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Artificial intelligence will soon take center stage in your contact center — if it hasn’t already.

Artificial intelligence (AI) uptake increased dramatically over the last few years. A 2022 PwC report revealed that more than 70% of companies were already using or planning to deploy AI in some form within their business operations. Business leaders are using the technology to realize an array of benefits, from product innovation to enhancing data-driven business decisions.[1]

AI helps companies operate more efficiently and address more customer issues with less direct human involvement. This outcome is key for AI’s return on investment. It’s natural, then, that many would wonder what role humans should play in the delicate dance of customer service. As they rapidly improve, are bots pushing humans off the dance floor?

We may not yet know exactly what it will look like, but there’s good reason to believe that there’s plenty of room for robots and humans to perform in harmony to create quality customer experiences. In fact, their ability to stay in step will prove to be essential. In the CX of tomorrow, bots aren’t pushing humans off the dance floor — but humans will need to change up their footwork.

The self-service revolution

Customer service used to be, essentially, a dance between two people: the agent and the customer. Providing a quality experience primarily meant training agents to engage customers with empathy and address their concerns. But this has all changed in the age of self-service.

Thanks to AI, many customer issues can now be resolved without the involvement of a human agent. From basic banking transactions to checking on the status of an order, today’s chatbot and conversational IVR solutions can address many customer needs while reducing the costs of service. Unlike human agents, they can provide 24/7 support and handle multiple customer queries simultaneously. New forecasts predict that AI agents could save the contact center as much as $80 billion in labor costs.[2]

These benefits don’t apply only to businesses, though. Customers want self-service. According to a report from Aspect Software, 73% of customers want brands to allow them to solve issues and answer questions on their own. Sixty-five percent say this makes them “feel good” about a company.[3] In other words, they sound happy to invite AI to the dance.

Where AI still falls short

There’s a catch, though. Customers are perfectly happy to go a turn or two with AI — as long as it resolves their issues. When bots don’t work well or create barriers to customer service, they cause more problems than they solve. A recent UJET survey even reported that 80% of customers found that interacting with bots only increased their frustration with a company.[4]

To some degree, the reasons for this are obvious. We’ve all experienced what happens when AI interactions go awry: the doom loop of incomprehensible or just plain wrong responses with a chatbot or the bot trap that won’t let you escape to the safety of a human agent. These are familiar scenarios in today’s service economy.

These AI limitations are still real, even as the technology improves and aims to move past them. Today, though, the limitations of AI can be more subtle — and, perhaps, more dangerous. Consider the recent hype around ChatGPT, the latest and most ambitious chatbot released by OpenAI in late November. This bot achieves a new level of conversational fluidity with its ability to respond to open-ended questions, even writing convincing humanesque essays in response.

ChatGPT seems so authentic that it could easily deceive anyone who is unaware.[5] It’s clear that, despite AI’s significant advancements, it still can’t quite meet the challenges of complex human tasks and interactions in the way that real humans can.

Setting the stage

Ultimately, these limitations point to what the new rhythm of customer service can feel like. AI hasn’t supplanted human agents — and likely won’t anytime soon. But it can support human agents in crafting a more complete customer experience.

AI can enhance customer service beyond simply replacing human-driven interactions with bot-driven ones. AI can augment agents’ capabilities in several ways. AI can easily collect vast amounts of customer data and turn it into personalized recommendations that human agents can use to enhance CX. It can seamlessly serve up customer information directly to agents so that they can solve customer problems faster. And it can accurately route issues to the right support teams so that the best-equipped agents take the call. This type of give-and-take represents the future of customer service in contact centers.

Moreover, by handling routine and mundane tasks, AI can offload interactions from agents, ensuring that they are available for more complex interactions. Experts have foreseen this for a while now. In its 2017 report, “The Future Of Jobs, 2027: Working Side By Side With Robots,” Forrester predicted that robots would complement and enable humans to focus on tasks that involve more complex intelligence, aesthetic judgments, and unique skill sets.[6] This, in turn, helps human agents improve to meet these new challenges — 79% of support agents report that handling more complex issues enhances their skills.[7]

To truly set the stage for a smooth performance, however, contact centers must ensure that their AI technology is dialed in and ready to perform. Training agents to do their part is essential, of course. But if your chatbots and conversational IVR systems are unreliable, they will only create more problems for your human agents, no matter how prepared they are.

