when compared to baby boomers (35%);
• Only 37% of employees believe that employers automate processes to improve the worker experience; and
• Less than half (44%) of employees believe employers provide them with easy access to information from HR and other departments; the same number felt they did not have access to the information vital to their job on day one.

A positive experience at work strongly correlates high employee net promoter scores (eNPS)– meaning, employees that create great employee experiences are likely to have more loyal, satisfied employees. That’s real business value.

ServiceNow Research Assesses Impact of Digital Transformation on Employees

New research from ServiceNow, a leading enterprise cloud based provider of digital workflows, reveals employees in EMEA companies, embracing workplace automation, report greater job satisfaction (62%), customer satisfaction (71%) boosted productivity (72%) and increased time for creativity (62%). Two thirds say workplace automation improves their organisation’s financial performance and nearly half believe they benefit from job creation.

EMEA employees express that the rise in digitisation enables them to benefit from automating menial tasks, subsequently improving their opportunities for advancement (64%) and more meaningful work. Yet fewer than one in three (27%) of companies studied (27%) have automated the processes with which they work, leaving over two thirds of work processes with substantial manual activity.

Employees worry more about change than fear of machines

There has been much rhetoric around ‘fear of machines’, yet employees studied worry more about change than robots taking their jobs:

• 31% are concerned about learning new skills or processes and 28% worry about changing the way their job is performed
• Only 17% worry about losing their job
• Employees in highly digitised companies report they benefit from increased job creation (42%) as opposed to only 23% in less automated companies (23%)
• 86% view AI technologies as the future of work
• Under a fifth (16%) fear being told what to do by a machine

Employees have a desire to learn and improve digital skills

• 66% of employees have a desire to learn or improve their digital skills
• 15% say their job requires advanced digital skills
• 75% believe they have the digital skills required to perform their job well
• Only 18% find adapting to digitised work processes difficult

Increased financial success

Employees in ‘highly automated’ organisations are more likely than those with less automated processes to report that their firms have high revenue growth, exceed financial goals and are much more profitable than competitors.

• 55% of those in highly automated companies see higher profitability than their competitors, compared to only 31% in less automated companies
• In highly automated companies, 21% see ‘much higher’ profitability vs. 5% for others
• 36% of highly automated companies report that they exceeded their financial goals compared to just 16% for others

“Highly automated companies are making use of digital workflows to simplify complex tasks, respond rapidly to users’ needs and take a predictive approach to maintenance,” says Chris Pope, VP Innovation, ServiceNow. “Automation enables employees to reclaim time spent on unfulfilling tasks and refocus it on more meaningful work. The result is significantly greater efficiency, productivity and job satisfaction compared to companies with more manually-led operations.

“Activities such as resolving customer issues are critical to customer and employee satisfaction, so they should receive more focus from an automation standpoint in the future. The question businesses need to be asking now is how they can make the necessary changes to realise these benefits,” adds Pope.

Guarantee Employee Job Satisfaction with Digital Workflows

Author: Chris Pope, VP Innovation, ServiceNow

The idea that company employees discuss and share their inner musings on corporate secrets when standing around the water cooler is probably more down to the movies than it is related to any form of reality. But if people are talking at work, one of the up-and-coming topics these days is their workflow—or lack of it.

Regardless of whether people talk at the water cooler, the tea station, or while queuing for lunch, we all discuss our working life experiences with each other in an informal way. It’s a sort of supplement―or you might say antidote—to human resources. And it’s where the crux of working lives is really played out.

So, in an increasingly connected and digitized world, may I suggest that the thread of water cooler conversations might be shifting slightly? Armed with new tools to transform the way many company processes are being carried out, people may now actually start discussing the state of their digital workflows and measuring their job satisfaction as a result.

A new yardstick for job satisfaction

People are now looking at the way work really gets done inside their organization in a far more granular and analytical way. Regardless of whether or not an individual is fully aware and cognizant of the digital workflow that their role may fall into, they are probably in one, nonetheless.

What everyone will know, instinctively, is that there is a flow of work between customers, partners and other members of an organization. What we can do with digital workflows is more accurately locate areas where work can be carried out more efficiently.

