AI in the contact centre is no longer a question of if, but where to begin. In our recent webinar with Jimmy Hosang, CEO and Co-founder of Mojo CX, we explored seven practical, high-impact AI use cases that are already delivering returns in real-world operations. From automating wrap-up notes to exploring full voice AI, the conversation cut through the hype to focus on what’s truly working – and what’s coming next.

From productivity savings – and easy wins – to value generation, here we summarise each of the seven use cases, their benefits, pitfalls, and what it takes to make them work.

1. Autowrap / Call Summarisation

This is one of the most immediate and measurable wins for AI – and it’s relevant to every contact centre, whether procedural or regulatory. With AI transcribing and summarising calls, wrap time is reduced by 50% and average handling times by 5–15%. In a 200-seat contact centre, at 10%, that’s equivalent to freeing up 20 full-time agents.

It’s an easy sell for operations leaders: the 2-3X ROI is immediate, the data is clean (and doesn’t need complex integrations, a simple copy/paste will do to start), and the impact on agent workload is obvious. What you do with the benefit is up to you; save the 20 FTE through natural attrition, reduce wait times, improve service. Less typing, less admin, more time for real conversations.

2. Auto QA (Quality Assurance)

Manual QA processes typically only cover 1-2% of calls. With AI-powered auto QA, every conversation can be transcribed and assessed, increasing both coverage and scorecard accuracy, with the potential to reduce QA overhead by 75%. Once the model reaches high accuracy (which can be achieved in four weeks or less), it enables a rethinking of QA resourcing. Where teams can reinvest those hours into value-adding activities like deep-dive analysis or real-time speech insights.

What’s more evaluation consistency is likely to see an immediate uplift, as is agent performance through real time feedback.

3. Auto Coaching

Team leaders spend 60-80% of their buried in fragmented data or playing detective to understand performance issues. Auto coaching can bring together call data, performance stats, and behavioural insights into one view – streamlining prep time and allowing leaders to focus on actual coaching.

From an efficiency perspective, this facilitates a shift in manager-to-agent ratios from 1:12 or 1:15 to something closer to 1:18 without losing effectiveness. But beyond that, coaching quality and consistency improve and agent development is more pointed and expedited. It also unlocks the potential for automated role play both on the job and in grad bays. This provides the basis then for both greater job satisfaction among both managers and agents, as well as delivering higher quality interactions throughout the operation. All of which have an impact on broader measures such as agent attrition, CSAT and brand perception.

SIDE NOTE: While those first three use cases focus a lot on the potential for reduction in headcount, it’s often more about doing better work, not just less work. Think: HITL (Human in the Loop), not human out of the picture.

4. Identifying Vulnerable Customers

This is where AI starts playing a key role in risk management and regulatory compliance. Agents can’t always be relied upon to spot vulnerability signals in real time – especially when they’re under pressure to do many things at one in a short space of time. AI can listen in and flag when it detects signs of vulnerability, alerting the agent in the moment and ensuring the right customer journey is followed.

The benefit? Reduced regulatory risk, better outcomes for vulnerable customers, and more confidence in compliance reporting. This use case also pairs naturally with summarisation – capturing the right context and actions in the CRM.

5. Agent Assist

Beyond risk management and efficiency, AI also enables agents to add value in the moment. Agent Assist tools analyse the live conversation and suggest actions – whether it’s handling a low-value enquiry quickly, spotting a sales opportunity, or guiding a customer toward a better outcome.

This is where things get exciting. AI is no longer just reducing cost – it’s helping unlock customer lifetime value and improving journeys. It’s also a mindset shift: from cost centre to value driver.

SIDE NOTE: The constant push for self-serve may well be eroding brand loyalty, where a great conversation with an agent isn’t only about making a sale or solving a query, it’s an experience that plays into customer brand perception.

6. Hands-Free Conversations

Imagine an agent who doesn’t have to type, click around systems, or juggle tabs – just talk and listen. That’s the promise of hands-free conversations. With AI handling navigation, form filling, and admin tasks, agents can give customers their full attention.

It’s not just about productivity, it’s about truly human interactions that focus solely on the customer. How satisfying would that be? It could change the type of people you hire and shift expectations around what great service looks like.

7. Full Voice AI

Everyone’s chasing the holy grail: fully autonomous AI voice agents. Why? 24/7 customer contact, instant routing, and scalable service without scaling headcount.

