Don't jump the Gen AI gun to realise returns on AI investments in the contact centre.

Don’t jump the Gen AI gun to realise returns on AI investments.

By Martin Cross, CTO at Connect.

Applying artificial intelligence (AI) in the contact centre has emerged as a prolific trend as the hype around Generative or Gen AI – the next iterative advancement in the technology – gathers pace.

Gen AI is a trending topic because businesses and consumers are captivated by the potential applications the technology holds in how the world works and engages, with the AI arms race between OpenAI, Microsoft, Google, and Meta escalating with the public release of platforms like ChatGPT, Bing Chat, Baard (now Gemini) and Meta AI.

In contact centres, the technology holds the potential to turn clunky chatbots into super-agents that deliver exceptional customer experiences 24×7, boost agent productivity, and drive business success by managing frontline engagement, offloading basic tasks from agents to boost contact centre capacity and first contact resolution (FCR) rates.

The technology can also boost agent productivity with automation, real-time guidance, and performance coaching and enhance operational efficiency by reducing costs, optimising resources, and enabling data-driven decisions.

Additional applications relate to better management and operational efficiency, supporting supervisors with AI-powered quality management or scoring and providing insights and recommendations for strategic planning.

Amid this hype, Chief Technology Officers (CTOs) feel pressure to invest in Gen AI in some form, with a BCG survey of over 1,400+ C-suite executives revealing that 89% rank AI and Gen AI as a top-three tech priority for 2024.

However, Gen AI is not a plug-and-play solution. It is costly and complex to build out Gen AI capabilities as creating the modelling needed to derive insights from AI engines is intensive, requiring scarce and expensive resources like data scientists and other technical experts. Moreover, businesses want virtual assistants and chatbots to engage with customers in a manner that reflects the business culture, which requires a human touch to design and refine.

In addition, the cost of delivering and supporting Gen AI capabilities is currently 20-30 times more than other AI models, and the processing power needed to run true Gen AI engines is enormous, which is why only the likes of Microsoft, Google (Alphabet), Meta and OpenAI can deliver these capabilities.

As such, the journey to Gen AI requires careful planning and implementation. The desire to leapfrog the AI lifecycle and invest in relatively expensive Gen AI capabilities without first putting the fundamental building blocks in place can result in unsuccessful and costly AI implementations.

Moreover, contact centre operators will fail to realise the full return on investment (ROI) in AI by looking to Gen AI to solve issues and challenges that basic AI, predictive AI and conversational AI can effectively address with lower cost and less complexity.

For instance, basic AI is adept at determining intent and finding and accessing relevant information from back-end systems to automate front-end engagement and offload repetitive, low-value tasks from agents to streamline CX and improve efficiency.

These AI models can also streamline data analysis in the contact centre, with the ability to rapidly process large sets of unstructured and inaccessible data in seconds to find patterns that help improve performance by informing data-driven decision-making.

AI-based decisioning can also field and prioritise inbound calls through intent recognition, which advances previous capabilities related to speech analytics based on exact phrases. By orchestrating first-line customer engagement with intelligent routing, the solution can allocate basic engagements and repetitive tasks to automated AI solutions like chatbots or conversational virtual agents.

In this way, basic AI augments the human role to support effortless experiences and handle higher call volumes by serving as an adaptive tool that helps to process calls faster, reducing average handling times (AHT) and improving FCR rates.

When used to augment the agent role, predictive AI provides the tools, insights and capabilities needed to help agents assist customers in the moment and address their specific needs and requirements with greater relevance and speed to boost customer satisfaction (CSAT) scores.

With the appropriate training, AI will super-charge live agents as they work alongside the technology in a manner that enhances their skills and empowers them with insights and intelligence to handle higher priority, more complex or sensitive tasks and engagement with customers.

AI-powered agent assist technologies can also understand the customer’s intent and context and leverage data analytics and big data to serve up relevant profile information, dashboards and historical interaction data to support agents in the moment.

By looking up appropriate responses within its knowledge base and delivering recommendations on the best actions to take next via the agent desktop, these solutions create super-agents and improve AHT to enhance CX and service.

Furthermore, applying conversational AI empowers chatbots and virtual agents or assistants to simulate agent conversations with customers, enabling them to actively respond to questions, queries and requests in real-time and in a way that feels natural and human-like.

Conversational AI solutions leverage natural language programming (NLP) to process and understand human language or text by recognising grammar, words and phrases. By linking to a Customer Relationship Management (CRM) application or other back-end data source, the system can anticipate a customer’s need and pre-empt a recommendation or response when engaging with a customer without sounding robotic.

As such, contact centre operators must acknowledge that Gen AI can solve certain challenges but does not yet have practical applications in every instance. Given the diverse applications in the business, AI strategies must consider which models currently offer the most credible cases for investment amid all the hype and excitement.

As such, the first step on the journey to advanced AI capabilities starts by defining the need and role that AI will play in the operation. It is critical to identify the relevant models to implement in areas where AI-driven innovation can drive RoI and deliver transformational benefits while mitigating the risks and inherent limitations that organisations face when implementing more advanced AI-based solutions.

Working through this needs analysis will reveal that Gen AI is not the most suitable solution to the business problem or challenge that contact centre operators currently face, with potential applications for other AI iterations potentially offering more relevant benefits and RoI.

Ultimately, if the requirement is simple, start with basic AI and build out your capabilities. Operators can then implement elements of each AI type and do not need to necessarily progress from one stage to the next in an iterative process.

Using a mix of basic, predictive, conversational and Gen AI in the right places will deliver the greatest RoI, particularly for those embarking on their AI journey.

Partnering with a business-outcome-driven, technology-independent expert in contact centre AI enablement can achieve similar outcomes that Gen AI can deliver today across various use cases at a lower cost using predictive and conversational AI.

As such, the potential exists to focus on building out basic AI capabilities within your contact centre operation to cover 80% of your requirements, with a Gen AI strategic roadmap in place for the other 20% of AI-enabled engagement to create an optimised cost model and future-proof your operation as Gen AI gathers pace as a transformative trend in the contact centre industry.


Connect combines global contact centre and customer experience (CX) expertise, deep domain knowledge, and unparalleled industry skills to make the complex, simple. Since 1990, we have leveraged our vendor-independent managed services approach to digitally transform how organisations communicate, both internally and externally. We specialise in combining the most relevant technologies and services from leading vendors and platform providers to create opti-channel engagement solutions, orchestrating frictionless experiences and simplifying complex communication challenges.

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