More than ever before we also know that people have more choice about the technology they use every day. We’ve witnessed the rise of Bring Your Own Device (BYOD) to work and the general consumerization of IT that came with it.

These experiences should tell us that if you don’t give people the right tools, then they will go and look for them. Equally, if you don’t give people the right applications, engagement systems and wider workflow patterns, then they will instinctively go and look for them, or make them.

Unrestrained innovation in a digitally native territory

The shift to digital business brings with it new opportunities. Non-techie business people are starting to embrace so called low-code software application development platforms that allow them to build elements of app functionality that work just the way they want them to.

As these new freedoms play out in the workplace, firms need to think about the unknown factors. Unbridled and unrestrained innovation is all very well, but the problem with custom-built point solutions is that they often do one thing well, but fail to provide scope for enterprise-wide scalability or an ability to integrate across the entire organisation.

If we think about platform-level technologies, we can build that innovation factor into software that is digitally native to the cloud era and so ready for a more structured approach. Because these applications have been built in a digitally native territory, they will be able to leverage fully integrated native device capabilities, such as maps, camera, and so on.

The virtuous circle of workflows

If we hinge our business models around digital workflows that define what data lives where, then we can more easily react to change and uncover new streams of profitable operation. Digitizing workflows means we can use defined data where it has the right impact, but also channel unstructured data to the data lake.

But even the information in the data lake need not go to waste―we can apply Machine Learning (ML) to these data resources and use algorithms to find patterns in business transactions where we weren’t even looking for them to drive new business outcomes. This can be a virtuous circle because workflows can be tuned and changed based upon the new insights uncovered.

The business process you didn’t know about

The best work processes are very often the ones that you follow, but that you didn’t even know about. If we define digital workflows and build our operational models around them, then we can increase productivity and create great experiences for employees who want to work anywhere and at any time.

A lot of employees have to take actions throughout the day that move the organization forward, but often these same actions prevent them from doing high-value work. It’s time to transform old, manual ways of working into modern digital workflows, so employees and customers get what they need, when they need it.

Create a joined-up experience

Kicking off digital workflow initiatives and getting your transformation started can be a real challenge and as a result, many companies struggle to even start their efforts. First of all, we all have disjointed internal systems and processes that make it hard to connect the dots. Trying to navigate these can feel like unravelling a ball of yarn, so the more you learn, the more complicated they seem.

Once you make sense of the systems and processes, you have to figure out the myriad tools and solutions that drive these. The end result you should be aiming for is a common, workflow-driven experience layer that is consistent across the systems in your organization.

Your typical company employee might still be more likely to discuss holiday plans, managerial peeves and whether or not the associate in accounts is being a pain about expense reports, but the water cooler conversation around ‘how is your workflow?’, is coming. Are you digitally hydrated yet?

About the author

As ServiceNow’s global VP of Innovation, Chris brings more than 15 years of C-level executive experience with leading technology solutions and platforms across Product Management and Strategy. Chris also has the rare, added-value, experience of having been a ServiceNow customer multiple times so he understands the client and the vendor perspectives on business transformation. Chris’ proven track record working at and with the largest organisations globally, has seen him recognised as a thought leader in process and methodology. He holds a Bachelors of Science degree in Electronic Engineering from De Montfort University in the UK, and is a well-published author and contributor to many leading digital publications and blogs.

The Case for a More Human Approach to AI

Author: Chris Pope, VP Innovation, ServiceNow

 

Artificial Intelligence (AI) is all about machines, obviously. Except it’s not. In truth, discussions surrounding AI may often centre around how competent, intuitive and contextually aware the machine brains we are building have become.

But really, AI is all about us―the humans—and how it can make our lives better.

There was a time, perhaps even inside the current decade, when AI tools and functions were still associated with the fanciful ‘talking computers’ that featured in many 1980s movies. It wasn’t that long ago that we considered AI as something of a ‘toy’ and its application in mission-critical enterprise applications was still somewhat laughable. Of course, now we take talking computers completely seriously. So much so that we’re equally focused on the proficiency of computer speech recognition.

 

Application of AI

But as far as we have come, we still need to look at the real world use cases of AI and ask how it can help us make our lives better. If we’re not applying AI to our human work experiences to examine and analyse where it can make those experiences greater, then what are we doing here in the first place?

