Artificial Intelligence in the workplace: Timesaving, chatbots & security

Three ways Artificial Intelligence is commonly being used in the workplace

Artificial Intelligence is a buzzword that is impossible to ignore in the world of technology. However, not all talk about the area has been positive.

Many believe that, in the foreseeable future, AI computer systems will match human intelligence and may even be better at certain tasks. This introduces the fear that the technology could even replace mankind.

While there’s certainly no denying that AI is a force to be reckoned with, we’re still relatively far from this outcome. The fact is, artificial intelligence is still in the early phases, although it’s quickly advancing.

You just need to look at developments made by Intel with its Watson natural language machine, which can answer almost any question. But why is there a need to look at AI negatively?


Saving employee time

There are many ways companies are using AI machines in a bid to streamline processes and to help employees in their roles. These systems can help prevent human inaccuracy and solve complex problems.

Of course, AI is still seen as a tech trend. It’s more of a future prospect than a mainstream area of technology. However, companies and organisations of all shapes and sizes are experimenting with it. American cloud computing giant Salesforce is one of them.

The firm has developed a product called Salesforce Einstein, a computer program that lets sales professionals analyse complicated information and calculate the needs of customers. By doing this, it saves teams time and allows them to deliver the best possible customer experiences.

Gavin Mee, senior area vice president of enterprise at Salesforce, believes that Artificial Intelligence has the ability to make humans more efficient and can help companies in an age where customer expectations are becoming more complex.

“In our connected age, customer expectations are skyrocketing and I believe Artificial Intelligence will be the tool to enhance human efficiency. In the workplace, AI is already starting to make employees more productive and valuable,” he says.

“For example, using Salesforce Einstein, sales representatives can analyse information instantly and in-depth and based on this, anticipate customer needs, and automate repetitive manual tasks like data entry.”

The system uses a mixture of machine learning and natural language processing to produce accurate results for employees. Instead of replacing them, it acts as a tool so they can achieve more for their companies and customers.

“By streamlining their workload, employees are able to better understanding their customers, and will naturally become more efficient and productive. Salesforce Einstein is like having a data scientist in your pocket. It gives each employee access to AI in the context of their role. Einstein removes the complexity of deploying AI so that any company, regardless of size or specialist expertise, can deliver smarter, more personalised customer experiences,” he continues.

“Powered by advanced machine learning, combined with natural language processing, Einstein is able to continuously self-tune, and so gets smarter each time you use it, creating an evolving, personal experience for every customer.”


Chatbot revolution

Chatbots, in particular, are attracting major interest in the business world. Powered by Artificial Intelligence, they aim to replicate intelligent human conversation. In a plethora of contexts, these computer programs are being used to help improve communication and information accuracy.

Habito, which is a mortgage broker company, is a good example. It’s developed the world’s first digital mortgage advisor, which lets millions of customers find the best mortgage for them using a connected device.

Daniel Hegarty, founder and CEO of Habito, says AI technology of all kinds will impact our lives greatly over the next few years – especially B2B sectors. His solution can help broker teams provide customers with accurate information and save time in the process.

“Algorithms, robots, automation, machine learning are all technologies impacting our everyday lives and traditional industries, particularly the financial sector. No more than a decade ago it was unthinkable that a customer could have a loan or credit card application underwritten online in milliseconds without an underwriter in sight,” he says.

“That level of speed and efficiency is what we should be striving for as businesses, whether you’re in financial services or not. We have to evolve to the point where we’re taking the complexity out of our services and freeing up our customers to focus on the big important decisions in life. 

“As a digital mortgage broker, AI allows Habito’s broker team to spend less time on ‘dumb’ work like collating and inputting information into lender databases or crunching numbers – tasks robots are infinitely better at. But more importantly it frees up broker time to provide the value consumers are crying out for – whether it’s providing the comfort of knowing someone’s on the end of a phone or helping with a complex case.”


Fighting cybercrime

When it comes to Artificial Intelligence, there’s clearly a big emphasis on saving time and improving efficiency for companies. But this area of technology can go even deeper and solve some of the most critical issues, including cybercrime.

In a digital age, companies are becoming increasingly concerned about cybersecurity threats, although AI can help. LightCyber, a cybersecurity company with operations in California and Israel, uses machine learning to map out and monitor all users and devices on a company network. This sort of technology could become a critical tool for the modern security professional.

David Thompson, senior director of product management at LightCyber, explains: “At LightCyber, we use AI/machine learning to establish baseline profiles of all users and devices on a network—essentially learning what is good and normal for each. This would be an enormous task for a large group of security professionals and difficult to coordinate into a single store of knowledge.

“We start with a blank slate and no preconceived notions, and use AI/machine learning to establish these profiles almost completely without intervention. Next, we use AI/machine learning to detect behavioural anomalies against this backdrop of learned good. To achieve a very high level of fidelity, we use machine learning to identify those anomalies that are likely truly malicious and indicative of an attack.

“One of the biggest problems of security today is that security and IT professionals are completely overrun by a daily flood or hundreds or thousands of alerts. Most of these are false alarms. To pinpoint an active network attacker, it is critical to produce only a small number of alerts, and they must be very accurate.

“There will be a critical role for the human to play for years to come (if not indefinitely). Within the next 12 months, AI/machine learning applied correctly will isolate and escalate a small number of actionable alerts that a human can then reasonably investigate and respond to.”


Also read:
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