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.

At Customer Contact Panel (CCP), we’ve witnessed first hand how these factors are influencing decision-makers, especially CX leaders and CFOs. If you’re in the midst of making an outsourcing choice, you’ve probably got one of the following on your mind. 

Growing Customer Demands: Meeting High Expectations 

It’s not just about answering calls anymore. Customers want fast, personalised, and empathetic interactions that feel seamless and aligned with your company values. This means businesses must be more careful than ever when choosing an outsourcing partner. A BPO’s cultural fit with your company is crucial—they need to speak your tone, align with your brand, and uphold the level of service your customers expect – all of which take time which you don’t have. So, companies are scrutinising potential partners more closely, ensuring they’re a perfect match. 

Technology: The New Wild Card 

Right now, you’re being asked to do more with less or deliver a better service with the same budget. With inflation, high interest rates, and currency fluctuations, offshoring doesn’t feel like a financial guarantee anymore. Add in automation—think AI tools and chatbots – and CFOs are starting to wonder if tech could be the silver bullet to that beast of a budget. Whilst AI and Automation can scale fast, they can come with hefty initial costs. Businesses are now weighing their options: 

1. Do they stick with outsourcing (onshore, nearshore, or offshore)? or
2. Do they double down on tech?

It’s a tough decision. Get it right, and they could boost customer loyalty; get it wrong, and it might lead to a backlash.  

ESG: Outsourcing in a Politically Charged World 

Outsourcing is no longer just about cutting costs; it’s also about navigating complex ethical and political waters. With Keir Starmer pushing for stricter ESG (Environmental, Social and Governance) standards, businesses are questioning their outsourcing partners, especially if those countries are known for poor labour practices or environmental issues. Throw in political instability and outsourcing now feels like a risky gamble. Operations could grind to a halt at any time, and businesses can’t afford that. 

On top of that, data security is tighter than ever. With the UK government’s more stringent regulations, especially for industries like finance and healthcare, outsourcing is becoming bogged down in compliance red tape. A single data breach could ruin a brand’s reputation and customers’ trust—so finding a partner who understands data security is more important than ever. 

Lastly, with the UK’s £22 billion budget shortfall and a focus on reshoring jobs, companies are balancing cost savings against their political and ethical responsibilities. 

How CCP Makes Your Life Easier 

At CCP, we get it – outsourcing feels complex. But we’re here to simplify it for you. We help businesses make smart, informed and equitable choices through services such as: 

• Partner Matching: We connect businesses with a handpicked network of pre-vetted outsource partners (220+ partners infact), cutting down on the time and risk of finding the right partner.
• Cultural Fit Analysis: We ensure your outsourced team aligns with your brand’s values and service style, so there’s no misstep in tone or approach.
• Technology Sourcing: We know how difficult it is to cut through the sales patter and find the right tech for your customer contact needs. Well look no further, we have a network of 120+ pre-vetted and audit technology partners – who will get right to the point.

The Bottom Line 

Outsourcing decisions are taking longer now because the stakes are higher. Customers expect nothing less than excellent service, and businesses are being much more careful about who they partner with. But with the right approach, outsourcing remains a powerful tool. 

At CCP, we guide businesses through the process, ensuring they find the right fit, reduce risks, and build lasting partnerships. In fact, 93% of CCP’s clients maintain long-term relationships with their outsourcing providers – proof that our approach works. 

With CCP by your side, navigating the increasingly complex outsourcing landscape is much smoother, helping you make the right decisions for today’s customer demands and tomorrow’s success. 

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. 

Since the launch of ChatGPT and subsequent proliferation of AI-driven technologies across the customer contact technology landscape, the pace of change has accelerated exponentially. From communication analytics, quality management and agent assist, to replacing IVRs with their omni-channel equivalents and real time translation services, the impact of AI on our industry has almost been as big as the invention of the telephone itself. Not only is this a source of organisational stress, are there implications for outsourcing and contract mechanisms?

While the telephone fundamentally changed human-to-human communication, AI technologies are transforming human-to-machine interactions. And given how we now communicate with each other, that can only mean that change is both permanent and ongoing.

This permanent change is putting increasing stress on organisations to restructure how they equip themselves to communicate with both their customers and their target market, irrespective of the sector they operate in.

We are seeing organisational stress in three areas:

1. Understanding the impact of these changes across the customer and target market demographic
2. Properly evaluating the ability of existing technology platforms to accommodate change and realign to new communication paradigms in the mid to long term
3. Fully understanding the mid to long term commercial impact of bolt on technologies to deliver short term performance and cost reduction gains.

In helping organisations cope with these stress areas we see striking parallels to the changes seen when organisations first began to interact with customers remotely. The evolution which began in the 90s to get more value from data, media and communication spend resulted in specialist operational activity often being outsourced as few organisations had the specialist people, process or technology to support those functions as cost effectively as outsourced providers could.

As customer became core to operations and remote customer management became an operational necessity, organisations began to establish their own capabilities, leveraging existing data management infrastructure to control and drive insight. Customer contact levels boomed, the technology to enable customer contact saw similar growth and our industry was born as more organisations grasped the benefits of controlled and managed remote customer contact.

Considering those parallels, we ask “Should organisations be stressing themselves or does that same customer contact outsourcing industry ‘muscle up’ for this second cycle of permanent change to reduce organisational stress in the shape of Outsourcing 2.0, underpinned by end-to-end AI driven technologies and the accelerated levels of operational insight that provides?”