That’s why, in the age of AI, a comprehensive testing solution is more important than ever. Contact centers need complete confidence that the chatbots and conversational IVR systems they deploy not only stay up and running but also avoid causing problems through clunky or unintelligible customer interactions. Cyara is the only CX assurance platform that covers your customer support solutions from end to end. With Cyara, you can ensure your AI-powered CX is performing at its best — and prepare for the main event of human-to-human interaction.

The dance may be delicate, but it can be especially beautiful when all goes smoothly. Take a look at our Building Smarter Chatbots ebook to learn more about how we can help you ensure that it does.

[1] PwC. “PwC 2022 AI Business Survey.”

[2] Tech Monitor. “AI in call centres could save businesses $80bn.”

[3] Bizreport.com. “Report: Poor Customer Service Pushes Consumers Away.”

[4] Forbes. “Chatbots And Automations Increase Customer Service Frustrations For Consumers At The Holidays.”

[5] Business Insider. “I asked ChatGPT to do my work and write an Insider article for me. It quickly generated an alarmingly convincing article filled with misinformation.”

[6] J.P. Gownder, “The Future Of Jobs, 2027: Working Side By Side With Robots.” April 3, 2017, Forrester

[7] HelpScout. “Will AI-Powered Customer Service Replace Your Job?”

Artificial Intelligence, Machine Learning

Posted on Posted in Digital transformation, General topics Tagged with , , , , , , , , ,

The demand for ongoing transformation and innovation is going to continue to drive IT budgets into 2023. As a solution to the challenges of inflation, recession, geopolitical instability, and the broader economy, IT is seen as the way forward.

Research shows that more than half – 52 per cent – of organisations are expecting to increase spending in IT. Among those that have already commenced the transformation journey, that number rises to 67 per cent.

Transformation is broad, however, and what IT leaders will see as a priority for investment will be technologies that bring human-centricity to the experience of interacting with technology. What this comes down to is two priorities – helping staff work at maximum productivity and efficiency, and ensuring that they’re happy in their jobs.

As Forrester put it: recession fears and talent constraints make paying attention to existing employees more important than ever – deep within the “Great Resignation” and facing an unemployment rate of just 3.4 per cent, every member of the executive team is being tasked with grappling with the challenge of talent.

By deploying IT spending correctly, the CIO is in the best position to solve this issue. Lenovo research shows that 75 per cent of employees seek purpose-driven work, and that transformation spend can be most effectively deployed in delivering solutions that engage workers, free up focus time, and improve business outcomes by helping everyone to do their best work.

Priorities for human centricity

The first priority for CIOs is to understand that remote work is here to stay, and the focus needs to be on turning that into a strategic opportunity. The Forrester research suggests that four in ten hybrid-working companies will try and roll back that policy and doing so will backfire on them.

In contrast, Lenovo’s research reveals that investing in remote work offers advantages. Employees are more productive, and 78 per cent of employees report that having better collaboration technology has unlocked the opportunity to recruit a more diverse workforce. This has unlocked the opportunity to access broader skillsets. In this context, it’s no small wonder that 44 per cent of IT leaders plan on making investments in hybrid collaboration tools to improve remote communication.

Elsewhere, employees also want to believe in the work they’re doing, and this means being a good corporate citizen and investing in sustainable solutions. This needs to be a multi-faceted approach, including the use of renewable energy, leveraging technology that is energy efficient, and reducing waste by ensuring that technology is reparable and has a long life. Hybrid work has a role to play here, too, by helping to eliminate the energy-inefficient commute to work.

