Artificial Intelligence (AI) is set to make remarkable advancements in the world of work. For contact centres, it promises everything from improved employee engagement to better customer experiences.

But between the nuances of what AI has to offer, it also raises important ethical questions. Most importantly: how can we harness the power of AI responsibly? Business leaders who are rushing to adopt AI may be short-changing critical considerations like ethical guidelines, bias detection and even simple safety measures.[i]

Therefore, it’s essential to bridge the gap between theory and practice. As a sector that’s been using automation technologies for decades, customer service offers a unique perspective. From automated call distribution (ACD) systems to online chatbots and, currently, new generative AI tools based on large language models (LLMs), customer service has been a pioneer in using AI’s potential.

To find the right way to implement AI, no matter the industry, there’s a lot that others can learn from the experiences and strategies employed by customer service providers.

Why responsible AI matters

One of the biggest aspects of using AI responsibly starts with data. Customer service operations often deal with vast amounts of sensitive information, from personal details to financial data. Yet, the challenge lies in maintaining the highest standards of data privacy and security while using AI systems to improve customer experiences.

Just as you wouldn’t leave your personal documents on a public bench for anyone to access, you wouldn’t leave customer data just lying around. Treating data with the same level of care is crucial to success. Within customer service, safeguarding sensitive information is not only a legal requirement, but it’s a fundamental aspect of building trust.[ii] Particularly when 64% of consumers trust companies that actually provide clear information about their privacy policies over those that don’t.[iii]

And what about generative AI? Although it holds great promise for customer service, it is susceptible to errors. After all, it generates answers based on patterns learned from datasets and there’s a minefield of legal, financial, and ethical implications if the content generated is inaccurate, inaccessible or offensive.[iv] It’s not like it has a self-correction feature either. There’s a risk of these inaccurate results placing a burden on agents to rectify these issues too, making their lives harder, rather than easier.

This is where responsible AI implementation comes in.

With contact centres, where customer interactions are at the heart of everything, it’s important to build and keep that trust. That’s why businesses can’t just add generative AI and automation technologies for the sake of it or use it to replace workers because it’s seen as cheaper.[v]  Customers want their problems solved with​ the nuance and empathy that only a human can provide.[vi]

Put simply, AI is not here to replace humans. But humans with AI will replace humans without it.[vii] Therefore, steps need to be taken to ensure that AI is integrated ethically to avoid the pitfalls of failure.

Transforming agent dynamics

Ultimately, AI serves as a critical ally for contact centre agents when you consider how it can be used to support them. Much like the retailer IKEA, which trained call centre workers as interior design advisers and introduced an AI bot named Billie to handle standard customer inquiries.[viii] This system allows the staff to focus on providing specialised interior design consultations, while the bot efficiently manages regular customer questions.

Here lies the essence of AI. By providing real-time support in decision making, particularly where complex scenarios demand quick thinking, it enhances customer satisfaction and aids agents in making informed decisions to address issues effectively. After all, customers are more willing to share data if they believe they’ll receive something worthwhile in return, like solving an issue they’re having.[ix]

And with generative AI, where it can provide instant access to answers for both customers and agents, a strategic and context-specific approach is essential. Using it within well-defined boundaries and implementing safeguards for constant monitoring can help identify and address inaccuracies promptly. Putting proactive measures in place, such as regular audits, helps businesses use generative AI without compromising on the quality of customer interactions.

This instant access to data improves response accuracy and consistency and also allows agents to focus on more complex calls and value-added tasks. More importantly, it leads to greater efficiency, enhancing agent engagement and ROI through intelligent automation solutions. Don’t believe me? Then consider this Fortune 500 global insurance company that deployed AI automated technology that yielded a 3X return on their investment within the first two years.[x]

If it’s good enough for a Fortune 500 business, it’s good enough for anyone. But how did they get it to work so well? The answer lies in how the AI is set up.

Supporting agents with AI

Ultimately, AI’s effectiveness hinges on its context-specific application. By understanding the intricacies of different scenarios, AI can be used to provide more accurate and relevant responses in addressing inquiries and issues, helping agents to develop a more efficient and personalised customer experience.

Beyond these functions, AI can also assume the role of a virtual coach, offering feedback to agents based on their call interactions. Unlike human coaches who have limited availability, many call centres use AI to support professional development for agents, as it’s accessible 24/7 whenever and wherever they need.[xi] The key thing to remember is that correct set-up of AI isn’t just a technological advancement, it’s a strategic investment that enhances the human potential within customer service.

With 83% of call centre agents saying that their work has a negative impact on their mental health,[xii] whether that’s through challenging customers, a repetitive high volume of calls or a large workload, AI can be used to support agent well-being. Research by McKinsey highlights that automation technologies can be used by corporations to reduce productivity losses due to employee burnout.[xiii]And contact centres – a demanding industry if I do say so myself – are taking full advantage of the technology to improve the lives of staff.

And by improving the lives of staff, you’ll start to improve the lives of your customers.

Paving the way for AI implementation

Implementing AI the right way not only transforms the efficiency of customer service operations but also highlights the benefits it offers between technology and the well-being of the human workforce. The key lies in keeping it within a context-specific approach and recognising that good data protection is at the core of this transformation. By harnessing the right technology and ensuring responsible data practices, businesses can not only enhance customer satisfaction but also safeguard the welfare of their staff.

Soon enough, humans with AI will replace humans without it. So, if you’re looking for a better ROI and a way to support your staff, AI is the way forward. No matter the business or the sector, as long as you first consider how AI can support and protect customers as well as staff, you’re on the right track.

About the author:

Paul Milloy, Business Consultant at Intradiem

Paul Milloy has almost 40 years of operational experience in customer facing activities & roles ranging from engineering, customer operations management to business change and improvement and latterly in resource planning.

He was Resource Planning Director at Centrica between 2016 and 2020 running an integrated planning function for British Gas Customer Operations, responsible for all aspects of end-to-end resource planning for all customer contact channels with over 20 million contacts per annum and an agent population of 8000.

In January 2021, Paul joined Intradiem as Chair of the Forefront Executive Council for UK&I, leading on thought leadership engagement and senior leader networking, and supporting on brand and solution awareness and business development.

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