As generative AI copilots and virtual assistants grow in adoption, many organizations still struggle with how to measure ROI. This is especially true for those deploying, or considering, generative AI platforms that require the purchase of additional licenses. In this webinar Metrigy will share our latest research data on generative AI virtual assistant addition for employee engagement, and ways that companies can measure benefits including gains in productivity, cost savings, and revenue gain.

Measuring ROI for Generative AI

Presented by: Irwin Lazar, President and Principal Analyst, Metrigy

Date: January 14, 2025
Time: 11:00 am ET

IT and business leaders should consider how they will roll out AI in the future, how they will integrate collaborative data sources, and what platform(s) makes sense for their environment.

At the recent Cisco WebexOne conference in Fort Lauderdale, I was struck by something that featured guest Alexandr Wang, founder of Scale, said during the opening keynote with Jeetu Patel. When Jeetu asked Alex to share his thoughts on how companies should be thinking about AI, Alex responded (I’m paraphrasing) that every enterprise is sitting on data that is unique, specialized, and differentiated, and that the most exciting area is how companies will use their data to advance AI.

This view highlights the evolution of AI in the enterprise. The last year or so largely focused on bringing AI into organizations in somewhat limited fashion, with a great deal of attention paid to how companies can restrict what is shared with large language models for training purposes. Companies in the collaboration space have introduced opt-in policies to assure customers that no company data is being used for training purposes. This paradigm is now changing.

The Value of AI Comes from the Data

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Agent assist helps agents drive revenue—and solve customer service issues.

Artificial intelligence (AI) is making waves in many areas of business, but one of the most significant is in customer service. Agent assist, virtual agents, and sophisticated analytics are catalysts for significant changes in the role of contact center agents—both virtual and human.

CX leaders are focusing on a few key goals as they fine-tune their AI strategy for human and virtual agents: making processes more efficient, boosting customer satisfaction, and ultimately, helping companies grow. Virtual agents can more efficiently address more simple issues, offloading some of the agent workload. But AI also plays a profound role for interactions that require human attention. Not only does agent assist help customer service reps resolve issues, it’s also helping them sell products and services to customers—elevating the contact center to a revenue generator vs. a cost center.

Virtual Agents: Automation Taking on the Basics

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Metrigy’s latest research study, Employee Engagement Optimization 2025, sheds light on the rapidly evolving landscape of generative AI in the workplace. While the technology holds immense promise, it also presents significant challenges and concerns.

The Rise of AI Virtual Assistants

A staggering 66% of organizations are either currently using or planning to implement AI virtual assistants. The primary use case for these tools is document and data summarization and querying, streamlining workflows and boosting productivity. However, security concerns remain a major hurdle, hindering widespread adoption.

Measuring the Impact

Despite these challenges, 33.1% of organizations report that AI virtual assistants are already delivering measurable benefits. This suggests that when implemented effectively, AI can significantly enhance business operations.

AI and Vendor Consolidation

A potential limiting factor in AI usefulness are siloes of knowledge held within each collaboration app. Absent open data sharing, an AI virtual assistant in one app will only be able to provide insights into the data stored within that app. This leads to the potential that AI will drive collaboration vendor consolidation as companies seek to integrate all of their collaboration apps into a single platform to provide AI with the ability to see all communications and content. The reality is more nuanced. Only 23.3% of respondents believe that AI will drive such a trend. This indicates that the market is likely to remain diverse, with various vendors offering specialized AI solutions.

Governing AI

To harness the power of AI responsibly, almost half of the organizations surveyed have implemented an AI governance strategy. These strategies typically focus on data privacy controls, rigorous testing, and robust security measures.

Training the Workforce

To maximize the benefits of AI, over 70% of organizations have or will have an AI training program in place by the end of 2024. These programs are designed to educate users on AI capabilities and ensure that they stay updated on the latest features and functionalities.

Measuring ROI

Most organizations are keenly aware of the need to measure the return on investment (ROI) of their AI initiatives. A significant majority are tracking or plan to track AI-related time savings to quantify the impact of the technology.

