How to Enhance Customer Engagement with AI

A New Era of Enriched Customer Engagement

Picture this: A new customer arrives at your company’s website. They’re greeted by an AI chatbot that points them in the right direction, streamlining their experience and shortening their path to purchase. From there, more AI technologies work in the background to provide personalized suggestions based on your customer’s browsing patterns.

Once they’ve completed their order, AI-enabled process automation allows them to pick it up at a store in a few hours. At the store, an AI-powered kiosk helps the customer easily navigate to the right counter. And when the customer decides to pick up some additional items, computer vision‒enabled checkout helps make the purchase experience fast and painless.

Just a few years ago, such an experience may have sounded prohibitively expensive or too complex to implement. But today, using AI in innovative ways to enhance the customer experience is within reach for businesses of all sizes. Organizations across industries are using technologies like generative AI, natural language processing, computer vision, and recommendation engines to revolutionize the customer experience, enhance engagement, and build revenue.

Of course, realizing these powerful business outcomes from your AI investments requires you to have the right approach, tools, and technologies at your disposal. To help equip your initiative for success, let’s walk through some key considerations for using AI to enhance the customer experience and increase engagement.

Identify the Right Use Case for Your Business

Every business is unique—and you know your operations and customers better than anyone. As you seek to enrich the customer experience through AI, it’s critical to strategically apply AI to the parts of your business where it can deliver the most value and have the most powerful impact on your customer experience. You’ll also want to be mindful of existing investments in areas such as your software stack, AI-capable hardware, and other AI tools already in play.

As you consider all the possibilities for how you can use AI:

• Read how recommendation engine provider Taboola worked with Intel to optimize and benchmark their prediction algorithm on 4th Gen Intel® Xeon® processors.
• Discover how Netflix delivers fast, customized streaming experiences with optimized efficiency by running AI on Intel® Xeon Scalable processors running in the cloud to provide fast, customized streaming experiences.
• Learn how Lee’s Famous Recipe Chicken reinvented the drive-thru using AI and Intel® hardware.
• Explore our Intel® Customer Spotlight library to find inspiration in others’ stories, and learn how Intel® technologies can help enhance your results.
• Consult our guide to AI use cases across various industries.

Consider All Your Options for Models and Software

Gone are the days when organizations seeking to enhance engagement through AI needed to spend a lot of time and energy obtaining an AI model to fit their desired use case.

In fact, today’s businesses can obtain the AI capabilities they need in several ways, including:

• Fine-tuning a preexisting or foundational model: Organizations can take advantage of an ever-growing number of purpose-built, open source models such as Llama 2, GPT-J, or Dolly that fulfill a wide range of business applications. These models can be customized to fit the specific requirements of your industry and desired use case. This process is typically called fine-tuning.
• Purchasing AI-enabled software with built-in algorithms: Many common use cases are also supported by software offerings that help you rapidly deploy AI capabilities. To find the right option for your business, visit our featured partners page.
• Training a model from the ground up: Some organizations may find their situation so unique or their intellectual property so sensitive that they opt to build a model from scratch. Here, tools such as the Intel® Geti™ platform can help expedite training and development.

If you don’t plan to purchase software, your organization will need to consider the development requirements for your AI solution—from performance to scalability and deployment flexibility. To help you achieve this, Intel offers a powerful range of data science and AI development tools, including optimizations for popular frameworks and libraries such as PyTorch and TensorFlow. Our AI development portfolio also includes the Intel® Distribution of OpenVINO™ toolkit and the oneAPI cross-architectural programming language, both of which can help boost developer productivity and streamline deployment across diverse IT environments, such as retail environments with various types of hardware already operating in them.

Maximize Deployment Flexibility and Efficiency with Intel

Enhancing the customer experience through AI requires strong performance and flexibility—both at the edge and in the data center. Across your entire IT landscape, you can take advantage of the Intel® portfolio to support your AI workloads with an optimal blend of performance and cost efficiency.

In fact, many of your existing data center environments based on Intel® Xeon® Scalable processors are likely ready to support AI workloads without requiring further hardware investments.

These processors offer accelerated AI performance—whether it’s for training, fine-tuning, or inferencing—especially when you take advantage of integrated AI acceleration engines such as Intel® Advanced Matrix Extensions and Intel® Advanced Vector Extensions 512. Up to 20 key machine and deep learning workloads—which are essential elements of many AI use cases, including chatbots and recommendation systems—get better performance on Intel® Xeon® processors compared to NVIDIA and AMD offerings.¹

While Intel® Xeon® Scalable processors can support many AI workloads in the data center, highly complex workloads introduce the need for specialized hardware that delivers the highest levels of throughput and performance. If your AI initiative involves large-scale training and inference, you’ll want to assess Intel® technologies such as:

• Intel® Gaudi® AI accelerators: Deliver high-efficiency, scalable compute in the data center, as well as standout power efficiency that helps control costs and increase sustainability.
• Intel® Data Center GPU Max Series product family: Accelerate insights through breakthrough CPU and GPU performance.
• Intel® Data Center Flex Series GPUs: Provide ideal support for AI visual inferencing workloads, such as retail video analysis.

For client computing needs, Intel® Core™ Ultra processors deliver powerful integrated AI capabilities that can help your team implement AI into their daily workflows. And for edge applications such as smart kiosks or computer vision applications, Intel® Core™ processors offer a compelling blend of strong AI performance, optimized power efficiency, and support for demanding environmental conditions.

As you assess your hardware needs and existing assets, remember that the Intel® portfolio can help you achieve AI with the right balance of performance and cost efficiency—both in the cloud and on-premises. And keep in mind that you can test-drive our hardware at any time using the Intel® Developer Cloud.

As you pursue proof of concept prototyping and begin moving into development, production, and deployment, you can take advantage of our full suite of AI software tools and development resources, which includes order of magnitude optimizations for popular frameworks and tools for every stage of the AI workflow. These tools and resources can help improve productivity, optimize performance, and simplify your project across the entire AI life cycle.

Finally, if you’re currently using a competitive technology and would like to explore your migration options, consult these resources:

• Habana Developer Site
• HabanaAI GitHub
• Habana Developer Forum
• Migration tools for Intel® Max Series GPUs

We’re with You Every Step of the Way

Implementing AI to enhance the customer experience is a complex journey. At Intel, we’re dedicated to applying our cross-industry experience in AI innovation alongside our technologies and vast partner ecosystem to help businesses of all sizes realize value from AI—quickly and efficiently.

As you continue planning your initiative, be sure to consult our in-depth guides to some of the AI workloads that are essential to enhancing the customer experience:

• Generative AI, large language models, and natural language processing—all of which play a pivotal role in technologies such as chatbots and virtual assistants.
• Computer vision, which is essential to automated checkouts and loss prevention solutions.
• Recommendation systems that can help you grow revenue while more easily connecting customers with offers they’re interested in.
• Classical machine learning, which can be applied to help you analyze customer behavior and find new business opportunities.