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Commentary

A.I. and Strategic Imperatives for BPOs: A Commentary

June 5, 2024

Executive Summary

BPOs need to integrate AI into their contact centres to remain competitive and harness new growth opportunities. Although the adoption rate of AI in the sector varies, its potential to transform the BPO industry is significant. Additionally, Contact Centre as a Service (CCaaS) providers are rapidly advancing their AI capabilities, posing a substantial threat to traditional BPOs. CCaaS providers, with their technology-first approach, are becoming increasingly competitive by offering sophisticated and efficient AI-driven solutions. 

Without considerable expertise, it can be challenging to realise the high Return on Investment (ROI) that sophisticated AI solutions can provide, especially those designed to offer comprehensive coverage of customer queries and automate associated tasks. Key applications include Conversational AI, which automates complex customer requests, and agent assist tools that boost efficiency with real-time recommendations. Sentiment analysis gauges customer emotions to improve responses, while text analytics help analyse interactions for continuous improvement. These technologies have the potential to enhance revenue, customer satisfaction, and even agent experiences.

Despite significant advances in Large Language Models (LLMs) and the user-friendly interfaces of tools like ChatGPT, substantial expertise in AI remains necessary to automate customer service at scale, handling complex use cases in depth and supporting a broad range of scenarios. Implementing AI solutions requires more than just investments in technology; it also demands significant investments in upskilling employees to ensure these systems are designed, configured, and operate optimally. Integrating AI into clients’ existing systems and customising these solutions to meet specific needs requires deep expertise in customer service automation. As the market evolves rapidly, it becomes increasingly difficult for companies to build specialist in-house teams. Therefore, leveraging advanced solutions from specialised providers is essential to address the intricate demands of modern customer service automation.

To stay competitive, BPOs are pursuing strategic partnerships and acquisitions to gain advanced AI capabilities. This approach enables BPOs to automate legacy operations, drive substantial growth, and achieve significant returns on investment. Additionally, there is a vital need to invest in comprehensive AI training, to diversify service offerings to include AI consulting and support, and to redeploy human agents towards high-value services that require human oversight.

Embracing AI is essential for market leadership and long-term success. By leveraging AI’s disruptive potential to drive growth and innovation, strategic AI integration can enhance productivity, expand service offerings, and improve customer experiences.

AI Transformation in BPOs and Contact Centres

Challenges to AI Adoption:

The adoption of AI in the BPO customer service sector has varied, with some companies making significant strides while others lag behind. Despite this slow start in some areas, AI holds enormous potential to reshape the BPO industry. As Michaela Goss and Robin Gareiss, CEO of Metrigy, note, “AI is not new to contact centres, but BPOs that invest in newer technologies often have happier agents, leading to happier customers.”

BPOs Can Become Trusted AI Advisors:

BPOs should prioritise AI investments with the vision of becoming trusted advisors on AI strategy for their clients. The successful implementation of AI solutions for both themselves and their clients would do much to underscore their expertise. As Gareiss states, “That gives them a lot of the experience internally — like ‘Hey, we’ve done this not only for ourselves, but for our clients.’ And it really gives them that foundation for digital transformation.”

Utilisation of AI in BPOs:

  • Conversational AI: Automates customer service queries via voice or text channels. Unlike traditional chatbots and FAQs, Conversational AI can handle complex interactions, providing personalised and context-aware responses and actions that significantly enhance customer experiences.
  • Agent Assist: Enhances agent efficiency with screen pop-ups, sales suggestions, and next-best-action recommendations.
  • Sentiment Analysis: Uses natural language processing to gauge customer emotions and contextualise agent responses.
  • Text Analytics: Helps agents quickly search organisational data and analyse interactions for continuous improvement.

Pros and Cons of AI in BPOs:

Benefits:

  • Boosts revenue and customer satisfaction.
  • Delivers higher profit margins.
  • Enhances digital transformation strategies.
  • Supports existing agents by freeing up time and improving agents’ experiences.
  • Increases understanding and analysis of customer data.

Challenges:

  • Need to upskill existing employees to make best use of AI solutions.
  • Higher investments in AI and automation technologies.
  • Integrating AI with clients’ systems.
  • Customising AI solutions to meet specific needs.