The truth is, many enterprises large and small have been struggling with finding the appropriate use cases for new and emerging AI technologies. Companies need to find the workflows inside their business models that can benefit from AI. Only then can they start to architect towards turning those operational throughputs into truly digital workflows.

So how do we define AI-enabled digital workflow Nirvana and how do we get there?

Typically, the process starts with a technology audit and a process of assessment, quantification and qualification running throughout the IT stack in question. Individual business units will need to step back and identify their work problems and challenges as they look for the elements of their workflows that can be digitised.

Everybody across every line of business function will be involved―we need to crowdsource and collaborate to identify strategic areas of business operations that still exist as predominantly manual, accurately measurable and fundamentally repetitive.

These are the parts of business that represent liquid gold, i.e. once we tap the seam, we can channel these functions into AI-driven services that subsequently run as digital workflows. Individuals are liberated from drudgery, productivity is increased and employees have a greater experience—a new virtuous circle is established.

 

Practical examples

Think about a typical office. When people leave the company, we need to manage who has a key fob for access to the car park. This is a perfect example of the type of job that has typically been performed manually through the use of a spreadsheet. This is time consuming, error-prone and obviously creates security issues.

But it’s also (I hope obviously) a perfect example of the type of task we can evolve to become a digital workflow driven by intelligence stemming from AI. Our analytics engine should know that an employee is leaving the firm and so reports, alerts, emails and perhaps even mobile device management, to cancel the key fob, can all happen automatically.

If we can make all those things smarter and more intuitive, then we can build better experiences faster.

Uber hasn’t actually done anything fundamental to change the way taxis work or drive. It has changed the digital workflow that governs the ability to book and pay for the service. The list of services-centric examples in this space is growing every day.

 

Automating a bad process doesn’t make it good

In the technology industry, we are often bad when it comes to decommissioning things. Think about how many business processes probably exist today that firms need to eradicate and get rid of.

There’s no point in applying AI to these aspects of the business. As we know, automating a bad process doesn’t make it a good process; it just makes it an automated bad process! So, this re-engineering is actually an opportunity to clean out your cupboard and stop doing the things that you no longer need to do.

An example that came out of a recent hackathon, we conducted, is a tool to help with filing of patents. One of our hackathon teams used AI and ML to trawl the web for all registered patents using word recognition. They wanted to identify connected words to see if a new invention already existed in some form already. This would have been costly manual work, that may have been handed over to a specialist (in this case, a patent lawyer), but now we can digitise these aspects of the business.

 

The human factor baseline

We as humans now need to engineer the existence of AI into our own mindsets and consider how it can help us work differently. This includes knowing what things we don’t need to worry about anymore. For example, we don’t take a map out with us these days, because we use a smartphone—so what else can we stop doing?

As we move down the more humanised road to AI, we will find that AI itself gets smarter as it learns our behavioural patterns, penchants and preferences. We must still be able to apply an element of human judgement where and when we want to, but that’s already part of the current development process as we learn to apply AI in balance when and where it makes sense.

The future of AI is smarter, and it is also more human. The end result is more digital at the core, but more human on the surface. If that still sounds like a paradox, then it shouldn’t. We’re at a crucial point of fusion between people and machines and it’s going to be a great experience.

 

About the Author

As ServiceNow’s global VP of Innovation, Chris brings more than 15 years of C-level executive experience with leading technology solutions and platforms across Product Management and Strategy. Chris also has the rare, added-value, experience of having been a ServiceNow customer multiple times so he understands the client and the vendor perspectives on business transformation. Chris’ proven track record working at and with the largest organisations globally, has seen him recognised as a thought leader in process and methodology. He holds a Bachelors of Science degree in Electronic Engineering from De Montfort University in the UK, and is a well-published author and contributor to many leading digital publications and blogs.

Cobots – The New Employee

Author: Chris Pope, VP Innovation, ServiceNow

 

The renaissance we are currently experiencing in Artificial Intelligence (AI), and all forms of Machine Learning (ML), has given rise to widespread discussion on how business will run in the immediate future. As the impact of AI starts to be applied to real-world use cases, we will inevitably need to get used to some new terminology. One of the technology industry’s new favorites is the notion of the ‘cobot’, short for collaborative-robot.