But Jimmy’s message was clear – don’t rush it, though do keep your eyes on the prize. Build your maturity and path to value with easier use cases, underpinned by the right data and processes. This isn’t about flipping a switch – it’s about a journey to transformation.

Final Thoughts: Think “value first, tech second”

Across every use case, the AI you deploy is about outcomes. Whether that’s saving time and cost savings, improving job satisfaction or deepening customer relationships, AI only succeeds when it’s introduced with purpose.

Start small. Pick the use case with the clearest ROI. And don’t be afraid to move fast – but move smart.

In today’s outsourcing landscape, success depends on much more than cost savings and process efficiency.

On 25^th February 2025, Neville Doughty and Phil Kitchen from the Customer Contact Panel hosted a webinar with Joe Hill-Wilson, CEO and Co-Founder of Learn Amp and Martin Hill-Wilson, Owner of Brainfood Consulting, to discuss Sustainable Operating Models in Outsourcing. One of the most important takeaways from the discussion on sustainable operating models is that Learning and Development (L&D) must be embedded into the core of every outsourcing strategy. Without continuous learning, sustainability simply isn’t possible.

Why Learning and Development is a Sustainability Driver

In outsourcing environments, teams often face rapid change, evolving client expectations, and shifting technologies. This is reflected in the data – 92% of organisations are facing high or very high risk of top talent leaving in the next year (Brandon Hall Group, HCM Outlook, 2024). Without a structured and ongoing approach to skills development, outsourced teams can struggle to keep pace, leading to inconsistent quality, reduced productivity, and higher turnover . During the webinar, 82% of attendees reported that current procurement practice restricts the value they can bring to their clients.

The key takeaway? Organisations that embed L&D into their operating models create more resilient, adaptable, and future-ready outsourcing workforces.

Challenges in Sustainable Learning for Outsourced Teams

The panel discussed the various challenges companies face when it comes to embedding learning into outsourced operations:

• Geographical and Cultural Gaps: How can we create a unified learning experience for teams spread across different countries, cultures, and time zones?
• Engagement and Adoption: With high attrition rates common in outsourced environments, how do we motivate teams to actively engage in learning?
• Measuring Impact: How can we quantify the ROI of learning programs in outsourcing partnerships?

What Effective L&D Looks Like in Sustainable Outsourcing

When looking at solutions for the challenges discussed, the panel noted the importance of centralised learning platforms that deliver consistent, engaging content to all locations. Platforms like Learn Amp help organisations create:

• Standardised onboarding programs to accelerate time-to-competence.
• Bite-sized, mobile-friendly learning content to fit learning into busy shifts.
• Social learning spaces that encourage peer-to-peer knowledge sharing.
• Data dashboards to measure engagement, skills development, and business impact.

Embedding L&D into Operating Models: 3 Key Strategies

Treat L&D as a Business Process, not a Project
Learning shouldn’t be an afterthought or an annual event. It needs to be a continuous, embedded process that evolves with the business and its outsourcing needs. 

Make Learning a Shared Responsibility
Learning success shouldn’t fall solely on HR or L&D teams. Operations managers, team leaders, and employees themselves all need to co-own learning outcomes. 

Measure What Matters
Sustainable learning models measure not just completion rates, but real business impact: faster onboarding; fewer errors; higher customer satisfaction; and improved employee retention. The LinkedIn Workplace Report shared that 94% of employees would stay longer if companies invested in their development. 

Key Takeaway

If there’s one key takeaway from the webinar, it’s this: sustainable outsourcing depends on sustainable learning. When organisations invest in embedding learning into every stage of the outsourcing lifecycle, they create an employee experience where team members thrive.

If you would like to access a copy of the recording it is available here: Webinar Link

The year ahead promises to be a turning point for customer contact. AI and automation are advancing at an unprecedented pace, yet businesses are facing economic uncertainty, rising costs, and rapidly shifting customer expectations. The pressure to adopt new technology and improve service levels means leaders must make bold, strategic choices.

At the end of 2024, we held our annual ‘Big Conversation’ to uncover key challenges for the year ahead and hear directly from cross-sector contact centre leaders about how they’re addressing them. These insights have shaped our latest whitepaper, 2025: A Year of Difficult Conversations?. In this paper, we explore those challenges in detail and outline priorities and solutions. One theme dominates: success in 2025 will depend on how well businesses navigate ‘difficult conversations’—both within their organisations and with their customer and suppliers.