Opportunities for BPOs in AI Integration

Enhancing Productivity with Sophisticated AI Solutions:

AI can significantly enhance call centre productivity by automating the handling of many customer service telephone calls, leaving agents free to manage more idiosyncratic and specialist calls. AI tools have an enormous potential to reshape the BPO industry by boosting efficiency and transforming operations. However, much of this potential remains untapped.

The implementation of AI solutions requires considerable expertise if high levels of automation and ROI are to be achieved. Sophisticated customer service automation solutions can support the full scope of queries and tasks, not just a small subset of simple ones. This comprehensive approach not only boosts efficiency but also improves overall service quality by ensuring that human agents are available to handle more idiosyncratic or high-value interactions. However, only a few suppliers can command high levels of ROI because of the expertise required.

Conventional AI platforms for automated customer services, like Google’s Dialogflow, are often inadequate to meet advanced needs. Additionally, new generative AI models require substantial expertise and additional, supporting layers of specialist software for commercial use. Solutions from dedicated Conversational AI specialists, both from established players and start-ups, can ensure data privacy through careful and considered deployment of Large Language Model (LLM) powered solutions on-premise. Although many Conversational AI companies claim to offer these capabilities, truly capable suppliers are rare.

New Service Offerings:

Automated solutions built using common platforms like Dialogflow can’t handle the majority of incoming customer queries due to their limited functionality in understanding, resulting in significantly lower automation levels. While these services can provide modest ROI given the investment, their breadth and depth of automation are distinctly inferior compared to more sophisticated solutions. The demand for AI-related services in call centres is growing, but tools like Google Dialogflow and IBM Watson are designed to accommodate engineers with limited AI expertise who want to create automated solutions. As a result, mainstream tools are simplified and unable to adapt to the full range of user queries and actions supported by contact centres.

For sophisticated support solutions that offer high ROI, deep expertise is essential to adapt, implement, and manage AI. Given the rapid market evolution and the shortage of skills, building in-house AI development teams is nearly impossible for a BPO. An expert team is required, not only in AI but specifically in advanced Conversational AI techniques. According to the Financial Times, the near $500 million valuation of PolyAI highlights the market’s confidence in scalable, specialised AI solutions from specialist providers. Other companies like action.ai are also emerging as key players, offering the same advanced capabilities tailored to specific BPO needs.

Competitive Edge Through Economies of Scale:

The right AI customer service applications, once perfected by an experienced team, can be efficiently scaled across multiple clients within the same domain. This has the potential to substantially reduce call centre labour costs. Such scalability promises BPOs a significant competitive edge serving multiple customers of the same type. PolyAI’s success, backed by significant investments, underscores this potential. “Hyper-automation leads to increased operational efficiency, generally improving customer service and reducing costs of legacy processes,” notes a Gartner survey, highlighting the strategic importance of AI.

Strategic Recommendations

Acquire AI Skills through Strategic Partnerships and M&A:

Developing AI capabilities in-house is expensive and time-consuming, putting companies at a competitive disadvantage. It requires recruiting and training a specialised team to solve specific problems seen in Conversational AI application design. These challenges are substantial at both a semantic processing level and at a speech interpretation level, even for AI experts without specific expertise in Conversational AI. Even the smallest bot demands a significant amount of work to ensure it can extend its understanding as more functionality is added. Conventional bots are faster to create, but they fail to scale well when additional functionality is needed to support more user queries and tasks.

Acquiring AI-focused companies, on the other hand, enables the rapid integration of advanced solutions. They can provide BPOs with full control and seamless service integration without the extensive time and effort required for in-house development. “Strategic partnerships and acquisitions will be key in bringing AI capabilities quickly and effectively into BPO operations,” says Neeraj Manik from IBM Consulting.

Invest in AI Training and Development:

While acquiring AI capabilities, BPOs should invest in comprehensive AI training programmes to upskill their workforce. AI solutions have the potential to make contact centre employees more productive and effective in their roles, while substantially reducing the number of repetitive calls they need to answer. This investment ensures effective management and optimisation of AI tools and leaves staff free to handle the more complex, specialised, and rewarding queries at which they excel. “Automation creates a chance for upskilling in outsourcing organisations, enhancing job satisfaction and reducing attrition rates,” emphasises Nick Jiwa, highlighting the human benefits of AI integration.