However, human centricity also means understanding how people work. This is because, in a hybrid work environment, there will be times where employees want to come into the office. There, they need both a seamless and superior experience. This means they need to be able to continue working as they had been at home, while also enjoying a superior working experience in the office. Communication between onsite and offsite employees also needs to be seamless, and for CIOs, this need to modernise the in-office experience will result in some IT projects. For example, Lenovo research shows that 32 per cent of companies have subscriptions to workplace collaboration tools that help manage IT-related tasks. CIOs might need to invest in further solutions to continue to strengthen the “work anywhere” experience.

Delivering human centricity needs holistic solutions

As the popular saying goes, too many cooks spoil the broth. The more individual pieces of technology and services that a company uses, the more likely it is to compromise the employee experience, as solutions don’t work seamlessly together. Vendor consolidation is expected to be a key theme for CIOs going into 2023.

For Lenovo, being able to provide an end-to-end solution to CIOs has been a key priority. By choosing a trusted partner to help streamline solutions, Lenovo promotes a superior human-centric experience in three ways:

Lead with a purpose-driven vision – Lenovo solutions equip employees with durable, repairable, energy-efficient technology, from individual devices right up to the datacentre solutions in the office.Super-charge collaboration – Lenovo solutions leverage AR devices, as well as smart platforms to allow for complex, rich real-time collaboration, screen, and device sharing.Support a trusted end-to-end technology partner – Lenovo solutions make Device-as-a-Service, Infrastructure-as-a-Service and custom cloud solutions from a single partner possible, allowing the organisation to consolidate their touchpoints and vendors.

A full 82 per cent of IT leaders want to work with technology that delivers on the value of the transformed workforce. This means technology that allows for human centricity, and, in 2023, it will mean the difference in hybrid work being a point of competitive advantage for the organisation.

Remote Work

Posted on Posted in Digital transformation, General topics Tagged with , , , , , , ,

The age-old debate on technology versus human capability remains inconclusive. But in this time of artificial intelligence (AI), analytics, and cloud, we’re seeing more opportunities to think of how humans and machines can come together as a team, rather than acting against each other. From diagnosing diseases and delivering effortless customer experiences to understanding human preferences and providing new customer insights, the human and AI partnership is evolving — and more in sync than ever. That’s making our lives simpler and more convenient. 

Gartner predicts that context-driven analytics and AI models will replace 60% of existing models built on traditional data by 2025. We will see new types of data — including unstructured data, such as audio, video, and images — being leveraged to give organizations a competitive advantage, get more value, and develop new use cases to set the stage for a new customer-driven era.  

This offers a glimpse into a future of close human and AI partnerships, where we think, collaborate, and create augmented by technology and business intelligence. This kind of partnership is important when the objective is to empower customers with personalized and relevant insights that can help them make informed decisions to buy products, subscribe to services, or use various offerings, which in turn adds to their trust and loyalty in a company. 

A real-life example of this can be found in an intelligent virtual agent or chatbot used by organizations to provide personalized service and guidance to people. Chatbots use AI and scripted rules to ask questions, identify the challenge, and resolve customer queries. 

Chatbots seem like a fool-proof solution to creating and delivering a good customer experience with fewer human resources, but recent Avaya research with Ipsos indicates that, based on their last interaction with a virtual agent, only 1 in 3 customers would recommend that business to others. This is because only 50% of them had their issue or concern resolved. This lack of success is due in part to the historical complexity of developing and delivering effective virtual agent solutions.    

Traditionally, it could take months to deploy a virtual chatbot, by which time consumer preferences, business processes, or even basic company information may have changed. Relying on a chatbot alone is a failure to leverage the potential of human-to-AI partnership.  

Avaya Virtual Agent removes this complexity, enabling organizations to quickly deploy Avaya-designed, pre-built, cloud-based self-service agents instead of building them from scratch. It leverages the Avaya Experience Platform™, which reimagines communications composability, providing customers with the option of constructing their own workflows or subscribing to pre-built experiences. This also enables businesses to participate in the Experience Economy by elevating their customer interactions beyond just making them more efficient to also making them more engaging to capture increased customer time and attention. The Avaya Experience Builders™ community can assist businesses with getting started or with addressing more advanced deployment requirements.