Balancing Innovation and Control

While many organizations are embracing the potential of public AI tools, they are doing so with caution. Almost all respondents allow the use of these tools, but they often impose guidelines to mitigate risks and ensure compliance with organizational policies.

Conclusion

Generative AI is undoubtedly a powerful tool that can revolutionize the way we work. However, it’s essential to approach its implementation with a balanced perspective. By carefully considering the potential benefits and risks, organizations can harness the power of AI to drive innovation, improve efficiency, and enhance employee engagement.

Far too many CX leaders view customer service as an either/or decision when it comes to AI—either fully automate with virtual agents or rely entirely on live agents. But in reality, AI shines best with a “both/and” approach, blending human expertise with advanced technology.

This blend, known as “human-centric AI,” drives impressive improvements in business metrics by allowing humans and machines to collaborate effectively to solve customer issues. For instance, AI can suggest upsell opportunities to service agents, resulting in a 35% boost in revenue from the contact center. It also provides context that enables agents to personalize interactions, leading to higher customer satisfaction and increased referrals.

While AI-powered virtual agents now handle 22% of customer interactions autonomously, the role of humans remains critical. It’s their guidance and expertise that keep virtual agents on track and continuously improving.

Join Cresta and Metrigy for an engaging webinar, packed with research insights, practical advice, and digestible tech updates. You’ll learn:

• What types of AI are best suited for human-centric AI?
• Where are companies seeing success?
• Do customers want humans, AI, or both? What should CX leaders do to ensure success with this approach?
• How does human-centric AI affect staffing, compensation, and management?

Humans Still Matter (a lot) in CX, but AI Makes Them Better

Presented by: Robin Gareiss, CEO and Principal Analyst, Metrigy; Devon Mychal, Head of Product Marketing, Cresta

Date: December 5, 2024
Time: 1:00 pm ET

Let’s face it: We’re doing things much faster (for the most part) because of AI. Simply using generative AI to code faster has resulted in quicker time to market for many products and services in the customer experience (CX) space. This rapidly increasing pace of innovation not only affects technology vendors; it also affects businesses that buy the technology.

Metrigy’s Customer Experience Optimization 2024-25 global research study of 544 companies provides insights into how companies perceive and respond to the pace of innovation.

The State of Innovation

Most research participants (64%) said the pace of innovation is “just right,” while 22.5% said things are moving too quickly and they can’t keep up. Only 13.5% said the pace is too slow for them—these are the companies whose DNA values technology and allocates the budget to prove it.

Of course, one of the problems is that consumers aren’t quite keeping pace with innovation. For example, only 12.7% of consumers prefer using chatbots, 40% avoid them, and 47% use them selectively.

AI: A Catalyst for Innovation

A significant takeaway from the study is the role of AI in accelerating innovation. Nearly two-thirds of IT and CX leaders say AI-based products are speeding up their own CX innovation—reflecting a broader trend of AI being a transformative force that improves business metrics.

Successful companies have embraced the rapid pace of innovation: 80% of Metrigy’s research success group attribute at least some of their progress to the integration of AI innovation, while only 55% of companies in the non-success group report the same benefit. This discrepancy highlights a clear advantage for those who are leveraging AI. The success group has much higher measurable business metric improvements than the non-success group.

Decision-Making Trends: From Deep Dives to High-Level Insights

Though innovations are speeding up, most IT and CX leaders prefer to have a detailed understanding of them, vs. a high-level understanding, though that is slowly changing. Nearly 64% of companies say they prefer to have an in-depth understanding of all technologies before deciding what to buy to solve business problems and opportunities. On the flipside, 35% say they prefer to have a high-level understanding of technology, present problems/opportunities to their technology partners, and trust their recommendations. Slightly more cited the latter as their preference in August 2024 compared to January 2024, saying the pace of change in CX technologies is too fast to keep up.

Trusting recommendations from partners allows businesses to make informed decisions without getting bogged down in the minutiae of every technological development.

