Artificial Intelligence

But healthcare remains behind other industries in agent, patient satisfaction

Patient experience (PX) technology, bolstered by artificial intelligence, is dramatically transforming tech-savvy healthcare companies, whether insurance, private practices, hospitals and clinics, or managed care facilities.

Though 51.2% of healthcare providers are using AI for their patient interactions, key success metrics are below average. PX leaders are challenged to both start AI deployments and prioritize the variety of products and services available, as innovation continues at record pace. Though many options are available for PX technology, those that focus on patient care representatives (aka “agents”) are most pressing.

Healthcare companies are seeing improved patient satisfaction when agent assist is in use; in fact, it’s pretty significant at 34.9%. But it’s not as high as the all-industry average customer satisfaction improvement at 39.2%.

Investment Increases Will Drive More Success

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The AI hype must translate into demonstrable business benefits.

At last month’s Enterprise Connect conference in Orlando the AI hype train was steadily moving along the tracks. Virtually every keynote and vendor announcement involved some new AI-based feature to improve customer experience, employee collaboration, security, operational management, and more. AI, specifically generative AI (Gen AI), has received the lion’s share of media attention over the last year as vendors race against each other to differentiate and to accelerate in their use of AI to advance their products. However, the rapid, and accelerating advance of AI, has created challenges for IT and business leaders as they move from hype to adoption. These include measuring ROI, change management, and ensuring security, governance, and compliance.

MEASURING ROI

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AI might get all the attention, but IT leaders are also concerned about some other key security vulnerabilities within their unified communications platforms.

Companies are facing a variety of unified communications threats — from AI, toll fraud and improper use of messaging channels — all of which were highlighted at a UC security panel at this year’s Enterprise Connect in Orlando, Fla.

The UC security challenges session, which I moderated, featured a diverse group of vendors. Mark Collier, CTO of SecureLogix, Ram Ramanathan, senior director of product management at Ribbon Communications, and Bryan Mack, master principal consultant at Oracle, represented vendors who have historically been focused on protecting their customers against threats of attack via voice channels. The panel also included Anthony Cresci, senior vice president of go-to-market and partnerships at Theta Lake, which helps companies meet compliance obligations, as well as Smita Hashim, chief product officer of Zoom.

Metrigy has tracked trends in the communications and customer engagement security space for the last several years. We’ve noted that even as security concerns grow — one in five of our research participants report having experienced a security incident — proactive strategies are lacking. Just 35% of organizations report having a proactive, company-wide strategy in place to protect against communications, collaboration and contact center threats.

AI tops security concerns

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AI can streamline customer interactions and save organizations money, but will it replace customer service agents? Maybe, but customer service will always require a human touch.

AI has already affected the number of customer service and sales agents needed in a contact center. Yet it won’t replace the need for the human interaction they deliver.

AI will continue to have a profound role in boosting agent efficiency and improving overall CX. It was also a major topic at this year’s Enterprise Connect conference in Orlando, Fla., where Metrigy hosted a panel of experts titled, “Job Shifting: When and How is AI Eliminating & Adding CX Positions.” The panelists generally agreed that AI will help agents become more efficient and effective.

The panelists included Steve Brock, senior director of solutions marketing for Avaya; Vi Chau, head of product for Zoom phone and contact center; Josh Goldlust, vice president of product management, digital platform for Genesys; Rei Kasai, senior vice president and global head of product for Talkdesk; and Andrew Traba, vice president of product marketing for NICE.

Do contact centers need AI?

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Critical as they are to a contact center operation and, ultimately, an organization’s ability to deliver on customer experience goals, supervisors haven’t necessarily received the same level of attention as agents when it comes to the work experience. But that’s starting to change.

Just as artificial intelligence (AI) has been put to use to improve the agent experience, so too is it starting to be applied to the supervisor experience. Improve the supervisor experience, and operational efficiency is sure to follow—or vice versa.

Agent assist software and supervisor assist software act in much the same way. They leverage different types of AI to improve the way agents and supervisors, respectively, do their jobs. For agents, it’s about providing in-the-moment advice, information, and context to deliver the best possible service. For supervisors, it’s also about providing context, along with analytics to improve agent performance and contact center efficiency.

Like agents, supervisors receive this information in screen pops, but also in reports, charts, and tables (which, one day, AI ought to make less burdensome to assess). The AI works with workforce optimization/workforce engagement management applications, such as quality management and workforce management, to help analyze agent performance on calls and to improve the accuracy of schedule and capacity management requirements.

As detailed in a recent MetriNote, supervisor assistance was one of the AI-related themes coming from customer experience (CX) providers at Enterprise Connect 2024. AWS and NICE are two examples of CX providers that introduced new supervisor assistance capabilities.

AWS announced that its contact center analytics and quality management offering, Amazon Connect Contact Lens, now supports generative AI-powered post-contact summaries for supervisors to use while reviewing interactions and assessing agent performance, and that the software will now automatically fill in and submit agent evaluations using insights from conversational analytics. And NICE introduced a version of Enlighten Copilot focusing on the operational needs of supervisors. It delivers real-time and historical information on agent performance, provides guidance on coaching requirements, and generates contextual alerts for real-time intervention.

These sorts of capabilities should resonate with CX leaders, based on findings in our global AI for Business Success 2024-25 research study with 697 companies. In the study, 43.9% of companies said they would see some value in improved supervisor functions, while 31.6% said there is significant need to improve supervisor capabilities.

The use of AI is already proving its value on supervisor time for the most successful companies in the study, as measured across a variety of metrics. Using AI helped companies reduce the amount of time supervisors spend on scheduling and capacity planning by 119 minutes. Although this isn’t exclusively attributable to supervisor assistance, but rather AI in general, it points to the potential gains we can expect to see when AI is applied to the supervisor role.

