AI Trends: Custom AI Journeys and More for 2024

The Gist

AI evolution noted. 2023 saw significant advances in AI-driven chatbots and natural language processing, enhancing customer interaction across digital platforms.
Predictive tools spotlighted. AI predictive analytics and customer routing refine marketing strategies, improving conversion rates and customer lifetime value.
Data compliance warned. The rapid adoption of AI in marketing faces potential risks from stringent data governance and compliance regulations in the near future.

Artificial intelligence (AI) has fully moved from the back office — for marketing activities like model propensity scoring, churn and attrition detection and mitigation, and process planning and optimization — to the front office, highlighting key AI trends in customer engagement.

AI now powers many customer-facing activities to improve personalization and engagement — via customer journey creation — across all digital channels.

In 2023, we saw improved chatbot experiences due to natural language processing (NLP) advancements — which rely on natural language generation (NLG), understanding of that generation via natural language understanding (NLU), and advanced sentiment/text analytics capabilities. Voice and visual recognition tech for the customer experience was enhanced as result of these advancements.

Let's take a look at some of the most recent AI trends and where we are heading.

Related Article: 8 Ways AI Can Elevate Your Customer Experience

AI Trends: Where We Are Today

The shift from AI back to front office began a number of years ago, highlighting key AI trends as we saw chatbots modernize from simple rules-based question-and-reply syntaxes to being fully AI-enabled. NLP technologies have strengthened front-end channel engagement, improved targeted marketing and produced more integrated and effective campaigns.

Today, NLP has been integrated into chatbots, interactive voice response (IVR) systems and other voice-based interaction tools. It helps marketing organizations better understand and respond to customer needs and queries, even with limited resources.

Text analytics helps organizations understand structured and unstructured text to infer consumer preferences and uncover customer behavior signals.

Sentiment analysis takes text analytics a step further and helps marketers understand the sentiment or emotion of a voice string, text query or other unstructured data source — in order to respond appropriately to customer comments, queries and messages.

Today’s more recent AI trends and techniques are increasingly found across marketing and customer engagement. Large language models (LLMs), for example, help marketers create and refine relevant and targeted copy and emails, images and advertisements.

AI tools rooted in predictive and prescriptive analytics provide guidance to marketers about next-best actions and real-time offer delivery.

AI-based optimization and customer routing techniques improve conversions and lifetime value by deftly and agilely guiding customers to customized end-conversion events rather than forcing them down brand-based predefined paths.

All of these improved analytical techniques help marketers hyper-personalize their efforts, identify customers at risk of churn or open to upsell and cross-sell and analyze campaign results to make real-time adjustments.

What’s Next in AI Trends?

In 2024 and beyond, AI will accelerate. As generative AI and other AI-based technologies continue to evolve, more and more marketing and customer-service departments will adopt and rollout these technologies — infusing them into a variety of customer journeys to drive better retention, loyalty, migration and growth.

Expect more generative AI-based approaches to be infused into chatbots using visual and voice recognition, IVR systems, and point of sale (POS) terminals and kiosks.

The automation of low-level customer service tasks will continue via robotic process automation (RPA) and LLMs. For some brand-to-consumer interactions, the line between what is human and what is machine will become very blurry.

For marketers and customer-service professionals, the use of AI, sentiment and text analysis through NLP will help them focus on handling more complex customer questions and requests in person, while giving the customer a personalized and interactive digital experience to manage simpler requests.

Governance, Risk and Compliance Backlash

While more brands will approve the use of AI technologies for specific projects and tasks, I strongly believe that the combination of data deprecation and the potential unwieldy use of generative AI in 2024 and beyond could result in a governance, risk and compliance backlash when it comes to AI trends.

The Golden Gate Bridge in a heavy fog in piece about the unknown future of AI trends. — While more brands will approve the use of AI technologies for specific projects and tasks, I strongly believe that the combination of data deprecation and the potential unwieldy use of generative AI in 2024 and beyond could result in a governance, risk and compliance backlash.clayllama on Adobe Stock Photos

Many of these same brands will pull back to ensure they have met data governance and compliance timelines. We will see global, country, federal, local and regional data compliance regulations start to test organizational data governance practices.

And undoubtedly another of many AI trends will be that a handful of organizations will face significant challenges. By not implementing responsible marketing practices — that is using marketing and customer data in a responsible manner — fines will mount. From the new EU AI Act to the General Data Protection Regulation (GDPR) to laws like the California Consumer Protection Act (CCPA), the next few years will be marked by mounting data compliance missteps.

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