In 2024, generative AI is poised to redefine how businesses engage with their customers and streamline operational efficiency. We expect AI to not only automatically flag particular problems, but also to promptly resolve those specific customer issues. At the core of contact center transformation, generative AI is reshaping the nature of customer interactions, data-driven insights, and how agents are helping customers resolve their issues. 

Although we’ve seen AI create incremental changes in service, we’ve arrived at a pivotal moment where commonplace technologies like transcription and free text summaries are evolving into profound generative insights. A large share of agent tasks can now be managed through automation, and for those tasks requiring human intervention, AI stands ready to support and assist agents in their work. Fueled by capabilities now unlocked by generative AI, enterprises can improve contact center efficiency and reduce both direct and indirect costs through nuanced understandings that enrich data and unlock unparalleled value.

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To implement AI into their CX stack in 2024, enterprises must establish foundational building blocks, such as high-quality transcription, and get their data house in order before they can really take advantage of the benefits of AI.

– Michael Lawder, Chief Growth Officer, ASAPP, Former CX Leader at Apple, Samsung, and EA

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Lawder underscores the importance of laying strong foundations for AI integration. Building these blocks, including high-quality transcription and organized data, is pivotal to reaping the full benefits of AI in contact centers.

Anticipate these impactful trends shaping CX in 2024:

• Evolution of Text Summaries: From Extraction to Generation
• Unveiling Valuable Sentimental Customer Data
• Surge of Generative AI in Bots
• Blending Technology and the Human Touch 
• Ending Bad CX: Reconciling Cost vs Quality

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Evolution of Text Summaries: From Extraction to Generation

For years, the promise of automating summaries using AI to reduce Average Handling Time (AHT) seemed within reach. But the early AI models, mostly adept at extractive summarization, only provided contextual information from past interactions. While they lightened the post-call workload for agents, these summaries merely offered light context, necessitating manual review for additional insights and a clearer view of the full picture.

So, why will 2024 be the year of AI-driven text summaries?  Because the benefit shifts dramatically with the summaries created by generative AI. Unlike extractive methods, generative summarization not only includes pertinent conversation elements but also gauges customer sentiment. 

If your CX stack is integrated, then generative AI summaries can be customized based on factors like intent or agent groups. This means automatic categorization of complaint types and severity, identification of key issues, or post-launch focus on new product mentions becomes possible. ASAPP’s AutoSummary stands as a testament to this evolution, showcasing the transformative potential of generative AI in turning data into actionable customer insights.

To learn more about AutoSummary, click here.

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Generative AI will continue to deliver incremental innovation across GPUs, LLMs, and Compute frameworks. Data will dominate to be the biggest differentiator, applying LLMs in a hybrid domain focus to achieve accuracy, time to value and scale. These vectors coming together will be the key to unlock exponential value for enterprises.

– Priya Vijayarajendran, President, Technology, ASAPP

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Priya sheds light on the pivotal fusion of technology and data. This convergence across computational frameworks not only drives incremental innovation but also highlights the indispensable role of data in achieving accuracy and scalability. It's the synergy between Tech, Data and seamless orchestration connecting enterprise systems for business outcomes that unlocks exponential value for enterprises.

Unveiling Valuable Sentimental Customer Data

Training generative AI on a particular business’s customer conversations can identify unique pain points, understand satisfaction drivers, and strategically enhance the overall customer experience. At the forefront of this transformation is Sentimental Data. This data segment delves into human emotions, pinpointing areas of improvement that customers feel, providing a roadmap to elevate customer experiences to unprecedented levels. Let’s look at a few industry examples.

Using sentiment analysis in the travel industry can uncover customers’ emotions tied to hotel stays, flights, and destinations, guiding improvements. Apparel industry brands can understand customer reactions to their offerings. By decoding feedback from various channels, these companies identify trends and specific customer preferences, enabling targeted product improvements and personalized marketing strategies. 

