AI has dramatically transformed over the past year.

All thanks to Generative AI, which has gained enormous prominence by exhibiting human-like capabilities of thinking, natural language understanding, interacting, doing tasks, and making decisions in a much faster and more innovative way.

Depending on LLMs that unlock coherent abilities, Generative AI effectively drives deeper chatbot adoption.

According to McKinsey, 75% of the value that Generative AI use cases offer encompasses customer services—one among four business function areas.

Reducing the time-to-respond is the primary objective of customer service or employee support. This has a positive outcome for businesses that improve user experience, brand loyalty, and customer retention.

While businesses use chatbots extensively—whether for customer support or employee interactions- they want to ensure they use Generative AI and build completely autonomous customer or employee support.

It isn’t wrong to say that businesses aim to transition to zero-touch user supportthat can unleash the effectiveness of Generative AI to automate routine to complex tasks, solve problems, and help build a proactive support ecosystem for businesses.

Zero-touch user support is a game changer that can be made possible using Generative AI on top of your existing or new CX platform.

Havard Business Reviews says that 81% of customers prefer solving their problems themselves before reaching out to a live representative.

Another report from Aspect Software suggests that 73% of users or customers want to have the ability to solve product or service-related issues independently.

Contact centers or service desks double down on virtual assistants or self-service platforms for user engagement. Unfortunately, a report from Zendesk indicates that the knowledge-base-only self-service platform fails.

It means self-service bots are not able to provide end-to-end automation and remove the friction from the customer or user support.

Generative AI, built on large language models underpinned by massive datasets, provides text-generation capabilities and improves natural language understanding to augment automation and problem-solving better than older chatbots.

This can efficiently help businesses transition to zero-touch user support, in which companies can implement almost fully autonomous support without relying on human agents initially and help provide information to solve user problems in real time.

A user, for example, wants his productivity app to have software upgrades. This is a case that needs a human assistant. However, zero-touch support can use Generative AI to supply accurate and relevant information in a synthesized manner to guide the user and help him perform a necessary upgrade in fewer steps.

Adding to zero-touch flexibility for leveraging independent help, it can efficiently work with voice or text requests, showing empathy to boost user confidence and belief to increase adoption.

The convenience of zero-touch support is such that it makes it easy for your GenAI-powered chatbot to understand the intricacies of an issue, identifying the need to transfer a call to an equipped agent without having to rely on an additional assist to escalate the ticket.

Generative AI can use massive datasets to learn from previous interactions or new training data to interact or perform an NLP task.

So, the key here is data. The more quality data an LLM model is trained with, the better the quality of providing answers is with the Generative AI chat interface.

Here are some approaches you can try to build your zero-touch user support.

1. Zero-touch support on a fine-tuned LLM model

Fine-tuning is one of the best strategies if you want to achieve little more than prompt engineering with off-the-shelf GPT 3.5 models. Working with a pre-trained model is also an effortless way that lets you tweak or train a particular part of the model with datasets specific to certain tasks.

However, finetuning only allows you to achieve a certain level of chat support, especially only with one or two use cases.

2. Custom LLM model for zero-touch support

You can best drive end-to-end workflow automation for zero-touch user support is to building your LLM model from scratch.

Well, this needs extreme investment of time, effort, and money from your end.

From having to take care of compute costs for cloud platforms to overseeing model development end-to-end with the help of your in-house team, the development of custom LLM models is time-consuming.

Besides, you need to ensure you have quality training datasets.

You need to look for historical data and create diverse conversation examples to match your use cases for zero-touch user support.

With a custom LLM model for your Generative AI-powered chatbot, you can easily automate user interactions and solve problems for as many use cases as possible.

3. Zero-touch support on a no-code LLM platform

A no-code platform can be your top choice for a hassle-free launch of your zero-touch user support.

With the underlying LLM infrastructure, you can quickly train the model with your use cases without considering compute cost, an in-house team of AI specialists, and writing a single code.

A no-code platform is equally good at text generation, NLP data processing, and understanding user queries for improved information discovery and enterprise AI search performance.

Workativ's no-code LLM platform or Knowledge AI gives you complete control to turn your chatbot into zero-touch user support.

Conversational AI gives a chatbot the ability to unlock human-like qualities to talk and understand the intent of a query and give answers. When combined with Generative AI, conversational AI can gain dramatic capability to process data, provide answers, and solve user problems.

Harnessing the power of conversational AI and Generative AI, leaders find it easy to transition to zero-touch user support.

There are some fantastic use cases for industry leaders to leverage and transform user experience with zero-touch user support. Let’s see where you can resonate with them.

Reshape employee support with no human intervention.

Employee support can encompass various business operations that need to be automated so businesses can resolve internal employee problems instantly and improve productivity.

Leverage zero-touch support and remove every friction a chatbot would otherwise raise for a simple task.

• IT support automation

IT helpdesk teams are long involved with manual and mundane work processes for typical issues such as password resets, software provisions, account unlock, etc. Workflows built with genAI properties can quickly eliminate human intervention and solve these problems for your internal users.

• Password reset

Using LLM-powered automation with your conversational AI workflows, you can remove multi-step requests and easily automate password resets by allowing your user to fix it just by providing an email ID and supplying information in a form.

• Software access

Your team has a new hire and needs access to software suites like M365. An LLM-powered workflow starts when you add the user to the AIM tool. Without further effort, the manager receives a message to grant access to the license. A chatbot message can help him verify all details and allow real-time access.

• Account unlock

It is not easy to remember passwords for multiple apps your users use. So, account unlock is quite a familiar issue. A chatbot built with LLM-powered workflows can suggest the proper steps to apply and resolve account unlock problems.

• ITOps automation

You must ensure your entire IT infrastructure faces fewer downtimes so that your people can unleash productivity.

