Agent assist is not a new subset of customer experience technology.
Contact centers have leveraged tools for years to recommend next-best actions, proactively surface knowledge base content, and automate desktop processes.
Yet, with the rise of generative AI (GenAI) and virtual assistants – like Copilot – agent assist has become a central area of contact center AI investment.
Moreover, many vendors have vastly expanded their agent-assist capabilities to meet this demand.
Six of these vendors have participated in this month’s CX Today roundtable, putting forward the following spokespeople.
- Donald McNelis, Cloud Business Development Manager at Avaya
- Michael Wallace, Americas Solutions Architecture Leader for CX at AWS
- Brett Weigl, SVP of AI Product Management at Genesys
- Elizabeth Tobey, Head of Marketing for Digital Solutions at NICE
- Crystal Miceli, VP of Product & Industry Marketing at Talkdesk
- Laura Ball, CX AI Lead for EMEA at Zoom
Below, each industry expert shares their favorite agent-assist use case before highlighting several benefits of deploying the technology.
Agent Assist: The Use Cases
Supporting Agents Adapt to New Policies & Procedures
Wallace: Agent assist is excellent for helping new reps reach proficiency faster. But, a more unexpected result is how it’s aiding tenured agents in adapting to new policy and process changes.
Often, tenured agents become used to doing things a certain way, and changes to processes or policies can introduce errors.
Agent assist gives new and tenured agents the same prescriptive guidance on policy and procedure adherence, minimizing the possibility of error and resistance to change.
Organizations can now expect that their customers will receive a consistent quality of service regardless of which agent the customer speaks with.
Simplifying Customer Content
McNelis: Some of the best use cases come from where grammar, natural language processing (NLP), and GenAI tools augment an agent’s written communications.
For instance, a virtual assistant can help summarize company information quickly in an easy-to-understand, clear, and concise way.
As a result, it’s not only easier to respond quickly to queries but also makes the process far less stressful, as people don’t have to spend time reading pages upon pages of company documents to find the right solution.
For agents with dyslexia or dyspraxia, this is an especially helpful aid as they can confidently correspond with customers, clients, and fellow employees.
Enhancing Case Management
Tobey: One of the tougher tasks an agent has is walking a customer through a multi-step process, such as an annual tax filing process.
One of the new ways that AI is augmenting agents is by generating step-by-step instructions.
Based on the need, AI can modify the format of the instructions to be very specific or general.
These instructions can pop up automatically during an interaction to guide an agent on how to help a customer, enhancing case management.
Agents can also personalize these instructions and use AI to take the customer through the steps at their speed, giving the agent time to focus on other tasks that require their attention.
As a result, it removes much of the frustration that can arise for agents and customers, leading to faster resolutions and better employee and customer experiences.
Automating Ticket Tagging/Contact Dispositioning
Miceli: With manual post-contact processing, agents incorrectly tagged customer conversations 27 percent of the time, according to Talkdesk research.
However, with agent assist, contact centers can automate that process with AI, which – according to the CCaaS vendor – only makes errors in three percent of cases. That’s a significant difference.
After all, contact centers use that disposition data to isolate customer trends, identify broken processes, and inform automation strategies.
So, when almost 30 percent of that intent data is inaccurate, misguided business decisions become a considerable concern.
Drafting or Informing Real-Time Customer Responses
Ball: Some agent assist tools – like Zoom AI Expert Assist – can access over 100 knowledge pools.
In doing so, they collect information from various sources to inform and – across digital channels – draft agent responses to customer queries.
On audio and video calls, agent assist can instead sift through knowledge bases and data stores to show the agent the most relevant articles and insights in real time.
Streamlining Agent Onboarding
Weigl: Agent assist streamlines new hire processes and reduces costs for organizations that invest in expensive employee training.
With AI copilots that automate tasks like note-taking, wrap-up codes, and more, employees can focus on more critical onboarding topics.
As such, new agents will feel more confident and require less training since agent assist lifts the burden of performing specific tasks.
Agent Assist: The Benefits
It Makes the Agent Role More Fulfilling
McNelis: Agent assist allows live agents to focus on higher-value activities, such as relationship management, retention, and revenue generation.
Indeed, reps have become more about problem-solving and collaboration, and – ultimately – more integral across the business as the single point of contact.
Yet, that doesn’t mean they’re always best suited to handle each and every query. Instead, they can be the orchestrators of conversations across the business, perhaps via swarming on connected CCaaS-UCaaS platforms.
Agents can also check AI-generated responses before sending them to customers instead of having to start them from scratch.
With these changes, agents become brand ambassadors who are critical to a positive, and therefore successful, customer experience.
It Supports the Development of Live and Virtual Agents
Tobey: Agent assist removes a lot of the grunt work notorious for bogging agents down and burning them out.
Instead of searching for information and struggling to figure out how to best proceed with an interaction, agents have the necessary information at their fingertips in real time.
Agents may also focus more on what matters most: developing stronger customer relationships.
Moreover, as bot-led interactions become more prevalent, agents will play a role in training bots so they deliver a similar level of service.
Indeed, they’ll create a collaborative relationship between bots and agents, transforming employee and customer experiences at the same time while enabling organizations to drive improved agent-assisted and unassisted interactions.
It Increases Efficiency & Process Consistency
Weigl: Contact center agents are facing more complex queries, higher customer expectations, and increased pressure to resolve calls.
Agent assist will correct the imbalance in a contact center agent’s time so they can better connect with customers and focus on high-value interactions.
With agent assist, employees can automate receptive tasks, summarize conversations, and get faster access to helpful answers – increasing their efficiency and ensuring process consistency.