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In 2024, more businesses will invest in leveraging AI and advanced analytics in order to create tailor-made offerings at dynamic price points and individualized levels of service.

– Forbes

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Sentiment data is also playing a pivotal role in telecommunications CX. Companies gain crucial insights into what delights or frustrates users by dissecting customer sentiments linked to service interactions, network experiences, and support encounters. Ultimately, this information empowers telecommunication providers to address pain points promptly, improve service quality, and tailor offerings to meet specific customer needs.

Surge of Generative AI in Bots 

Next year, we’re anticipating a significant rise in the utilization of generative AI in bots, with unprecedented low barriers to accessing this technology. The immediate potential lies in elevating bots to conversational entities and eliminating hurdles in understanding user intent, which allows seamless navigation through customer inquiries. 

Looking ahead, the evolution of generative AI involves integration with APIs for tailored responses derived from individual customer data. This could extend to bots understanding unique customer situations, departing from standard responses to offer personalized interactions. Ideally, generative AI bots not only achieve this but also autonomously act on behalf of customers, either independently or after human agent confirmation.

This surge in generative bots represents a transformative shift in customer interactions. Its impact varies based on implementation nuances. Some applications optimize workflows and virtual assistant functionalities, adapting dynamically to interactions and policy changes, substantially reducing manual effort. 

But a more advanced, integrated generative bot transcends these efficiencies. It seamlessly handles multifaceted queries, customizing responses by fusing knowledge base insights with specific customer data. It could comprehend customer queries holistically, autonomously accessing APIs, gathering required information, and executing tasks on the customer's behalf, reshaping the customer service landscape.

Blending Tech Investment to Amplify the Human Touch

The transformative integration of generative AI and people in contact centers isn't a distant vision—it's an unfolding reality informing the way businesses empower real human agents. It isn't about replacing human interaction but amplifying the human touch with technology. Generative bots act as indispensable sidekicks to agents, offering nuanced, real-time information, enabling agents to focus on complex calls and foster meaningful connections. 

By embracing generative AI, leading contact centers will transcend transactional interactions and foster relationships that are built on understanding, empathy, and personalized attention. It's this blend of technology and human interaction that paves the way for more high quality customer experiences. 

In Forrester’s 2024 Planning Guide for CX, 71% of leaders are prioritizing increased budgets to drive deeper customer insights, while 48% are earmarking resources specifically for contact center technologies. This heightened investment shows a serious commitment to leveraging tech advancements to enhance customer experiences. Moreover, a substantial portion of this budget increase is directed at data and research, highlighting the pivotal role of unlocking hidden CX data in the year to come.

Ending Bad CX: Reconciling Cost vs Quality

The struggle to articulate needs and provide seamless experiences often defines poor CX. Miscommunication and missed connections hinder the very relationships businesses aim to build. We all have our bad customer experience stories. Yet, the challenge persists: how to achieve high-quality service while managing costs. It’s been a core CX issue from day one.

Traditionally, this balance led to compromises, where either quality suffered or expenses soared. Now, the emergence of generative AI introduces a new trajectory, bridging the gap between cost-effectiveness and exceptional quality in CX, ensuring each interaction embodies the ethos of service at the heart of every contact center. As it shapes our approach, we move toward a CX era where the convergence of cost and quality through generative AI finally ends bad customer service.

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About ASAPP

ASAPP is a research-based artificial intelligence cloud provider committed to solving how enterprises and their customers engage. Inspired by large, complex, and data-rich problems, ASAPP creates state-of-the-art AI technology that covers all facets of the contact center. Leading businesses rely on ASAPP's AI Cloud applications and services to multiply Agent productivity, operationalize real-time intelligence, and delight every customer. To learn more about ASAPP innovations, visit www.asapp.com.

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ASAPP has significantly improved our efficiency in a very short time. Not only are we moving interactions from phone to digital, we’re doing it in a way that both our customers and our crew members love.

– Ian Deason, SVP Customer Experience, JetBlue

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