The ready-to-deploy virtual agent is designed to deliver the full benefits of virtual, AI-based communication experiences by leaning into the human-to-AI partnership. The solution reduces call volumes to live agents, decreasing average call wait times. It also increases agent productivity by providing important context to the humans who may have to solve more complex customer issues. Most importantly, though, it delivers true speed-to-value, enabling companies to infuse high-value capabilities into the customer experience in a matter of days. This means you can scale your AI efforts while leveraging an existing CX framework, building a true partnership between human and machine. 

That partnership is a win-win-win situation for the company, contact center agents, and the customer. The company can swiftly compose the kinds of interactions that its customers expect; the call center agent is given access to a single, easy-to-use dashboard that eliminates the need to train and helps dedicate more time toward meeting customer expectations; and customers appreciate the heightened level of responsiveness.

This advanced capability also does away with misconceptions about technology taking over jobs. This perception stems from the inability of companies to have an open discussion with employees about embracing AI across business functions. Using technology with a purpose is known to help employees focus more on business innovation and value-added tasks, rather than spending time on mundane work. It is a company’s responsibility to demonstrate and educate their employees on how technology can augment and support their work to achieve satisfaction.  

In today’s experience economy, human abilities can fall short, due in large part to the outweighed importance of heavy data analysis. But relying entirely on machines is hardly the right approach — organizations need the automated, fast-calculating power of AI. But they also need the human ingenuity that’s required to solve complex issues. The focus, then, should be on adopting AI technologies that enhance the skill sets of your employees. 

Artificial Intelligence

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In my last column for CIO.com, I outlined some of the cybersecurity issues around user authentication for verification of consumer and business accounts.  

Among other things, I advocated that in this remote/hybrid work era, CISOs must protect their company’s access to data by having a cyber-attack plan ready to implement, understanding the new tools and tactics that cyber thieves use, and being aware of newer AI-based technologies that can lessen cybersecurity risks. But first and foremost, I stressed that to better protect their organizations, CISOs needed to adopt (if they hadn’t done so already) some of the evolving identity and access management technologies being offered by a crop of emerging companies. 

Responses from other industry professionals generally agreed that there are issues around authentication, including multi-factor authentication (MFA), but some asked, “Isn’t FIDO supposed to eliminate the risks from all that? Didn’t the FIDO Alliance just recently announce new UX guidelines to speed up MFA adoption with FIDO security keys?” Well, yes, but there is more that tech pros can do. I’ll explain more below.  

Why FIDO?

FIDO as an industry initiative was set up a decade ago to standardize the need for strong authentication/password technologies. It’s basically a stronger set of security authentication measures, in essence, a better security ‘handshake’ between the device and a third-party service. Companies in the alliance include board-level members like Apple, Amazon, Meta, Microsoft, Google, and other tech-heavy hitters. Collectively, they are seeking to solve problems caused by users needing to create, maintain and remember multiple usernames and passwords.  

While these initiatives are great, they are only solving an authentication problem between the device and the end service. FIDO provides seamless and secure authentication to a service from a browser, your phone, or an app. But the reality is this is a device authentication, not a human one. There’s still a step on the front end, where the user has to authenticate themselves with the device, and this can be compromised. 

Identity and access – the user authentication challenge 

For example, using my phone’s face recognition access, my kids can hold my phone up to my face, and boom, they have access. All of the added protection provided by FIDO just got wiped out. My kids could have used (and abused) my accounts. Thankfully, I’ve raised them right. Or at least I hope so! 

In addition, someone could create a fake identity representing me on their device. From that point forward the third-party service thinks that I am the user because the device or browser has been authenticated, even though it is really a hacker who has hijacked my identity to set up the device. 

Obviously, there’s still a need for a layer of continuous authentication and user identity management to help protect against these exploits. This is about identifying the user versus the machine on an ongoing basis, not just at set-up or log-in. How can we do a better job of identifying who our real users are, while also eliminating former users (employees and contractors) from the ranks of those who have access to some of the most critical of systems? 