Cobots come in many forms. Some will be purely software-based helper robots that we might think of as sophisticated extensions of chatbots or virtual assistants. Some will more physically manifest themselves as robot arms, exoskeletons or some other form of intelligently programmed machinery. Some will be a super-smart mix of both.

 

Your intelligent new office buddy

You can think of cobots as your new office buddies and people—I do mean all of us―are going to have to get used to working alongside intelligent machines, in close proximity, very soon.

Cobot brains are composed of software-based virtual services that form the synapses of ‘thought’—we know its processing and data analytics really―that they run on. Like a Tamagotchi, they do need feeding and watering, but only in the form of software updates, exposure to new datasets and patches for security provisioning and so on.

People who find the notion of cobots unnerving should perhaps stand back and consider the fact that machines have already been looking after us in close proximity for years. Your desktop machine, tablet and smartphone are all using AI to power the spam filter algorithms that assess every email you get for its potential threat value.

If it helps you warm up to the concept, think of cobots as just one step further than a spam filter. But instead of just protecting you from a potential virus, cobots will be able to intuitively manage your work schedule, actions and business decisions, to create a better employee experience all round.

As DXC Technology’s Marc Wilkinson writes in Wired:

For businesses, the promise of AI is that [intelligent assistants] will be embedded across all aspects of the organization. Such agents will analyse data, discover patterns over time and then make decisions based on predictive analysis. The outcome? The application of AI on this level will make businesses not only more efficient, but also more profitable.

 

Behavioral responsibility

As shiny and fabulous as all this sounds, there is a responsibility factor to bear in mind here. As we start to feed data into cobot brains, we need to be able to reflect a consciousness of and appreciation for society’s acceptable behavioral norms.

This means that cobots will need to be able to assess the risk factor in terms of the judgements they give to any individual worker based on that person’s skills, background and other competencies. To do this effectively, we will need to be able to assess and measure individual workers’ skills in an even more granular and mathematical way before we start to engineer more automation of this kind into our lives.

Cobots will also need to appreciate cultural, ethical and behavioral norms for the global culture that they are applied in depending on location—and this is of course a subject in and of itself.

 

Cobots and global digital workflows

As the cobots start to take over the mundane tasks in our world, we must consider how people will now coexist in the new world of automated controls that drive digital workflows and how we actually implement these devices―be they software-based, hardware-based or both—in the workplace.

Some argue that we will now need to be able to measure an individual’s rank or score in terms of workplace competency. If we accept this methodology, then it could arguably help us find the engineering point at which we can apply cobot technology to an individual’s role.

To reference DXC’s Marc Wilkinson again, he notes that really smart cobots that run on fine-tuned ML models will be able to bring a new level of workplace personalization to our daily routines and discover where we could be doing better. He talks about ‘intelligent agents’ that are capable of interpreting emails for us to automatically schedule meetings, flag important tasks and even unsubscribe us from newsfeeds that we never open, and more.

With a cobot as your new office buddy, we can start to think about the workplace itself from a different perspective. We’re all used to open plan office seating layouts these days, but with cobots in the workplace, the software itself will be able to straddle cross-team functionality matrices that far outstrip the boundaries of the physical office itself. For example, team member actions in the UAE can be automatically reflected in plans for the UK or US offices in near real-time. The cobot doesn’t sleep, so a new global digital workflow starts to become possible.

 

A toast to cobot IPA

With cobot technology now developing fast, we will more clearly be able to understand our transition from RPA to IPA or IRPA. If Robotic Process Automation (RPA) allows us to program home heating controls, for example, based on defined patterns, then Intelligent Robotic Process Automation (IRPA, or just IPA) is one step further, where home heating controls start to program themselves for optimum usage and efficiency based upon observed patterns of use. Cobots have IRPA in their ‘DNA’ from the get-go.

We’re on the cusp of many technologies―perceived today as almost ‘toy like’, such as self-driving cars—becoming quite natural. We will think that cobots and intelligent assistants are quite standard in half a decade’s time. In the same way that you went from reading a map in the car and now automatically turning the GPS on, you get to a point where you just expect a new technology to be there…and cobots will be there.