How can you make the right tech decisions in the age of AI?

AI can be a powerful tool for improving operational efficiency. However, the reality is stark: according to Gartner, 80% of AI projects fail, which is twice the failure rate of non-AI projects. Despite this, the pressure in the boardroom to “do something with AI” is stronger than ever. The key question isn’t whether to implement AI, but how to do so strategically and safely.

When AI is implemented well it can deliver valuable results. But the risks of adopting this still fledgling technology can be significant—wasted investment, damage to reputation, and disruption to operations. The businesses that succeed with AI will be those that clearly define its use cases, align them with business goals, invest in high-quality, integrated data, and ensure that AI complements human expertise rather than replacing it. AI has the potential to be a game-changer—but only with careful consideration.

How do we meet economic, regulatory and resource challenges?

While grappling technology decisions, contact centres also face ongoing economic headwinds, regulatory challenges and a 15% decrease in headcount since 2019.

As businesses introduce new contact channels and explore innovative solutions, the fundamental customer need remains unchanged—a fast and effective response

But despite the rise in self-serve and co-pilot automation, customer satisfaction in the UK has declined. While automation is handling simple queries, agents are left to tackle only the most complex cases with fewer resources overall. Agents have little respite from more intense interactions and operations have fewer agents available. Even with future AI implementations, research predicts relatively modest headcount reductions of a maximum of 15%.

What’s more, in 2025, UK contact centres will need to absorb and manage an 8-10% increase in agent costs. Meanwhile the ongoing cost of living crisis means customers remain stressed and regulatory requirements add to operational demands —all against the backdrop of a muted growth forecast and ongoing economic challenges. No wonder things feel pressured.

Consequently, leaders are exploring various ways to optimise their service models, including offshoring, automation, or refining their approach.

 

Getting It Right: From Good to Great

One thing is clear. Transformation isn’t optional—it’s essential. The businesses that thrive in 2025 will be the ones that take a proactive approach. The most successful organisations will define clear, achievable AI use cases, align data, technology, and human expertise, prioritise governance, security, and compliance, and engage employees in AI adoption from the start.

The path ahead will present both opportunities and challenges, but with the right strategy, tackling today’s difficult conversations can pave the way for a stronger competitive edge tomorrow.

Read our paper for more detailed analysis of the challenges, but more importantly, how to tackle those challenges and put in place a positive programme of change.

The Whitepaper is free to download and immediately accessible below. We would love to hear your experiences too. Follow us on LinkedIn to share your thoughts.

In early February I attended the IP Integration “Spotlight” event at the Midland Hotel in Manchester where we were provided access to some great insights from the team and from Steve Morrell of ContactBabel, what follows are my thoughts and reflections arising:

Something around customer adoption of automated solutions has been playing on my mind, it often happens when I suggest someone talk to an automated bot solution so they can experience first-hand how far the technology has come, where it is going and what the real possibilities are.

Being in the CX world and having several partners on our network that have such solutions, I have a number saved to my phone, just for this type of conversation.  If I pull the phone from my pocket, find the number, dial it and hand it someone to have a conversation then I often feel that the “conversation” isn’t as free flowing as it should be.  Why? Well that is a great question.

I suppose it could be that for the past 15 years when contact centres have effectively forced customers to speak to automated voice response systems, we have typically limited customer so saying one word “listen to the following list of options and then say the option you would like” or “in a few words please say why you are calling today” so for years we’ve been saying ‘please speak to this automated system in a short staccato format’. Now, in a matter of a couple of years, some businesses are offering customers the opportunity to speak freely to their bots or automations, whilst others are still on the limited few words space. No wonder consumers get confused – and the acceptance and adoption of voice automation could well be held back as a result. 

Voice is here to stay?

The truth is that voice interactions are still our favoured route of contact as customers, when it comes to getting things done and obtaining reassurance that we’ve been heard.  Whilst the death of voice in contact centres has been forecast for the past 20 years, the reality remains that voice is here to stay, millennia of evolution cannot be undone so quickly. Data shared at our webinar on the State of the Customer Experience Market with David Rickard of Everest Group in November (article link) validated this, as their research highlighted that 72% of revenues amongst the outsource community were still coming from voice-based activity in 2023 when both agent supported voice and conversational AI driven interactions were considered.