LLM-powered helpdesk can reduce manual intervention and repetitive tasks to build resilient ITOps support.

• IT incident management

If a computer or an internal application crashes, an LLM-powered chatbot can help instantly by making it easy to ask questions about what went wrong and what steps are necessary to fix the issue. This helps reduce workloads on L1 support.

• IT incident note development

By utilizing the text generation capabilities of Generative AI, IT helpdesks can allow anyone to craft incident notes so the team can know about the proper incident and mitigate the impact of the incident in real-time.

Transform HR support autonomously.

Human resources is one area that takes care of too many administrative responsibilities. Unfortunately, these tasks are repetitive, manual, and mundane, increasing resolution time for user queries.

An LLM-powered chatbot can help automate HR tasks and transform the user experience through zero-touch user support capabilities.

• Time off request

An employee may need information on the steps to apply for time off. A lengthy knowledge article may be too difficult to navigate and absorb correctly. Create a workflow that provides concise yet accurate information to help satiate user queries.

• Leave requests

Your employees need leave–maybe for maternity or sickness. You can make it easy to find information and follow the company policies so that they can properly utilize leave benefits yet ensure efficiency.

• Onboarding for new hire

A Generative AI chatbot can make onboarding absolutely effortless for your HR team. From paper processing to user provision, you can automate every step and comfort your new hire.

• Common HR queries

There are many more use cases an HR can interact with every day. Employees can have queries for settlement, PTO, taxes, etc. Automating manual work with Generative AI-powered workflows and reducing manual workloads is easy.

Elevate customer support with autonomous workflows.

It is a tested theory that customers hate to wait. A second delay means gains for your competitor. Zero-touch customer support is a new way to remove friction and elevate user experience.

• Automate order placement

Navigating through items doesn’t always guarantee a purchase. Customers want personalized service that suggests recommendations for best fit or color preference. A chatbot with generative AI capability can detect user preferences from previous interactions and instantly suggest the best buy for them while initiating order placement.

• Make “return” easy

You can easily take the hassle out of your customers’ way when it comes to returning an item. An LLM-powered chatbot can easily track down which product may have a defect and help your customers proceed with a return.

• Refund status

By interacting with its databases, an LLM-powered chatbot can know the refund details of a customer. So, when a query comes, it promptly provides details and ensures a refund in a stipulated time. As a result, a customer can gain a seamless shopping experience and improve brand advocacy.

With zero-touch user support, you can always enjoy additional benefits for business growth.

• Reduce time to respond.

Your support can deliver delayed responses if your human agents are tied with too many tickets.

A self-service platform built on LLMs can remove friction from your support and allow your users to find information and solve problems autonomously. Thus, it reduces the time to respond and improves uptime.

• Improve mean time to resolution or MTTR.

When integrated with LLM-powered databases, your self-service platform can reduce the time to respond to any common to complex query. Users can handle their issues independently without seeking help from human agents. So, it ultimately reduced time to mitigate impacts and improve MTTR.

• Enhance CSAT

With zero-touch support, there is no extra effort to craft back-and-forth emails or connect over a call to repeat the case. Users can quickly surface information with condensed information that helps them resolve issues instantly. As a result, a reduced wait time for each common query adds to user satisfaction.

McKinsey is of the opinion that Generative AI will reduce workload by 60% which can be directly related to reducing workloads for human agents in the support ecosystem.

Another study from NBER highlights that Generative AI can improve problem-solving by 15% in the future.

It is right to consider that Generative AI can relentlessly drive towards zero-touch user support and aim to improve CX.

In addition to prioritizing CX, zero-touch user support user support makes sense. If you want to be in the competition and leverage the potential of zero-touch support driven by Generative AI.

Here is what you can do.

Set clear objectives

First, identify why you need zero-touch support. Work on everything, such as use cases, timeframe to launch your product, and resources to implement a Generative AI-powered chatbot to elevate your user support.

Build a strategy with internal stakeholders.

Connect with all stakeholders who can add value to the strategy. Ask for their suggestions and agreement on matters discussed. Everyone from HR, IT, Finance, Legal, and Marketing, including the support agents, can participate and help deliver better outcomes.

Collaborate with the right partner.

You can find the right partner after you evaluate your preferred model to build your zero-touch workflows. The best you can do to reduce the investment load on your bottom line is to go for a no-code platform that gets you onboarded swiftly without all the hassles of building in-house LLM projects.

As per Accenture, 65% of executives feel an urgent need to embrace Generative AI.

It is about driving the best value from Generative AI as others aim to do. Overlooking the significance of Generative AI can mean losing to your competition, who are serious about applying GenAI technologies across their services.

Deploying one in your CX platform can reap better outcomes and reduce operational costs. If your bottom line budget is a constraint, start with a no-code LLM platform to kickstart your zero-touch support journey.

Workativ harnesses the power of large language models or Generative AI for its Knowledge AI platform. With the quick upload of knowledge base articles, you can build a massive data repository, apply Generative AI to retrieve answers, and help reduce response time.

Workativ delivers a ChatGPT-like natural language experience as your support users interact with Knowledge AI and derive answers to solve problems autonomously.

With a no-code platform that requires zero coding expertise or technical acumen, Workativ ideally takes no big time to create conversation workflows as per business cases so that you can launch as quickly as possible and transition to zero-touch user support.

Both your users and customers want frictionless user support, meaning it must deliver accurate answers, understand a variety of queries in a single conversation window, and differentiate between context switching and surface accurate and relevant answers initially.

Workativ can seamlessly allow you to aim for zero-touch user support and drive towards building elevated user experience.

If you are still not evaluating zero-touch support, it’s worth considering and launching one. Your users would love it and help you save on operational costs.

Want to get a head start on zero-touch user support? Connect with Workativ today for a demo.