It Supports the Convergence of Service and Sales
Miceli: In the future, agents may have a more blended role with sales, as more complex problem resolution may lead to potential upsell or cross-sell opportunities.
Yet, agents will also need to become more sales- and tech-savvy, which requires significant training.
That tech-savviness is crucial as agents must be able to use and adapt to continuously changing technologies beyond what’s immediately available on their desktops.
Lastly, agents will evolve into more trusted advisory / consultant-type roles – placing more emphasis on empathetic people skills, relationship development, and conflict resolution skills because bots will handle more simple, repetitive queries.
The good news is that this gives agents more time to deal with complex issues. But, with agents dealing with difficult situations more frequently, it also creates a need for them to show more empathy and creativity, which can drain their energy.
It Lowers Administrative Burdens and Streamlines Workflows
Ball: From next-best-action recommendations to real-time translation, agent-assist use cases typically help to reduce administrative burdens and streamline workflows.
In doing so, it boosts agent productivity, satisfaction, and – ultimately – engagement by minimizing repetitive tasks and enabling more meaningful customer interactions.
It Aids the Evolution of Contact Centers
Wallace:
AI agent assist technologies are – ironically – helping agents become more human.
By removing many administrative tasks and simplifying knowledge access, agents can allocate more of their headspace to providing empathetic, emotionally intelligent customer service.
This is crucial in evolving contact centers from a historical cost center into revenue-generating profit centers.
A rising tide lifts all boats. A better customer experience leads to both happier customers and happier agents.
When a customer gets the right answer on the first contact, and it is delivered quickly and accurately, they will be pleased, and the agent will benefit from the positive interaction.
Agent Assist: The Providers
Avaya
McNelis: With the Avaya Experience Platform, companies can leverage AI to provide intelligent assistance, personalized support, and targeted training recommendations.
In doing so, contact centers may reduce stress, enhance job satisfaction, and foster continuous learning and development.
Moreover, the platform empowers employees by offering personalized coaching, development opportunities, and the solutions they need to solve customer problems efficiently, make informed decisions, deliver high-quality service, and take ownership of their growth and performance.
Avaya also allows customers to choose which large language model (LLM) they want to power the GenAI agent assist use cases across the platform.
Indeed, while its standard turnkey offers are based on a single LLM, Avaya can enable customers to bring their own LLM via its API-first approach, with transcriptions done by either the customer or Avaya.
Lastly, Avaya’s “Innovation Without Disruption” approach allows customers to deliver GenAI agent assist without ripping and replacing their on-premise or private cloud contact center.
AWS
Wallace: Amazon Connect has AI/ML at its core, and the rise of generative AI is a natural, built-in evolutionary path.
Security is also critical to how AWS starts with the development of all its AI services, as it’s a lot easier to start with security in the development rather than bolt it on later.
Its security focus, combined with the vertical integration of Amazon’s AI expertise, helps AWS keep pace with changing end-customer expectations.
Furthermore, Amazon Connect started as a service used by Amazon.com that AWS believed could be of benefit for other organizations.
As such, the vendor thinks there are still many more lessons from retail it can share to help others become similarly customer-obsessed.
Genesys
Weigl: Genesys natively built agent assist technology into Genesys Cloud.
With its end-to-end architecture, agents on the Genesys Cloud have support from start to finish in their workspace.
Additionally, unlike point solutions, Genesys Cloud AI is optimized for CX and ready to deploy on day one, enabling faster time to value.
As a result, its customers can be more self-sufficient, minimizing IT involvement in day-to-day maintenance and support.
NICE
Tobey: NICE is developing its AI to support live and virtual agents.
On the one hand, its Enlighten Copilot technology supports agents in every step of their journey, guiding them through real-time interactions with contextual guidance to drive optimal outcomes.
As such, the technology removes the burden that traditionally impacts agents and has proven effective in lowering contact center burnout rates.
Moreover, Copilot lets agents focus on what matters most, taking away repetitive, low-level work and letting agents prioritize more strategic, impactful work.
NICE is also leveraging AI to support supervisors and CX leaders, providing real-time and historical insights into CX operations along with actionable steps to optimize employee and customer experiences.
Finally, NICE has been developing its AI technology so human agents can become overseers of bots, monitoring bot-led interactions and training bots to perform better.
Consequently, its AI assists human and virtual employees, supervisors, and leadership teams.
Talkdesk
Miceli: Talkdesk Copilot offers disruptive capabilities that help agents handle complex conversations.
By analyzing procedural documentation and executing logical thought chains, Copilot enables accurate and efficient problem resolution.
In doing so, it reduces errors that often occur under pressure and empowers agents to focus on conversations rather than the clock. Because they’re less stressed, they’re able to be more human.
Also, Copilot improves accuracy and consistency. For example, its automatic summarization feature achieves higher accuracy in case summary compliance and disposition than manual agent efforts, removing agent bias or manipulation.
All of this is done with simple and approachable AI, making it extremely fast for agents to become comfortable with the tool. Indeed, time to value is a major driver of the offering’s success.
Zoom
Ball: Helping businesses deliver prompt, highly personalized customer experiences is more critical than ever as consumers increasingly expect quick, real-time support.
Zoom’s vision to empower agents and achieve a new standard in the industry with AI-driven tools is brought to life by Zoom AI Expert Assist.
One key feature is message auto-translation, which facilitates seamless communication in over 20 languages simultaneously.
Another is next-best-action, which offers real-time guidance so that new agents can perform to the standard of experienced ones and – ultimately – resolve queries quicker.
AI Expert Assist also stands out by pairing with the Zoom Contact Center, which supports a robust suite of channels, including voice and video.
Miss out on our previous CX Today roundtable? Catch up here: CRM for Customer Service: AI, Other Trends, & Providers