The data shared in the room in Manchester by Steve Morrell of ContactBabel corroborated this view, with 64% of interactions being cited as voice in his forthcoming 2025 report. Also that we are so keen to ensure that we speak to someone that we will now wait in the longer queues that have been identified post pandemic and that we have accepted these as the norm.

So, as a human race we have a deep attachment to use of voice, however I’m still receiving articles daily which suggest otherwise – and ours is an industry which is based on employing people to talk to customers. We need to acknowledge that ‘the bots’ or automation is coming for our lunch, which according to an article in the New York Times on February 1^st it may however already be in a place to arrange someone to bring our lunch and where may that end?

An article by Kevin Roose details several tasks which he managed to complete using OpenAI’s Operator, a new AI agent in the week prior. Most of the tasks it did autonomously with minimal intervention. It met its brief of being an AI agent that uses the computer to accomplish valuable real-world tasks, without the need for supervision, to complete tasks in the background with a handoff back to the user to enter passwords or payment card details.  However, in Kevin’s article he talks of how it ordered lunch to be delivered to a colleague’s house and responded to LinkedIn messages well, up to the point where it started signing him up to attend webinars, amongst other tasks.  There were, however, several tasks where the automation struggled or needed an amount of reassurance or confirmations. Because of which he felt that it would have been faster to do the tasks himself, but acknowledged that the AI agent is at an early stage of development.

What we do know is that the evolution of technology is only gaining pace. Peter Diamandis, founder of the XPRIZE (https://www.xprize.org/) , is cited as having said in 2020 that “the next 10 years will bring more progress than the last 100 years” Given the pace of change in the past 5 years, it is reasonable to assume that Moore’s Law will hold true in this instance –  and that we need to be ready for this.

As humans we like voice, we choose voice. But if personal assistants in the form of OpenAI’s Operator or DeepSeek were to be adopted by the general public (your customers) to complete their home admin tasks, then these systems won’t have the same emotional connection to voice conversations and will be happy to interact directly with a company bot. However, how quickly will we reach that point?

Public adoption is key then?

We can implement the best solutions in the world, but if nobody uses them, what use are they?

Whatever is coming next, we have a dependency on customers to embrace and use those solutions, whether that is voice automation in the contact centre or the potential for the eventual use of “their own” automation by customers to engage with brands to resolve issues.

We’ve seen before conversations around ‘brand by-pass’. Now, using an Alexa or alternative voice-activated AI assistant to complete simple tasks is clearly the gateway to us getting to a point of asking technology to, say, engage with our utility provider to amend our direct debit or to find a cheaper insurance renewal.  At this point we as individuals will have less input to what brands we choose to purchase, so then the brands that will succeed are those that are easiest for our automations to interact with.

But before we get to this utopian vision of admin free lives with our AI assistants ensuring the effective running of our homes and lives, we need to pass a point of public adoption of AI.

A 2023 report from Ipsos shows that 66% of people they surveyed globally expect that products and services using artificial intelligence will profoundly change their daily life in the next 3-5 years. Whilst this is the average, the range of responses on a country and demographic level vary considerably, with the proportion expressing this belief in South Korea as high as 82%, whilst France sees the lowest number agreeing with this sentiment at 51% (we in the UK see 58% agreeing with this statement).

So, whilst there is broad agreement that services using artificial intelligence will change our lives, what people are willing to adopt and how is a key consideration, acknowledging that some will be unable to adopt due to a variety of reasons.

The conversation at the Spotlight event therefore quite naturally centred on work that could be done to implement changes or applications of AI to better support the contact centre agents in delivering service efficiently without too much impact to the customer, generating a series of marginal gains which support the agent in resolving customer queries, potentially reducing call durations and in turn queues and repeat contacts –  a series of win/win scenarios which:

• Improve service
• Reduce pressure on the contact centre team
• Reduce repeat contacts
• Reduce the time customers spend trying to get through
• Reduce costs
• Improve staff wellbeing

Changes which fulfil the appetite of businesses to implement changes and leverage AI, but consider how willing customers are to adopt these changes.

Is some re-programming required?

If we want the possible AI solutions to be successful, we will have to consider how we guide customers to use these solutions most effectively. Our industry has created a sub-optimal situation through a combination of poor customer experiences in the past, limited system capabilities and a “tell me in three words” approach. If we want customers to embrace the possibilities of technology, then we need to bring them on the journey.