This is where I think that some of the newer products emerging from the start-up world will be very beneficial to protecting our organizations. 

Man vs. machine 

Solving the human user identity and authentication issue is just part of the problem. A recent article in Security Affairs notes that “while people need usernames and passwords to identify themselves, machines also need to identify themselves to one another. But instead of usernames and passwords, machines use keys and certificates that serve as machine identities so they can connect and communicate securely.” These can be also compromised by hackers. 

Managing the identity of devices used in cloud services, SaaS applications, and other systems is perhaps becoming an even bigger problem. Organizations often set up a new web service, create an identity for it and the IT assets associated with it, and once it’s up and running, IT staffers are likely not rushing to change or update security configurations on those systems. Once the initial dependencies are set up between devices, it gets that much harder to sever or update those complex relationships.  

However, good security acumen would determine that those should be refreshed, which can be a huge management problem. As a result, older, stale credentials become a softer target to attack. 

Hackers are increasingly exploiting the credentials of machines, not humans, to launch their attacks. Just like fooling other humans, hackers can fool other machines into handing over sensitive data. According to Security Affairs, given that machine identities are the least understood and weakly protected parts of enterprise networks, it should come as no surprise that cybercriminals are aggressively exploiting them. From Stuxnet to SolarWinds, attackers are increasingly abusing unprotected machine identities to launch a variety of attacks. In fact, over the past four years threats targeting weak machine identities have increased by 400%. 

This is a big deal.  

The bigger picture 

Ultimately, as companies continue to expand their use of hybrid and multi-cloud digital services, the more human and machine entities there will be to manage.  

CIOs must lead IT operations teams to ensure management of the whole identity and access lifecycle for both humans and machines. This is likely to involve new AI-connected tools that seamlessly handle integration, detection, and automation. These tools can equally limit or extend access to certain functions for both human personnel and automated actions, improving security while bringing down costs by pruning unnecessary account licenses. 

In addition, these solutions will fill a void that today still creates major headaches around compliance and reporting. Building a full audit trail into your existing systems is a start. With automations already in place, IT staff can then better manage the governance.  

Ready or not, CIOs and CISOs need to adapt to the evolving identity and access management landscape to adopt a holistic strategy or risk security breaches, failed compliance, and costly fines. 

Authentication, Cyberattacks, Security

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An alarm sounds on the factory floor: a critical piece of equipment has malfunctioned. An engineer approaches the machine, scans its QR code, and immediately accesses visual step-by-step instructions for fixing the issue created by the people who work with the same machines every day.

This is SwipeGuide, a B2B cloud-based SaaS platform that captures and scales operational knowledge, helping teams in industrial environments to create, improve, and share instructions and standard operating procedures using mobile and wearable devices. The platform is designed to help reduce errors and downtime, improve the quality of products, and help onboard new employees – all powered by the expertise of frontline workers.

SwipeGuide Chief Technology Officer Sue Li has worked in the tech industry for over a decade, with a degree in educational technology and instructional design from Harvard University’s Technology, Innovation, and Education programme for her master’s degree. Li gained experience in visual art and UX design as well as product management and software development before joining SwipeGuide in 2019. Less than a year later, she was promoted from full-stack developer to CTO.

“I learn best through hands-on learning and just by tackling problems,” Li says. “My first year as a CTO involved learning a lot about the security and scalability of the infrastructure, data privacy, and compliance. Part of the learning process was figuring out how to ask the right questions and work with experts to solve very detailed and strategic problems.”

Harnessing the power of data for frontline workers

One of the challenges that Li contends with in her role is the ever-increasing volume of data that the platform produces, including content, feedback, usage, and behavioural data. Li is developing SwipeGuide’s new strategy to figure out how to manage it and how to put the data to work.

“The strategy that we want to go forward with is self-service analytics: how can we empower users on the factory floor so that they don’t need to rely on a data scientist or analyst to get insights? We want to have all of our data in a data warehouse as a single source of truth so that we can analyse and provide those insights to the operators. I think that’s going to be an important step towards having more robust machine learning models as well. It’s going to be very, very powerful.”