Diversify Service Offerings:

BPOs should include AI consulting, implementation, and support services in their offerings. This diversification positions them as essential partners for businesses integrating AI into their operations. Vitally, such diversification is crucial to developing and growing new revenue streams. “Outsourcing firms must become strategic partners capable of delivering transformational digital solutions,” states Kendra Gaffin.

Focus on High-Value Services:

Shifting from simple, repetitive tasks to complex, high-value services requiring human oversight helps BPOs maintain relevance. Emphasising sophisticated NLU-based chat solutions and high-value automated call centre solutions ensures sustained growth and client satisfaction. “AI-driven analytics provide valuable insights into customer behaviour and preferences, enabling more personalised service delivery,” notes Paul Nicholas Soriano.

Insights from Rickard David:

Generative AI is significantly transforming the customer experience management (CXM) landscape, leading to concerns about declining revenues and increased costs for traditional contact centres. According to Rickard David, over the last 12+ months, the stock performance of nearly every publicly traded CXM service provider has dropped dramatically due to market nervousness about how generative AI will impact the need for human-operated contact centres. Traditional contact centres have built large workforces and real estate portfolios. The expectation that generative AI will reduce the need for human agents and large real estate spaces risks increased exposure to real estate costs and potential revenue declines.

However, David highlights that many traditional methods of human interaction are still necessary for complex customer issues. Despite the rapid rise of technology aimed at reducing agent interaction, over 70% of service provider revenues still come from the voice channel. This demonstrates that customers still want to talk to people, especially for high-stress or complex problems. Moreover, leading CXM service providers are not standing still; they are heavily investing in a wide range of technologies to improve the customer experience and reduce the need for human-assisted contacts while making support agents more effective and efficient.

David also notes that many providers have reduced their real estate exposure through the increased use of work-at-home models. Enterprises are increasingly looking to service providers to support them in deploying technologies such as generative AI, which presents additional opportunities for providers who can demonstrate capabilities in this area.

Strategies for Enhancing CXM Provider Success:

  • Build Solutions that Address Business Problems: Solutions should go beyond generic goals like “reduce cost” or “improve CSAT” and address real business challenges where CX can drive significant change.
  • Demonstrate Differentiation: Providers need to show, not just tell, how they solve real business problems by combining human and technological solutions.
  • Build Strong Technology Partner Ecosystems: Partnerships allow providers to deliver comprehensive technology solutions across the customer journey.
  • Develop Flexible Delivery Models: Leveraging work-at-home, GIG, and Impact Sourcing models to meet changing demand.
  • Build Commercial Models that Benefit Both Parties: Move beyond traditional per FTE or per transaction models to ones that allow visualising and realising the value of a more efficient operating model.
  • Use Technology to Solve Operational Challenges: Invest in technologies and skills to address operational challenges effectively.
  • Develop a Culture Focused on Margin Over Revenue: Recognise the value of deploying solutions that may bring lower revenue but provide better and longer-lasting business benefits.
  • Be Forward-Looking with Skills: Build location and talent strategies to provide the talent required for the future.
  • Develop Strong Account Management Disciplines: Strengthen account management to differentiate in a competitive market.
  • Use Technology to Improve Employee Experience (EX): Leverage technology to remove mundane tasks, allowing employees to focus on value-adding work.

Conclusion

Acquiring AI capabilities through strategic partnering and M&A activity is crucial to maintain competitiveness and growth in the BPO sector, especially in call centre operations. By enhancing productivity, expanding service offerings, and leveraging economies of scale, BPOs can turn the AI threat into a huge opportunity. Public perception often assumes that successful automation comes at a detriment to customer experience. However, with the right tools and expertise, AI automation has the potential to improve customer experience. Effective automation means that customers can get what they need faster and at any time they want. And, with automation handling a large proportion of queries, if a customer does need to speak to a human agent, they will spend less time waiting on hold. Strategic investments in AI training, collaborations, and diversification will ensure the successful navigation of the AI revolution, helping BPOs to secure and expand their market position.

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