Consider how self-serve check-outs have become the norm when we are out shopping in recent years . There is a journey that I’ve certainly been on to this point, which I discussed with IPI’s Sam Grant at lunch.

Coming prepared, we need our customers to come to the contact prepared to engage with AI.

Similarly, from prior experiences I soon learned that I need to stop putting my shopping bag in the bottom of my basket, then putting my items of purchase on top of it, which created friction in the process when I needed to get to my bag to enable me to pack items as I scanned them.  So, ideally, we need our customers to come to the contact prepared to engage with AI (unless they don’t want to?)

Offering a choice? Do I want to self-serve or would I prefer to queue?

When I’m approaching the tills, I can see a queue for a till with a cashier or I can see available self-serve checkouts. If I can also see someone there by the self-serve tills to support me, then I can make an informed decision.

Unexpected item in bagging area! Solutions need to be flexible enough to minimise friction.

That bag I just dug out from my basket, I’ve tapped that I’ve brought my own bag, but it is perhaps heavier than the scales expect, therefore I’ve got an unexpected item. I’m removing and resetting the bag but there is a red flashing light and now I’m waiting for someone to come help me.  We’ve all been there (please tell me this wasn’t just me!). The solution has now evolved, though, replacing scales either with additional trust by the retailer, or with cameras, but the result is a smoother customer experience.

Authorisation for purchase There will be times when someone must step in. If so, ensure it is done in a timely fashion.

OK I bought wine, it’s the weekend, please don’t judge me. The process to verify that I’m of age and can make that purchase has parallels also. We need to ensure that if a customer needs support then it is quickly available. Now I want those annoying flashing lights to flash brighter, because   I need help to complete my purchase.

How do you want to pay? Payments need to be frictionless, tap and go, no creased banknotes!

The same will apply to your callers they need to be able to make the payment without being moved to another channel and of course you need to ensure you are properly protecting that payment data.

Do you require a receipt? perhaps we need to acknowledge that customers will want validation of their conversation, of what was committed to and that they can trust that it will be done.

It has taken me a long time to reach the point of clicking no to a paper receipt. I want to be able to evidence that I’ve paid and not just walked round the shop popping things in my bag. Part of the reason so many of us are still reverting to speaking to a human when we have an issue, other than our lived experiences of trying to explain a complex situation in 3-word blocks, has to be that we can say “I talked to …. And he said he’d sorted it”.

What does it all mean?

People are complex. The implementation of self service and automation of the simpler query types means that average contact centre conversations are now much longer than they were and with rising staff costs there is a clear pressure on businesses to make changes to reduce customer servicing costs.

There is a broad spectrum of solutions available to support businesses address these challenges, whether outsource or technology. These need to be properly aligned to your objectives, and it is likely that you may need to speak with someone around how to select, prioritise and deploy these solutions.

If you need to chat then feel free to drop us a line.

Collectively Customer Contact Panel (CCP) have a lot of experience in contact centres and CX. However, as things are changing rapidly in the world of AI, we met with CCP to discuss some of the broader considerations, including what technology we could deliver as an alternative view of what could be our probable future reality with the support of AI – we agreed we would share the output.   

The art of the possible?  

We can talk about the pace and the tone of this piece, however the reality is that with appropriate questions raised and some boundaries that we included (some for our amusement) the content within this 10 minute AI generated “BotCast” not only demonstrates the capabilities of AI, but raises some interesting questions and considerations as to how CX evolves and what guard rails need to be in place.  

Click here and have a listen, and of course, if you want to discuss we’d be happy to deploy some of our humans. 

When you assemble a room of people with extensive levels of contact centre experience, as we did for our event hosted at Sutherland Labs, you know from the noise levels over coffee there are going to be some great conversations! Add some fantastic speakers from our outsource and technology networks to share their views of the market and a lively, open dialogue around challenges and opportunities (new and old) will follow.

We are looking forward to continuing these conversations and scheduling another event.  But in the meantime, how do we bring so much collective experience together in a short article that does justice to the quality of the conversations?

Navigating Business Decisions in a Rapidly Evolving Landscape

In the current environment, companies face a range of critical decisions, from implementing new technologies to fostering employee engagement. Despite knowing what needs to be done, many organisations struggle to translate that knowledge into actionable outcomes. This disconnect is often a result of inadequate systems, outdated training and coaching models, and an inability to adapt to change. 