Chris Pope, VP Innovation at ServiceNow

How Employee Corporate Email Use Can Put Your Organization at Risk

Author: Morey Haber, CTO, BeyondTrust

 

As part of onboarding, new hires typically sign an employee handbook which includes policies and guidelines for acceptable information technology usage. Within the details, are often policy restrictions regarding unacceptable usage for email. Typically, these policies state that email should only be used for official company business correspondence, and not for personal communications.

If you travel frequently for work, or are responsible for purchasing merchandise or services for your employer, is it acceptable to use your work email address, or should you use your personal email to complete the transaction?

This question, and the aftermath of your departure from an organization, can create a complicated situation and security risk that most employers are completely ignoring. And, unfortunately, they have no way to manage or mitigate the potential risk. Consider these real-life scenarios that organizations are facing today:

 

Scenario 1: Using corporate email accounts as login for travel services

An employee creates an account on an airline’s website using the corporate email address. This address is used for authentication into the service and to book flights or other travel arrangements.

Potential security implications

After their employment is finished, any notifications or future bookings for flights are tied to the suspended business email account. If your organization auto-forwards the email to a peer or a manager, then an identity theft threat vector has now been created. A co-worker now receiving the former employee’s emails can simply select “Forgot password” and own the former employee’s account. This is especially true if the account is not further protected by security questions or additional two factor authentication. If verification is tied back to the same email address, then it is game over once they have a confirmation link.

Recommendation

The most security-conscious way to handle this scenario is for an organization to enforce the use of an approved corporate travel service for booking flights, hotels, cars, etc. in lieu of allowing employees to book travel on their own and using a corporate email account. If the business permits bookings outside of a corporate service, allow and recommend individuals to use their personal email accounts for booking travel—even if they pay with a corporate credit card. After all, it is their account.

 

Scenario 2: Email address formats

Most organizations have an email address schema. Typical formats include first initial last name or first name dot last name.

Potential security implications

What happens when an employee leaves the organization and a new employee starts with the same name or initial combination? The new employee potentially receives all email of the former employee even if it not slated for them. Depending on the new employee’s role, the email may not be remotely appropriate (such as when PII and financials are involved) for them to receive. Organizations that continue to grow will have a higher statistical likelihood of overlap for names and initials.

Recommendation

Organizations should never reuse email addresses from former employees for new personnel. Consider adding numbers like “01” to the end of new email addresses to avoid this problem in the future.

 

Scenario 3: Using corporate email accounts for payment gateways

Some organizations allow for the purchase of merchandise and services through common payment platforms, like PayPal or Apple Pay. These are necessary for some employees (such as marketing team members) to perform their job functions.  However, none of these platforms should be set up with a user’s corporate email address. If they need to use a business email address, create a group or alias for these services.

Potential security implications

Just as with the air travel example in the first scenario, a personal account used for services can be leveraged against the individual if they leave and have no access to change their email address.

Recommendation

For these types of situations, it is recommended to use a dedicated account name for authentication, as opposed to an email address. This option allows the account owner to change the email address, but does present additional risk if the account is shared. Former employees using shared accounts for payment services underscore the ongoing risk of inadequate privileged access controls and the threats of shared accounts.

 

Scenario 4: Using corporate accounts for personal email

Some employees use personal email for group-based personal correspondence, such as for their children’s school.

Potential security implications

Once an employee departs the organization, the receiver of forwarded email is now potentially exposed to highly personal information, and potentially in violation of some local regulations.

Recommendation

Corporate email addresses should always remain strictly delegated to business usage—and never for personal communications. The results can present some interesting legal ramifications, especially if removal of the address from a group is not trivial.

 

Today, the boundaries of work and personal spheres continue to blend and blur—providing benefits (work flexibility, higher productivity, etc.) for both employers and employees—but not without cyber risks. Completely strict policies of corporate email usage will only introduce more risk as employee turnover occurs and our dependence on electronic communication continues.

Organizations have embraced policies like Bring Your Own Device (BYOD) for mobile device support and should consider allowing personal emails addresses for exactly the same reasons. Acceptable email usage policies need to clearly state when personal usage is acceptable, should be implemented, and when it creates unnecessary risk due to employee termination.

