As an enthusiast of nature and intelligence for the majority of my life, I was fortunate to be introduced to artificial intelligence (AI) when it wasn’t still a buzzword, even in dusty computer labs of the ‘90s.
Then, some 20 years ago we introduced emotions to machines, proving “emotional machines” to be superior to traditional “logical machines.” Since then, all areas of technology have progressed, but AI’s enormous power to improve human life has exponentially advanced.
We are going through an exceptional moment in human life and the COVID-19 pandemic acted as a catalyzer to accelerate those changes.
It is an amazing time for innovation. And AI is offering us so many chances to understand ourselves as well as to understand and enhance our intelligence.
When Viola and Jones showed a computer model in 2001 that was detecting human faces, the audience was woven in attention and awe.
Now we all have biometrics and facial matching in our smartphones. And we can not only detect and identify humans, but a few companies have products that can also detect actions, behavior, and emotions.
Few advances in recent years, including the affordability and accessibility of computational power and progress in developing more agile and robust AI models, have given way to massive amounts of opportunities in creating enterprise applications.
And a growing number of these intelligent applications are analyzing humans, their identities, and their behaviors.
Why Do We Care About Behavioral Analytics?
Behavioral analytics is the key to these applications as it gives us the capability to identify any kind of patterns, trends, or even frauds through understanding human behavior.
Basically, behavioral analytics provides companies and organizations with helpful actionable insights that ideally enable them to truly respond to their employees’, customers’, and users’ needs, like giving the customers what they are really looking for, in faster, cheaper, or more sustainable ways.
So behavioral analytics as people-based datasets, may be generated from the users, which helps the companies in getting pretty good maps of the types of customers they deal with. And if these datasets come from the workforce, then these businesses will get clear inside views of what it is like to be on their side.
As the CEO of Hummingbirds AI we understand the importance of having actionable insights about the workforce.
The workforce is the gate between the users and the companies. Therein lies the importance of also getting the data to understand how the employees feel, interact, and develop their tasks. The better a company understands that fact, the faster it will be able to help the employees improve their performance and give the customers better responses.
Those critical objectives can be achieved through AI-driven behavioral analytics. However, workforce optimization (WFO) or employee performance is not only about the tasks themselves. It is about safety and human lives: which could also be at risk by giving the wrong information. These consequences could happen if a driver, a factory worker, and yes a contact center agent is tired, disoriented, or distracted.
At the same time, WFO and employee performance is also about boosting the level of satisfaction employees experience while doing their jobs.
One very helpful feature is the wellness or “happiness” feature. (Yes! in technology we need to think human, and human emotions.)
It uses vision-based behavioral analysis to give employees real-time feedback/recommendations. Like “Time to stand up,” “Take a minute to stretch your legs,” or “Time for hydration,” which are important messages to keep a workforce healthy and motivated.
Contrary to the belief that implementing AI solutions might seem pretty complicated or even overwhelming for most companies, in reality it is much easier than thought.
That’s why, as an AI entrepreneur, it is reassuring to see that everyday more and more companies—whether big or small—take to AI for workforce performance optimization.
AI has the power to optimize and protect your business all at the same time.
At present, any business should expect their competitors to be using AI. Realistically, not employing AI could very probably end up leaving that business at a competitive disadvantage due to higher costs and higher churn rate. Remember: AI has the power to optimize and protect your business all at the same time.
A New Challenge: Remote/WFH as the New Normal
This new normal era definitely has some challenges. One is the fact that our home has become altogether our office and our meeting room, we’ve merged our home and office, i.e., work-from-home (WFH).
And when providing a service, such as in the case of contact center agents, the environment in which the agents deploy their work is a key element when it comes to performance and customer satisfaction.
To address the customer’s issue assertively, any agent needs to be attentive, focused, and without distractions. The more an environment provides for this, the better the agent will feel and perform.
Luckily for contact centers, AI solutions in their field are constantly improving and offering new tools both for agents’ performance and customer experience.
In fact, these smart solutions are becoming so accurate and precise that they can even detect, in real time, both the psychological state of the agents as well as the uneasiness of the customers, regardless of their location.
Voice recognition, or voice-AI, is a good example as voice recognition is technically simpler than vision recognition, or vision-AI. Yet this is just the beginning for vision-AI.