In our recent L&D survey it was apparent that there is a clear gap between knowing and doing.  Results show that while employees understand their roles, there’s a significant disconnect between knowledge and execution. This is particularly evident in how businesses approach training, often relying on outdated, “once-and-done” programmes that fail to evolve alongside the changing work environment. As companies shift to remote work, many are noticing a reduction in employee loyalty and engagement, partially because of the lack of in-person interaction and relationship-building.

Addressing the Changing Needs: Evolving Training and Technology

To bridge this gap, organisations must rethink how they train their employees, particularly if they are to continue with a work from home or hybrid working model. Has enough been done to redesign training and refresher modules that better fit a virtual environment? Equally, more needs to be done to focus on continuous education rather than static, one-time courses which tick a box for compliance. Furthermore, conversational AI can be a powerful tool in reshaping learning; allowing employees to ask dynamic, evolving questions rather than relying on predefined solutions.

AI offers the potential to unlock the true capabilities of people and data, but as we have said before is not a silver bullet. It can revolutionise business processes by supporting employees in their roles, reducing friction, and enhancing decision-making. AI can also help agents manage customer queries more efficiently, giving them access to foundational knowledge in real-time. However, the challenge lies in positioning AI correctly: not as a threat to jobs, but as a tool for augmenting human capabilities.

For example, AI’s ability to analyse customer intent and apply insights to guide agents through complex interactions can dramatically improve customer experience (CX). By properly integrating AI into business workflows, companies could potentially resolve the eternal challenge of moving from being seen as a cost centre to profit centre, unlocking new value opportunities across the customer journey.

Location strategy is still a consideration as the global market evolves. The outsourcing industry, particularly in sectors like fintech, IT support, and healthcare, appears poised for significant growth.  We know countries such as South Africa have already emerged as strategic hubs for business services, offering talent and capabilities that align with the growing demand for multilingual and technologically adept service providers. Whilst there are valid concerns as to the capacity that remains available, with 33% unemployment in South Africa (60% for young people) as well as the wider continent opening for business, then combined with the capabilities of technology great opportunities remain available.

Overcoming Challenges in AI Adoption

While AI presents numerous opportunities, it also comes with significant challenges. Many process owners may be hesitant to adopt AI due to concerns about how it will impact their workforce and customer relationships. Meanwhile, senior leadership may be focused more heavily on the potential cost saving benefits.  There’s a widespread misconception that AI will replace jobs, particularly in customer service. However, AI’s true value lies in assisting and enhancing human roles, not replacing them.

For businesses to adopt AI successfully, they need to:

• Align AI with company goals and culture: AI should be seen not as a technology investment, but as a strategic asset that drives both customer and employee experience.
• Shift from a cost-saving mindset to a value-driven approach: Technology shouldn’t be about cutting costs; it should unlock value, address problems at their root cause and improve service quality.
• Build the right business case: Secure buy-in from different budget owners by emphasising how AI can enhance outcomes across the organisation.

Aligning Metrics and Culture for the AI-Driven World

To fully leverage AI’s potential, cultural and operational changes are required. Business leaders need to:

• Align metrics with an automated world: Ensure that technology handles routine tasks, allowing people to focus on complex, human-centric work.
• Redefine the agent role: The agents of the future will need to deliver more value and possess different skills compared to traditional customer service roles.
• Foster a culture of continuous improvement: Embrace ongoing evolution, where AI serves to complement human skills and free up time for higher-value tasks.
• Focus on proactive engagement: Let technology handle the repetitive, allowing people to engage with customers in a more meaningful way.
• Encourage bravery in decision-making: Leaders must support bold decisions around AI investment to drive long-term success.

Irrespective of delivery location, the future of CX delivery will increasingly rely on AI and automation to enhance customer journeys, optimise operations, and drive sustainable growth.

Transformation is never-ending. Businesses must approach AI and automation not as one-time projects but as ongoing evolutions. This requires understanding the unique challenges they face, aligning technology with business goals, and ensuring that AI enhances rather than replaces the human element.

With the right strategy, AI can unlock unprecedented opportunities for growth, helping companies stay competitive in a rapidly changing world. However, without the appropriate attention to employee experience, success will be illusory or limited.

Delivering the right experiences

At Customer Contact Panel we support organisations in delivering contact centres that match their ambitions. In a Deloitte Digital research articles from May 2024 it was cited that 55% of contact centre leaders reported that they didn’t meet their strategic goals in 2023 and 76% reported that their agents were overwhelmed by systems and information*.