 

About the author:

With more than 20 years of IT industry experience and author of Privileged Attack Vectors, Mr. Haber joined BeyondTrust in 2012 as a part of the eEye Digital Security acquisition. He currently oversees BeyondTrust technology for both vulnerability and privileged access management solutions. In 2004, Mr. Haber joined eEye as the Director of Security Engineering and was responsible for strategic business discussions and vulnerability management architectures in Fortune 500 clients. Prior to eEye, he was a Development Manager for Computer Associates, Inc. (CA), responsible for new product beta cycles and named customer accounts. Mr. Haber began his career as a Reliability and Maintainability Engineer for a government contractor building flight and training simulators. He earned a Bachelors of Science in Electrical Engineering from the State University of New York at Stony Brook.

Getting ‘SMART’ About AI

Author: Paul Hardy, Chief Innovation Officer, ServiceNow

Global access to data is exploding. At the same time, our ability to categorise, classify and analyse this data is also expanding. As this new world of data unfolds, businesses are looking to create new data models―and their supporting data analytics functions—to directly and positively impact growth, profit and expansion.

But let’s go back to first principles for a moment. We know that Artificial Intelligence (AI) and Machine Learning (ML)―when correctly applied—can improve the way organisations work and operate. But do organisations know where to start as they look to create these new data models?

We―and by ‘we’ I mean you as the customers, us at ServiceNow, as well as our partners, everybody basically—need to ask where to categorise and compartmentalise processes and functions to build new digital workflows. We need to examine which aspects of the business should be most directly ‘exposed’ to AI. We also need to know what is and isn’t possible in the short, medium and long term.

In other words, we need to get smart about being smarter if we’re going to bring a new era of business forward. So, what does smart really mean in modern business terms? I think it is time to look at AI and digital workflows through the lens of SMART (Specific, Measurable, Attainable, Relevant, Time-bound) objectives.

Specificity

When we use the word ‘specific’ and demand a greater level of product or service specificity, we mean it in the most granular sense possible.

We can’t just say we need more paperclips, more salespeople, more office air conditioning or more field sales automobiles. We need to ask what kind of paperclip shape we need, what colour, what build strength and perhaps even what level of ‘clippyness’ every clip needs to exhibit.

When you are thinking about delivering AI and ML in the business you have to be really focused on what you are trying to achieve―and by that I mean, you need to be able to tie down specific use cases for each and every paperclip.

Measurability

Getting smart with new digital workflows also requires measurability. If you can’t measure it and put it in your business plan and balance sheet (a process, a service, a workflow element, anything at all) then you need to step back and ask whether you should really be doing it.

The reality is that data is often captured and not ever used. It simply falls unmeasured, and unloved, into the data lake. The real cost of this is the ‘noise’ that is created throughout the business because for one, wasted data goes crashing into the lake and secondly, there is then the splashing that occurs afterwards when users do actually realise that they have to start diving into the lake to look for the data that they might actually need in order to make work experiences better!

Attainability and relevancy

If an AI initiative is not attainable or achievable, then why has it formed a part of your current business strategy in the first place? Nowadays we can forecast how far AI will realistically be able to change any given business in real practical terms.

Similarly, if an AI business initiative is not relevant to the business and not able to exist within the context of the organisation’s current and immediate goals, then it forms no sensible part of any smart business plan.

Timeliness

Lastly, we come to timeliness. In the not so distant past, business cycles and the general approach to commercial objectives were typically annual. In this post-millennial age, firms are measuring themselves in much smaller strategic increments.

Key Performance Indicators (KPIs) and business targets used to change year-on-year. Today, they might be calibrated to change monthly, weekly or perhaps even on the basis of individual (tickets) activities relating to individual jobs.

Your next steps

The goal for any business should be to get to the point where they can use smart digital workflows to drive greater productivity, greater quality of all services and greater experiences for all employees.

We know that an increasing proportion of organisations are already examining where they can bring AI to bear and create new value in their business. We also know that many are already on that road and creating new applications and new experiences. Factors that matter most now include service quality, cost reduction, speedy delivery and the need for geographical availability for all new products and services. These are all the defining trends that should be shaping the way we develop new digital workflows that leverage AI and ML.

