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AI: What’s Possible and Practical?

AI: What’s Possible and Practical?

AI: What’s Possible and Practical?

Reimagining how AI can be used in the contact center.

This story, about technology with unlimited possibilities and the capacity to generate massive change, is still in its early chapters.

Artificial intelligence (AI) has the potential to do a tremendous amount of good and is one of the biggest and most influential technology trends ever experienced.

AI is enabling and enhancing many other important developments including blockchain technology, the metaverse, virtual reality, 3D printers, autonomous systems, and so much more, because of its ability to continuously self-learn and improve.

AI technologies had already captured the market’s attention due to their transformative capabilities. But when OpenAI boldly made ChatGPT and its supporting large language model (LLM) available to anyone who wanted to try it in November 2022, global interest exploded.

Generative AI technologies have been around approximately 20 years but were not well known before OpenAI opened the door to consumers around the world.

OpenAI’s marketing ploy worked: garnering the attention of everyone from grade schoolers to enterprise executives. It raised the profile of Generative AI and many other AI technologies.

Seemingly out of nowhere, technology vendors introduced all types of AI-based or enabled systems and applications that were capable of improving the way “work” could be done in all industries.

When AI was combined with automation and powered by the processing capacity of the cloud, it changed the cost dynamics and availability of these solutions, making them more accessible and consumable.

Contact Center Vendors Join the Wave

As AI technologies matured, many contact center vendors that had used AI and automation on a limited basis for decades recognized the potential to address other challenges: that had been confounding and limiting them for years.

With strong backgrounds in speech-related AI - natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG) - these vendors leveraged their domain expertise to expand their use of AI.

For example, after nearly four decades, breakthroughs in self-service technology are changing how these solutions are designed, built, and interact with consumers.

  • The days of identifying and coding every possible intent and answer are being replaced with systems that leverage technologies that invite customers to speak naturally, then use this input to find or generate an appropriate response.
  • Omnichannel intelligent virtual agents (IVAs), or bots, are now available to address a growing number of uses in contact centers and on websites.
  • The newer intelligent Conversational AI (CAI) self-service solutions are good for consumers and are equally useful in helping employees source the information they need to respond to customers accurately and quickly.

Several new AI-enabled solutions have recently come to market to help and augment agents. Context-relevant AI-enabled knowledge management (KM) solutions can deliver answers and procedures from internal and external sources in real-time.

These applications help agents do their jobs, increasing first contact resolution (FCR), improving the customer experience (CX), and enhancing the employee experience (EX).

They also help reduce agent training and onboarding time, greatly increasing their value and demand after years of fighting to attract market attention.

Agent assist is an emerging category of agent-facing tools generating strong interest. They include virtual assistants (VAs), real-time guidance (RTG), next-best-action (NBA), and post-interaction summarization, and more is on the way.

Interaction analytics (IA) is the underlying AI-enabled technology in all these solutions, just as it is for transcription, another application that is finally experiencing wide-scale adoption.

Being cloud-based makes each of these solutions viable and cost-effective, as it means companies do not have to purchase the servers to run them nor do they have to implement and maintain them.

Several new AI-enabled solutions have recently come to market to help and augment agents.

Generative AI is another important contributor to contact centers. This technology is useful by itself but is even more valuable when combined with other AI-based contact center applications and capabilities.

It is being used to enhance the accuracy and effectiveness of IVAs, VAs, RTG, NBA, post-interaction summarization, and CRM solutions.

Generative AI is great at drafting content and answers to questions. As long as it has access to an LLM of data that is targeted, tagged, curated, and maintained for each customer’s specific use.

As of the end of 2023, every known contact center system and application has been AI-enabled in one way or another.

Some of these solutions, like IA and IVAs, were built using AI technology including NLP, NLU, and NLG. In others, such as CRM and workforce management (WFM) applications, AI technology is being used to enhance various components and features of these solutions.

Most CRM applications now come with an AI layer, data repository, and LLMs to enhance their overall performance. Contact center WFM solutions include AI-enabled algorithms to improve their forecasting and scheduling capabilities, with a great deal more innovation on the way.

All contact center innovation starts in the cloud, and when necessary is retrofitted for premise-based systems. Most new contact center technology start-ups only offer cloud-based applications, even though more than half of the seats are still on-premise as of the end of 2023.

Digital Is a Driving Force

Digital activity is growing rapidly and will continue to pick up momentum in the coming years, although voice-based channels are not going away. Companies are struggling to figure out which of the dozens of digital channels to support, as the “channel du jour” changes frequently.

Based on our research, we recommend supporting email, chat, short message service (SMS), WhatsApp, and mobile apps at a minimum, in addition to voice.

However, as companies need to meet customers in their channel of choice, each organization should ask their customers for preferences and then do a cost/benefit analysis to help them decide what to add.

Customers are making their strong preference for self-service clear, and they expect to be able to help themselves in any channel they choose. This is a positive trend for enterprises as self-service solutions reduce contact center servicing costs, but it means revamping how they address these needs.

Most companies still only provide self-service via their websites and contact center IVR systems. It’s time for them to invest in the new generation of AI-enabled omnichannel IVAs that are able to provide consistent answers, rendered appropriately for each channel and user.

And when deciding on digital channel support, organizations need to consider self-service capabilities.

It’s Time To Get Started With AI

It’s easier than it may seem to get started with AI, as most of the contact center applications include some form of the technology. However, it’s up to each contact center leader to decide whether they are ready to take advantage of these advanced capabilities.

In some applications, AI enhances standard features by making them more accurate than they would be without it. In other systems, AI gives them the ability to do things they couldn’t in the past, as is the case for post-interaction summarization.

...companies begin by creating an AI strategy to provide them with a direction for getting started.

There are few established best practices for AI adoption as no two organizations are the same, and there are many types of AI. This technology is new, and contact centers all over the world are trying to figure out the best way to utilize it to enhance their entire operation or a specific function.

Most companies start with a small pilot to see if it works and to learn how to use the application, and then roll it out broadly. The top uses of AI in contact centers today are enhancing self-service capabilities, and leveraging interaction analytics and the growing cadre of applications it enables.

We recommend that companies begin by creating an AI strategy to provide them with a direction for getting started.

The strategy may be as simple as stating that they want to improve customer self-service or augment agent performance. This provides a goal, enabling the organization to identify the scope and concentrate on technology and vendors that help them address the specific challenges.

Final Thoughts

There has never been a more exciting yet confusing time for contact centers due to the amazing AI-enabled technology already available and emerging solutions and capabilities on their way to market.

No one can definitively say that AI is going to replace the need for all live agents, but it can be said that these new capabilities augment and enhance agent performance and productivity and improve the CX and EX. Contact centers are at a pivotal point.

They need to change to be able to deliver a consistently outstanding and cost-effective CX, and because of AI and automation, they have the tools to achieve these goals.

Donna Fluss

Donna Fluss

Donna Fluss, Founder and President of DMG Consulting LLC, which provides a unique and unparalleled understanding of the people, processes, and technology that drive the strategic direction of the dynamic and rapidly transforming contact center and back-office operations and markets. Donna can be reached at [email protected].

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