If you are facing challenges meeting your strategic goals or fulfilling the ambitions you have for your people, customers or technology, we have the experience to support you. Just ask. 

*Balancing priorities in a new era of contact center transformation – Deloitte Digital

Like it or not, AI is coming and it will change how we talk to customers. But there are risks. What if those customers are vulnerable? Can AI look after them properly? And while we’re thinking about vulnerability, as AI increasingly consumes customer data, what needs to be done to look after that too?

On June 25^th Customer Contact Panel hosted an event with CXReview at the IBM Innovation Studio in London on this very topic. Speakers included Gemma Woodcock of IBM, Jim Steven of Experian, Elaine Lee of Reynolds Busby Lee and Keith Shanks of CXReview.

Steve Sullivan of CCP was master of ceremonies and led the discussion.
Here we outline the key takeaways from all speakers for what we can do right now to mitigate those risks and set contact centres on a path to responsible use of AI. 

Contact Centre AI: Not if but when

• The event focused on: Outlining the risks and considerations when implementing AI and automation, and
• The adoption scope within the Contact Centre environment, specifically supporting agents to deal with the ‘cognitive load’ when handling vulnerability and more challenging customer contacts, whilst maintaining quality and overall customer experience.

While there was much discussion around Al, Generative AI and the inevitable impact on our roles, we are still a long way from a time where agents will not be required in customer contact; we’ve evolved too far as humans for this to change. However, ignore AI at your peril. 

“Consider those that did not take the internet seriously, those on the high street who failed to embrace it and look at what happened to them”

Gemma Woodcock of IBM

The AI data question

Ultimately the use of AI depends upon building models that can make predictions that add value. These are dependent on what the source data looks like. Ensuring correct identification and use of the right material is essential; wrong information can lead at best to incorrect responses and at worst to biases or hallucinations, all of which carry considerable risk to brands and their customers.

Consider also that using the questions that your customers ask you to inform future responses may not be typical – for example they may have arisen from an unusual event at a specific point in time – and if you treat them as such, this may lead to incorrect or just plain weird future responses. . Moreover, if the answers to those questions relate to your own IP and you are using open-source solutions, you may be making your IP available to others.

Additionally, who you are sourcing your solution from needs to be considered. In March 2023 alone there were 14,700 start-ups established in the AI space. Which means due diligence and an understanding of how AI solutions, which are often highly specific by nature, work together is essential.

That isn’t to say everything in AI is new. The early concepts and mathematics of AI date back to the 1950s and 60s. Over the last decade or so, increases in computing power have begun to make AI more commercially accessible. Which means AI and machine learning is already well-established in using models that look at patterns, as we’ve long since seen for Amazon purchase recommendations, or in more recent years the introduction of machine learning and explainable AI in credit scoring.

As is often the way with AI, these are specific use cases with an enormous amount of investment behind them to make them function well, particularly to allow for the use of AI in regulated industries. One aspect of these is that they depend on properly labelled data. Which is already well-ordered and highly specific in the world of credit risk. But the process of labelling data, especially data that isn’t already extremely well-ordered, is intensive and expensive.

Imagine then the complexities of labelling data in natural language usage and you begin to understand the significance of recent advances from the likes of IBM’s Watson – or the oft referenced ChatGPT – in Generative AI. In customer contact, these are what we call “foundation models”. They are pre-trained and need prompts, but can’t answer questions specific to your customers without customer data and an understanding of how customers are likely to interact. These large language models can be applied to this process – they can use

labelled data and the numerous ways to ask the same question in the past to develop further to meet your and your customers’ needs.  

4 key tests for effective AI

The use of Generative AI should have 4 key considerations:

1. Open: use of best technologies and innovation
2. Trusted: can you trust the outputs
3. Targeted: designed on specific use cases
4. Empowering: ability to augment the human role/experience, not to replace it.

Pretraining and governance funnels need to be in place, with considerations ranging from the benefits of the use case to ensuring only the necessary inputs go into the model. Put simply, if nothing “inappropriate” goes in, then nothing inappropriate can come out. Additionally, this approach means it should cost less to set up the model and take less energy (power) to run. Remembering just how energy intensive AI can be, this is an important consideration.

When it comes to Risks, Regulations, and Technological requirements, there needs to be a level of governance. And during scoping of your solution, you need to consider the ongoing effort required to support it to ensure it meets – and continues to meet – strict governance. AI is not a fire and forget implementation.