On the one hand, any device nowadays has a camera, which makes for the easier deployment of this technology and on the other, the face is where humans show their expressions; there is a lot of information in any tiny gesture, from sadness to happiness, frustration, and to pleasure.
As we saw in the last decade, when we integrate AI-driven behavioral analytics with automation tools, it is truly remarkable how it can contribute to the simplification of the contact center agents’ tasks and improve clients’ experiences.
In commerce, for example, vision-AI is used to identify customers and their behavior to offer them instant suggestions on products and special offers. In human interactions, it can provide information on the mood of that person, which can help agents to choose the most suitable words to address customers.
Consequently, with these solutions, companies and organizations are able to reduce their costs and keep the agents focusing their expertise on helping customers where only a human can help.
But while remote work/WFH has advantages, financially and non-financially when it comes to balancing working and personal life, in terms of data privacy and security it has also proved to have its challenges.
Some contact center agents deal with sensitive data that not only has to do with the customers’ private information but also more confidential data, such as financial-related information.
For an agent not working at the company’s premises (but probably in any place with internet connection), visual hacking, aka prying eyes, shoulder-surfing is always a risk. This is a common way of social engineering whose goal is to steal sensitive information from a device.
However, it would be a mistake to think that this type of data threats only happens outside the conventional working space. Inside the company’s environment, visual hacking is also a great risk, as we have to consider data breaches happen very often amongst their own staff.
Besides, inside the company there are different degrees of employees co-existing, which allows for greater risk while the level of alert against visual hacking actions is lower because employees simply tend to relax and forget the danger of being observed for data hacking purposes.
With the mindset of protecting this data and keeping the employees’ privacy intact at the same time, companies are developing solutions to offer endpoint security solutions that protect businesses and their customers against data breaches, while increasing agents’ performance.
The key here is to protect the sensitive information and keep the conversation flowing and do so while providing a frictionless experience.
Empowering the Supervisors
Novel intelligent AI-driven applications can also work to benefit a missing player in the contact center equation: the supervisor, particularly in hybrid/WFH environments.
Contact centers with access to clients’ data, such as financial and healthcare, have to enforce corporate clean-desk policies, meaning the agents are not supposed to bring any extra computers, phones, tablets, pens, paper, etc. that can be used to record the customers’ data.
This compliance used to be enforced by supervisors, but as the pandemic caused a rapid shift to WFH there hasn’t been any tools in the market to make contact centers compliant with the regulations.
Some big companies tried to solve the issue through invasive solutions and got backlash from employees and unions as these methods and tools lacked respect for employees and their privacy.
However, a better, privacy-at-the core approach is to empower the supervisors with behavior analytics. For example, when a suspicious object, such as a phone, is detected, the intelligent application would look for the associated behavior of the agent with that object. Like if they were texting, recording, or taking a picture from the screen.
The supervisor and the information security team can then remotely and seamlessly make a better decision to safeguard the information against vulnerabilities while enforcing the regulation, rules, and standards.
So, behavior analysis in this case is helpful in assessing the risk, proposing a proper defense, and taking necessary actions, all in real time. And that’s the beauty of actionable intelligence.
With cloud being the new trend, most companies are signing up left and right for transferring their data to the cloud for convenience.
Yet there are a few important problems associated with the cloud, such as more cyberthreat vulnerabilities and the lack of privacy.
Uploading our data to the cloud is easy, space-saving, and comfortable, but without an internet connection there is no real access to it, it is not physically accessible, and the data can easily end up in hackers’ hands.
Therefore, a new wave of tech companies are developing cloud-independent applications which run locally at the device/edge, thus called edge computing.
It’s estimated the size of edge computing applications would be five times the size of the cloud-based market.
When saving your data in a device, hackers have no chance of breaching because their only chance is through the internet. This way, data remains in the owner’s hands, physically accessible, and protected.
Employing edge computing is also a smart move to consider cloud-independent applications, which can still do their jobs if the internet connection between them is lost.
In this case, employees and companies keep their data safe and agents can continue to serve their customers when the connection returns.
The future of work, hybrid and remote work, cannot and must not be disregarded.
This new reality and its future can also be seen in the AI prospective market. According to a report by MarketsandMarkets, the market for contact-centers AI technology is expected to grow from $800 million in 2019 to $2.8 billion by 2024.
This number by itself shows the growing importance and positive impact AI-driven technologies are having and are expected to have in the near future for companies in general and those offering services in particular.