As vendors, we need to help businesses identify areas for improvement, not just before they start to lose profits and market share, but more significantly, before they start to actually lose contracts. There’s a new culture for predictive business strategy that we are underpinning and making possible.

Smart is smarter if it is more productive and creates greater experiences for everybody inside and outside your organisation. It’s where the smart money is, believe me.

Paul Hardy, Chief Innovation Officer, ServiceNow

The Truth About AIs Impact on Jobs

By Allan Leinwand, CTO, ServiceNow                  

According to a recent report from PwC, AI is expected to raise the global GDP, in 2030, by 14% (approximately US$15.7 trillion). That being said, AI is seen by many as being either a hero or a villain. On one hand, AI is currently driving nearly every CIO’s agenda because it intelligently automates work processes, making it possible to do things that have never been done before. But on the other, many workers are scared of the rise of AI as they believe it is rising from humble beginnings to become a villain that will steal their jobs.

The truth is that some jobs will be lost, but many more will be created. It is important to understand that fundamentally, AI is not strong at creative, interpersonal or physical work. It will be used for “decision support, not decision making.” So lets debunk a few myths.

Reduce and Simplify

As workers, we want to use automation to get our jobs done. AI will free us from having to spend long hours analyzing data and invest that time in achieving a better work-life balance.

Information technology, manufacturing, financial services and human resources will all see significant improvement and productivity gains because of AI. These industries have many repetitive tasks that can be easily automated, helping workers become more productive. For example, AI can streamline the onboarding process of a new employee. It can alert HR when background checks are completed, and aid them with the creation of benefits packages and employment contracts. It can help IT order and provision new equipment. Similarly, it can help the employee complete and send tax forms and direct deposit information to finance.

The Mundane

Workers want to move to more meaningful roles. In fact, according to the Society of Human Resource Professionals, workers, particularly Millennials, want to “create outcomes within meaningful projects and may become impatient with mundane tasks.” AI can automate the more mundane tasks allowing for new jobs to be created that are more fulfilling, strategic and meaningful. AI can help workers be more productive and efficient at their jobs, while learning new skills. In addition, AI can help workers become better organized, reducing stressors, improving productivity and overall job satisfaction.

Financial compliance is a great example of this. Until recently, the creation of expense reports and review of submitted expenses was a very manual, mundane process requiring hours and hours of review. In the cases of expense report review, only a sample of expense reports could be reviewed in order to hopefully identify some patterns of fraud in submissions. Now, not only can AI generate the invoices, but it can sort through the hundreds of expense reports, invoices and other transactions and  identify potential areas of fraud, waste and mistakes by employees, vendors and others for humans to further investigate, saving their companies billions of dollars each year.

Customer Satisfaction

The idea behind AI is to create more satisfied customers. Because workers can focus more on the interpersonal and creative parts of their jobs rather than the more mundane, they will treat customers better. In customer support cases, this will be done by employing AI to identify and provide a solution for the issue and utilizing a human who can react to nuances for interpersonal communications. Customers will develop loyalty because their needs are met and issues are resolved quicker, more efficiently and with a personal touch.

Let me give you an example. Years ago, many companies implemented phone trees to help route support calls more efficiently. All of us have been frustrated to get to the end of the menu realizing that we must press “star” in order to go back to the previous menu in order to talk to the right person. While this is automated support, it didn’t employ a combination of people and AI to do so. Rather than having to press the right button to move forward, imagine answering a few questions at the beginning of the call describing what the issue is or what you want to accomplish, and immediately being routed to the correct person (yes, person) who will help you or to the right menu telling you store hours. This will speed up support, improve loyalty and create better satisfaction for customers.

Convenience

One of the biggest benefits of AI is the convenience to customers. AI allows nearly every aspect of business to occur faster, from identifying and fixing support issues so that workers don’t have to drive into the office on weekends to fix a server, to providing more accessibility to information, services and more.

As an example, there seem to be ATMs on nearly every corner in most major cities and more bank branch locations than ever before. However, bank teller jobs have not been eliminated because of the rise of ATM machines. Yes, there may be less tellers in general, but their jobs are more valuable to customers and their employers. When one walks into a branch at a bank, there are dozens of workers providing better value-added services with shorter lines helping customers to be more satisfied with the convenient service provided. More than likely the work these employees do have higher margins, enabling them to make more money for both themselves and their local branches.