AI and the bad guys

“It isn’t only the good guys that are using AI and Automation, ‘mal-actors’ are using it to enhance their processes too.”

We were fortunate to be joined by Jim Steven of Experian who shared with us some of the activity he has seen from his work in managing data breach responses. This has implications on multiple levels.

• Consolidation of data: bringing everything together to enable automation could mean that you are at greater risk if your business is breached. Additionally, using suppliers with cloud-hosted data may mean that their breach becomes your breach too.
• Benefits of automation are not exclusive to those doing good: we are not the only ones that can leverage great technology. Those with mal-intent are using it too; and they will typically do so more quickly.
• Consideration of how those impacted by a breach find the experience: when a breach occurs, it is likely that it will be across your entire estate of stakeholders. Therefore, it is not just your customers that will be impacted – it will also be employees, former employees, pension members, contractors and suppliers.

Communication with people who have had their data compromised is personal, it needs to be managed in different cohorts and isn’t really something to automate – especially with your employees, who you will need to support your customers through the situation with empathy and understanding. Not only that, but it’s important not to lose sight of the millions of customers who don’t currently interact online at all – they aren’t typically digitally savvy and may not even consider that their data is an important asset that can be used for nefarious means.. They must  be informed and supported in ways that work best for them, cognisant that it is us who hold their data digitally.

Moreover, data breaches are not always one way – it’s not always about theft or ‘acquisition’ of data. Looping back to the theme of ensuring that you consider what data is held in the system for interpretation, bear in mind that even the simplest upload of additional data to your systems can impact operations. For example, there was an accidental, entirely innocent, upload of bad data to air traffic control systems in 2023 that resulted in 98% of aircraft being grounded.

People accessing and uploading bad data to your network could equally paralyse your organisation. Be mindful that centralising your information management may enable system vulnerabilities that could be exploited.

What about vulnerable customers and AI?

Elaine Lee joined us to speak about vulnerable customers and the need to ensure that we are considering them in our approach to technology and process solutions.

“40% of Companies are not doing well enough when identifying and supporting vulnerable customers.”

The FCA considers 52% of UK population to be vulnerable. The impact of the cost of living crisis on the UK population is that 25% of adults now have low financial resilience and the drivers of vulnerability are varied, including:

• Health
• Capability
• Life Events
• Resilience
• Equality
• Access

Remember, vulnerability isn’t static. We may be displaying vulnerability and require additional support today, but not in a few weeks’ time.

With 40% of companies already not doing well enough when identifying and supporting vulnerable customers, how will the introduction of AI affect those customers? Of course, there is a spectrum of risk. So it’s important to understand who and where your customers are on that spectrum at any given time, and the potential for harm – understanding what they are vulnerable to?

People may also be vulnerable through lack of access or confidence with digital tools, they may be under pressure financially through the continuing cost-of-living crisis or low financial resilience, they may be experiencing a physical or mental health condition or going through a life event that changes their ability to make decisions in the usual way.

When implementing changes, ensure that you have properly tested your solutions to work effectively for vulnerability. Use diverse customer panels and map the possibilities for different customer types. The effort needed to get it right does have a financial impact on your business, but if you succeed it will reduce customer complaints, increase engagement and therefore increase customer value.

Use cases and how to implement AI safely in Contact Centres

CXReview’s Keith Shanks rounded up the presentations with a reminder of the history of automation and AI use in contact centres. He highlighted the predictive dialler as being a key example of great technology that when implemented either badly or with mal-intent, has negatively impacted consumer perception and experience.

“Automation in Contact Centres: It isn’t new. It’s been around for years with mixed results through implementation.”

Due the nature of the customer contact operations, there are plenty of use cases that can be considered for development and implementation.

• Ensuring consistency and pace
• Automation of decision making
• Increased accuracy
• Assisting agents in dealing with complex customer contacts
• Enabling access to the right information at the right time.

However, we need to be cognisant of the potential challenges and ensure that these are properly addressed.

• Data privacy
• Security
• Vulnerabilities of both organisations and individuals
• How we ask our people to engage with the use of technology

With great opportunity comes great responsibility

If you would like to discuss more around how you are implementing AI and automation within your organisation and what it may mean to your people, customers or processes, then please contact the team.

Additionally, we are able to provide access to content from the day if you would like to read further.