SwipeGuide is expanding its services beyond its European customers to the US and China, which presents the challenge of ensuring data privacy and compliance for an increasingly global audience.

Currently clients can access analytics dashboards on the platform that can show entities the adoption of their content, like how many instructions have been created over time by specific teams in different workspaces, and how often they’re viewed.

“We want to be able to provide better insights with those dashboards, and another part of that is embedding that data right into the platform itself: being able to see which guides have been the most popular and are the highest quality. Later on, we will be able to analyse which characteristics the highest-rated guides have, maybe something about the structure of how they are written or the structure of the images or videos. This is where machine learning will come in, to help us make recommendations to improve the quality of instructions over time.”

The human factor in Industry 4.0

Life on the factory floor is changing rapidly with the onset of Industry 4.0, the fourth wave of the industrial revolution powered by data and bolstered by automation. Tools such as SwipeGuide aim to optimise operations by minimising downtime, but the insights needed to create smarter factories must come from human expertise first.

“Our work is all about empowering the frontline worker — the biggest waste is untapped human potential. I think that the problem that we’re trying to solve is all of the silent knowledge that people have: crowd-sourcing that knowledge from all the different operators and frontline workers, and then externalising and capturing that in a standard format that is easy to share,” Li says.

Contrary to popular imagery associated with Industry 4.0 – workers replaced by endless rows of indefatigable robots – Li believes that humans will have an important role to play. “There are very few smart factories out there where there is no human intervention,” Li says, citing an example of a car manufacturer in Japan that has an automated factory for building auto parts after figuring out the step-by-step instructions necessary for robots to execute those tasks.

“With the data processing power that we have now with edge computing and cloud computing, there will be a huge shift over the next 10 to 20 years in what can be automated. But in order to reach that level of automation, we need to be able to build algorithms: some of the questions we’re asking are can we emulate the procedures, can we create an algorithm with the instructions, and how can we hook performance data into operational data?”

Branching out into wearables and augmented reality

Li and the SwipeGuide team are actively exploring other types of emerging technologies that work in harmony with the platform. The company is experimenting with wearable devices that will free up workers’ hands while they repair and service machinery.

SwipeGuide has created an Android app that can be installed on a durable industrial wearable like Realwear, which creates helmets and smart glasses built for factory settings. “We are also looking into compatibility with Google Glass,” Li says. “Wearables allow the operators to be completely hands-free when they’re repairing a machine or doing whatever they need to, which allows us to do more with voice commands.”

For more complex instructions, augmented reality can help workers understand specific gestures and motions that would be hard to describe with photos or text.

“We did a pilot with XM Reality, a remote support calling platform. If a worker gets stuck on a particular instruction, the remote experts can show users what needs to happen with augmented reality. Imagine, a worker has shared a real-time video of a part of a machine that is broken or loose, and they can see a hand on their screen making a motion or drawing a shape. Making the experience interactive can really help in situations where a course of action is very complicated and difficult to describe.”

Fostering innovation through an agile, user-centric approach

The challenges that SwipeGuide is currently facing, like integrating new technologies and developing SwipeGuide’s data strategy and machine learning models, require fostering a culture of innovation within the team. For Li, the best inspiration for new ideas comes from the people who use the platform and the solutions come from her team: “I think our customers really know the most, so it’s important to get insights from the market, the users, and the customers. We do our own usability testing — for example, we created a small competition where we created step-by-step guides for creating origami. It helped us experience the challenges that our customers face while uploading images or making changes to instructions, for example.”

Li believes that an important part of innovation is having an agile mindset, especially when it comes to software development, to measure the effectiveness of a new solution or idea.

“We track events and collect data so that we can measure solutions in relation to specific goals, like increasing visibility or usage,” she says

“If it works we keep it, and if not we create another iteration of that solution and then try again. We work in an industry with huge enterprises that use the waterfall methodology, but I think that takes away from the innovation element of being able to experiment with smaller improvements, collect and learn from the feedback, and develop new and novel ways to solve problems.”

Industry, IT Leadership