Observing change in the global customer contact outsourcing market

Outsourcing is a very broad church. Our global network of two hundred plus providers gives us a privileged view of the diversity of the services provided, service delivery and how services are contracted. Whilst industry pricing has generally reduced in real terms over time, the way that service pricing is presented has not really evolved that much, it has not been that complicated, clients have had a choice of:

1. straight hourly rate,
2. the hourly rate with outcome components,
3. outcome with activity components and
4. outcome alone.

Making money has not been that complicated either. As long as the effective revenue per hour outweighed the total known costs per hour, then outsourcers made money.

The outsourcers’ challenge has always been about packaging service and price to be more attractive than the nearest competitor. Of course, that global mind set has led to an incredibly diverse and attractive industry offering, but it is doing little to relieve the level of stress we see in organisations today. Especially as permanent change begins to impact on mid to long term business performance forecasts.

What we see in the global outsource community is the emergence of some clear lines of distinction between service offerings. Principally between those that have the capability (or plan to have the capability) to relieve mid to long term organisational stress and those that don’t. Whilst those customer contact outsourcers that don’t have (or don’t plan to have) this capability to de-stress, continue to be well placed to solve organisations’ immediate and short-term challenges, we have seen some significant levels of technology and skills investment towards an Outsourcing 2.0 capability, amongst those that can.

What we are not seeing enough of is an evolved, Outsourcing 2.0 contracting proposition. One that is equitable for both parties. A simple contract proposition that provides an upside for the technology and skills investment of the outsourcer and in return, long term risk and cost reduction for the client.

Striving to deliver an equitable position to accommodate permanent change

1. know more about how changes in customer contact are going to flow through product and service delivery,
2. be able to make active decisions on what those changes mean in terms of risk and profitability,
3. identify service solutions that will de-risk their journey to deliver customer contact at lower cost,
4. deliver value and benefits that justify the time, cost and effort in enabling process change
5. potentially deal with specific customer use cases where they do not have the physical capacity or technical capability,
6. do all this without compromising service delivery in terms of quality and data governance i.e. the regulatory and contracted controls supporting data privacy and data security.

We also recognise that the world of customer contact tech is changing faster than it probably ever has; and it’s hard to tell what the next few years will bring in terms of time saving and service enhancing technologies.

SaaS based technology is easier to deploy, easier to recognise ROI, is already impacting on the flow of low complexity tactical work into the global outsourcing industry. This trend is also evidenced by more work. being delivered via the client’s own technology, enabling them to leverage their existing back-end systems integrations and continue BAU without interrupting the established end to end data flows supporting their existing operational reporting and decision-making processes.

Whilst the outsourcer community is continuing to strive to deliver uncompromising value, to positively impact  service delivery and comply with regulatory and contractual data governance, there is clearly an acknowledgment of the impact that customer contact automation brings to their core market.

Contracting to deliver mid to long term value by de-risking the transition to a permanent change in customer contact

Global outsourcing capability now has a firm dividing line across it. Those that have (or plan to have) the infrastructure and technology to deliver permanent change (2.0) and those that have not.

For those that have (or plan to have), we can see the opportunity for a new type of contracting relationship with clients. A contracting relationship that:

1. de-risks the client from the turbulence of technology change whilst delivering the permanent changes we see in human communication and the impact that has on customer contact service delivery,
2. will enable the outsourcer to deliver appropriate levels of automation without compromising the clients service objectives and targeted cost reduction when expressed as simply as a ‘cost per customer per annum’.

In the context of customer contact, clients find the idea of managing permanent change, de-risking the potential downside of getting that change wrong and doing that at a fixed and reducing cost very attractive. Especially when that contract properly considers how service quality is measured and underpinned as well as being directly linked to cost.

There are then two big variables in the client conversation that are both fundamental to a new contracting proposition.

One is the composition and contracting position of the legacy technology overhead that delivers existing levels of customer contact, especially how that customer engagement technology stack is connected into the ‘back office’ technology of the organisation.

The second is about existing costs. This is the client’s understanding of their current cost of managing their customers. Specifically, how that’s calculated especially in the context of a desire to express that as a ‘cost per customer per annum’.

Recognising the barriers to change

It is easy for us to oversimplify what we see as a new contracting paradigm. But we also recognise that the old contracting models don’t proactively and deliberately reduce the organisational stresses that put mid to long term business performance at risk.

Of course, some business verticals carry significant levels of technology debt. However, unless we explore, and explore deeply, what the possibilities are, then the weight of technology debt will drown organisations and fail as a lifejacket to guarantee ongoing survival.

Unless your technology is able to destress your organisation now, then the same technology stands little chance of keeping you afloat in the mid to long term.

Customer communication and customer contact management has changed permanently and is different from customer contact pre-the explosion in generative AI. This means new risk and new levels of risk for both client and the customer contact outsource communities. Our view is that contracting between the parties needs to change fundamentally.

Outsourcing 2.0 offers a mid to long term view of how both client and service provider can benefit whilst reducing risk on both sides. By looking at contracting differently, both parties can focus on their core strengths and experiences to set and deliver against service goals and commercial objectives. To do that mutually establishing, expressing and agreeing the existing technology stack directly supporting customer engagement and the cost per customer per annum to deliver growth and service objectives.

What next?

What are your thoughts on the future of customer contact outsourcing contracts? Do you think we’re thinking along the right lines, or have we underestimated the complexity of clients’ current position, especially in the context of technology debt? Whether you’re a client or service provider we’d love to hear what you think.

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.