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Allan Leinwand, Chief Technology Officer, ServiceNow

In summary, while AI might result in loss of certain jobs, it is more likely that the amount of work each worker will need to complete will be reduced and simplified rather than eliminated. Employees will feel more satisfaction in what they do because they can focus less on the mundane and more on the strategic. Customer satisfaction will increase because customers will have more human interactions, faster, with people who know how to resolve issues they have. In addition, customers will have more convenience than ever before.

 

Personalize the Employee Experience by Going Digital

By: Jen Stroud, HR Evangelist and Transformation Leader, ServiceNow

You know Frequently Asked Questions (FAQs), one of the oldest and most rote tasks in the web builder’s playbook. I’m here to tell you that if you’re in Human Resources and building a knowledge base for your employees to use: Ditch those FAQs. Instead of making assumptions about what information employees want and need, figure out what questions they’re actually asking and focus your efforts there.

I call these Actually Asked Questions, or AAQs.

Implementing a knowledge base with AAQs can be a great first step in leading your organization into a new era, one in which organizations become more personalized, predictive, and seamless for their employees. This is a critical transformation. A recent survey of CHROs (chief human resource officers) reveals that more than half of CHROs (56 percent) see their roles as creating a digital, consumerized employee experience. And 77 percent, or more than three in in four, expect to see improved employee experiences from digital transformation in the next three years.

So where should you begin this daunting task of providing all information pertinent to your employee base? Start simple and take a phased approach.

To start, have your HR department take a few weeks and log every question that comes its way, whether via email, phone call, or someone flagging them down in the hallway. Build a database. See what it is that employees need to know, and what’s bubbling up as a question being asked over and over again. Use the top 20 or 30 questions to build your knowledge base. If you have the answers to those AAQs, you’ll be well on your way to creating something your employees will find useful.

When it comes to search functionality within your knowledge base, keep it simple and uncomplicated. Google became a massive company with the simplest of search pages. Learn from that. Equally important, ensure the search results are simple, too. Write answers in conversational, digestible language that employees can easily consume. You do not want to provide as the first search result your company’s entire policy. No one will read it and you’ll start the vicious cycle of phone calls to the HR department all over again.

Building AAQs does take some time. There’s work required up-front that will pay off if done right. Which means curating the content listed, not lifting and shifting information into the knowledge base from some other database or portal without carefully vetting it first. Listen to the employees. They’ll tell you what they need. And then refine that information into something easily digestible, so it’s of maximum utility.

Once you’ve built a knowledge base, keep it growing. As employees ask more questions, add them to the AAQs, because they’re coming from a place of authenticity. The knowledge base should be a living organism. For instance, perhaps when you assembled your AAQs, no one had asked about jury duty, but suddenly the courts call several of your employees. Go ahead and put that in.  One key to making the knowledge base work: Assign one person to be your knowledge manager. Especially key in the first six to 12 months after the knowledge base rolls out, the knowledge manager needs to keep a close watch on which questions are being asked, what searches are successful, and so on, so they can update and grow the database accordingly.

Here’s a bold idea that we tried, and it really worked: When you’re ready to go live with your new knowledge base, turn off your general 800-number and email accounts previously used to reach HR staff. Force employees to use the knowledge base and continue to refer them to the AAQs. Many organizations, however, find that approach too aggressive. You can still keep the lines of communication open if you like. Then if someone comes to HR with a question that could have been solved by searching in the AAQs, have HR reply with a gentle note along these lines: “I found your answer in our new knowledge base. Here’s the link.”

Either way, the knowledge base should be easily searchable on the employee-facing website/portal so you reinforce the habit of turning there first for all questions. It should also have the option to submit a new inquiry to the knowledge base, with a prompt along the lines of: Would you like to submit a case? Then the knowledge manager can respond, route their question, and take the steps necessary behind the scenes to incorporate the answer into the knowledge base for the next time that question gets posed.

That’s where the project comes full circle. You’re using real-life transactions to help inform and build your living knowledge base, ultimately serving the needs of your employees.  And with that, you’re well on your way to the new era of serving employees through digital transformation!