In the ever-evolving landscape of customer experience, organizations are constantly striving to improve their interactions with clients. Metrigy’s recent Customer Experience Optimization 2024-25 research study sheds light on the state of customer interactions and reveals key factors that differentiate successful companies from those lagging behind.

Metrigy asks all research participants a series of quantitative questions that measure the success of companies when they use various CX technologies. For example, how did the use of virtual agents affect customer satisfaction or revenue? If it increased or decreased either, by what percentage? Companies with the most measurable success were placed in a research success group, while those with the lowest measurable success were placed in a research non-success group. This enables us to compare behaviors of both groups.

Based on that analysis, here are a few areas CX leaders should consider to drive more success in business metrics.

People vs. Technology: Striking the Right Balance

One of the key takeaways from the study is the debate between the importance of people and technology in delivering successful customer service. The majority of companies still prioritize people over technology, with 77% saying the former is more important. However, the success group was more favorable toward technology. About 45% of the success group said technology plays a crucial role, while only 18% of the non-success group said the same. The top technology that helps to improve customer service is AI, underscoring the measurable value successful companies are already realizing with the technology.

Agents Need a Break!

Another area of focus for the success group when it comes to improving customer service is being attentive to agent experience. One of the big things the success group does is leverage AI to identify when agents need breaks during the day. Overall, 43.9% of companies are addressing the increased complexity of agent interactions by providing more 15-minute breaks each day. The success group is giving four more 15-minute breaks per day (in an eight-hour shift), compared to the non-success group, which is providing two more breaks. Adequate breaks not only prevent burnout but also ensure agents remain attentive and effective. Without these mental breaks, companies see higher turnover rates—and that affects customer service overall with fewer, experienced agents and more newly (and often inadequately) trained agents.

Transforming Customer Experience

The technologies and operational practices to manage an effective CX organization are ever-changing. That’s why so many companies are regularly engaged in CX transformation projects. We define CX transformation as the application of new or existing technologies to improve the agent and/or customer experience, ultimately driving measurable business value.

More than 60% of companies have completed, are in the process of completing, or plan to start a CX transformation project in 2024. Among those already finished, 61% say their projects were successful. The projects generally fall into three buckets: Apps and channels, foundational projects, and worker-focused projects. The research success group not only has completed more transformations than the non-success group, it’s also 83% more likely to have a successful outcome of their project.

Successful companies are focusing on the following projects significantly more than the non-success group: Adding or improving agent assist applications; adding or improving voice of the customer programs; improving CX security; moving functions to carrier networks; moving from on-premises to cloud platforms; improving agent hardware; and automating scheduling and capacity planning.

Metrigy’s research underscores the evolving nature of customer interactions and highlights the need for companies to regularly adapt their strategies. By addressing the aforementioned areas, businesses can increase their likelihood of driving more success, whether in the form of higher revenue, better customer satisfaction, or lower costs.

The alarming rise in contact center turnover rates negatively impacts agent morale, customer interactions and ROI. In many ways, AI is seen as both the cause and the solution.

Contact center turnover rates are on the upswing again and they don’t appear to be settling down anytime soon. Several factors contribute to high turnover rates, including AI, automation, agent burnout and the lack of qualified agents. High agent turnover can lead to bad customer experiences in the contact center, brand reputational damage and lost revenue. But businesses can take several actions to stem the flow of turnovers.

What is turnover rate and how is it calculated?

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With its AI capabilities, Microsoft Copilot provides several enhancements to Microsoft Teams functionality, including meeting summaries and action item follow-up.

Copilot for Microsoft 365 presents several productivity possibilities to users of the Microsoft 365 application suite, especially Microsoft Teams. Given its price of $30 per user, per month, business and IT leaders must understand the potential benefits of Copilot – and how best to implement it — before investing in the AI-powered tool.

What are the features of Copilot in Teams?

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In this episode, Jonathan Rosenberg, Five9’s CTO and head of AI, and Metrigy’s Robin Gareiss discuss the huge changes coming to customer experience in the next several years, driven largely by generative AI and contextual data.