It’s a win-win for improved supervisor experience and operational efficiencies.

Even customer service agents in the contact center often have upsell quotas. AI provides transformational value for boosting sales.

In the customer experience (CX) world, we hear regularly about how AI is helping companies better serve their customers. We don’t hear as much about how it helps them sell to their customers.

AI for sales is poised to explode – for good reason.

Perhaps the most compelling reason is illustrated in the actual success metrics from Metrigy’s recently released AI for Business Success 2023-24 global research study of 697 companies. Among the 34% of companies using agent assist, 54.1% cited sales increase as a benefit provided by AI. Those companies using agent assist saw a 35.6% boost in sales – not too shabby. What’s more, 70.4% of our research success group (those with higher-than-average business metric improvements through the use of AI) said agent assist increases sales, versus only 47.9% of the non-success group.

Yes, agent assist also improves customer satisfaction scores, slows agent attrition, and reduces average handle time. But actually attributing sales increases to AI? That’s golden.

AI’s adoption in outbound contact centers or even with outside sales teams makes sense. But its use is now spreading to less likely places.

The use of AI is especially fruitful in traditional inbound contact centers where customer service representatives at 54% of companies now must adhere to upsell sales quotas, along with their service key performance indicators (KPIs). Indeed, customer service agents’ jobs are getting harder with bots handling the easy questions, so one way agents can increase their income is through earning previously unavailable sales commissions. AI simply makes this plausible now.

HOW COMPANIES USE AI FOR SALES AND SERVICE TEAMS

Here are just a few ways business leaders, along with the frontline agents and sales teams, are using and finding value in AI when it comes to sales.

Continue reading at nojitter.com.

Certainly, to nobody’s surprise, artificial intelligence (AI) dominated last week’s Enterprise Connect 2024 event, from presentations on the keynote stage to demos on the expo floor. Since a year ago, most vendors have shifted from speaking of the art of the possible, particularly with generative AI, to today’s deliverables (along with plenty more to come).

Along with product availability has come increasing recognition of AI’s value for work purposes. We know this from conversations at Enterprise Connect, as well as from our recently published AI for Business Success 2024-25 global research study with nearly 700 companies. In this study, 82.3% of participants say they’ve become more accepting of AI’s value for their workplaces. More telling yet is that most companies are already using or planning to adopt AI for customer and employee interactions this year.

The study, conducted in December 2023 and January 2024, shows rapid adoption of generative AI for both employee and customer interactions, with more than 40% actively using today vs. the 27% of companies using generative products in June of last year. The top uses today are generating content for customers and for marketing purposes, with reviewing open-ended comments from customer feedback and generating content for agents to use during conversations being the top wish list functions.

Of course, none of this is to say that companies are throwing caution to the wind on AI. Rather, most companies are applying AI in a few areas for employee and customer interactions or are running pilots. (Worth noting, however, is that this study’s research success group, as determined by improvements across a variety of business metrics, is twice as likely to use AI extensively for both types of interactions than all other companies.)

Particularly for generative AI, the quality of the data set and data privacy remain top concerns. And most companies aren’t comfortable letting generative AI tools do their thing without some babysitting. Less than 15% of companies say generated content requires no vetting prior to using it, whereas 81.2% say either all (47%) or some (34.2%) content must have human oversight before using.

Companies not only are requiring human oversight when generative AI is using external data, but also when it is pulling content from their own knowledge base—and even when that knowledge base is managed and known to be accurate. Nearly 49% of companies still feel human oversight is mandatory each time content is created using data from their knowledge base, with 37.3% saying it’s necessary for some content.

Among other factors most companies are considering as they plan for the use of generative AI are service-level agreements (SLA) from their vendors. Among the nearly 62% of companies that either have or expect an SLA for generative AI, upwards of 71% are looking for guarantees on speed of response and response accuracy. Other desired SLA components are uptime (49.1%), reimbursement of business loss (45.5%), and latency (44.5%).

And while 62% of companies have or expect an SLA for generative AI, 42.4% say they won’t work with a vendor on AI without one. SLA is the fourth must-have for companies before working with a vendor on AI, behind analytics tools that show accuracy of AI responses, experience training models, and integration with multiple data sources.
As vendors flesh out their AI roadmaps and build out their AI portfolios, enterprise organizations are expecting them to do so with rigor. As do we. (Watch for Metrigy’s assessments of AI-related Enterprise Connect product announcements for employee and customer engagements, to come soon!)

Whether you run a small healthcare practice or a midsize hospital system, embracing the right technology will deliver measurable benefits. Healthcare is somewhat behind other industries when it comes to applying technology to daily operations, but even small changes will deliver big results.

When companies integrate Electronic Health Records (EHR) with their cloud-based communications systems (including contact centers and internal employee collaboration), they will see improvements in patient experience, operational efficiency and revenue. Couple that with powerful AI applications in the contact center, and patient experience scores will soar.

This webinar will give you strategic guidance, based on real-world research data from Metrigy CEO & Principal Analyst Robin Gareiss. You’ll also hear from Vonage’s SVP & Chief Technology Architect, Sanjay Srinivasan about how customers are using Vonage’s healthcare products and services today—and what benefits they’re driving. We’ll share insights and recommendations, and answer the following questions:

What value are healthcare practices and their patients uncovering through integrating Electronic Medical Records with cloud communications platforms, patient experience technology, and AI?
How are healthcare organizations driving operational efficiencies by leveraging technologies to improve clinical and patient experience?
What technologies help hospitals and practices drive more revenue, while also better serving patient needs?
How do you select a technology partner you can trust to understand the nuances of healthcare to gain the most value for your investment?