Next-generation KPIs for Digital Customer Experience Management Adoption | Market Insights™
January 26, 2024
Customer Experience Management
Customer Experience Management
Customer Experience Management
Customer Experience Management
Selecting the right Large Language Model (LLM) is critical for developing the best-suited generative AI (gen AI) solution. However, choosing an LLM on the number of parameters alone can be a costly mistake as larger size alone doesn’t always equate to better performance. Discover a comprehensive framework that evaluates and compares more than a dozen LLMs on 27 key parameters to enhance enterprise decision-making.
Since the fervor surrounding gen AI started in November 2022, the explosion of LLMs is redefining language understanding and generation boundaries. As more models continue to emerge, evaluating them presents a significant challenge. A more structured and detailed approach is critically needed to evaluate these massive models that goes beyond assessing them solely on their sheer number of parameters.
Given the rising interest in gen AI across diverse applications, the lack of comprehensive research into LLM evaluation is striking. Relying solely on the parameter count when choosing an LLM can be misleading. It neglects crucial performance aspects, increases implementation costs, hinders enterprise readiness, enhances risk, and more. As these LLMs shape interactions and decision-making, an all-inclusive evaluation framework is essential to navigate their impact effectively.
Building on inaugural research in this area, Everest Group has assessed LLMs on multiple parameters and showcased how they rank against each other to help enterprises make the best and most informed decisions.
Everest Group’s AI LLM Assessment presents a comprehensive framework, offering valuable guidance for stakeholders seeking to understand the various elements of LLMs. This assessment meticulously evaluates 13 leading LLMs across 27 distinct dimensions.
The framework evaluates LLMs’ unique capabilities, enabling a deeper understanding of their functionalities. Consequently, enterprises can determine which LLMs are fast, user-friendly, and capable of handling large amounts of input data for practical implementations.
The AI LLM Assessment evaluates various capabilities through such dimensions as the number of tokens they can process, the modalities supported, inference speed, training data quality, and overall market perception. These factors ultimately become differentiators, setting LLMs apart from peers and predecessors.
Below is a snapshot of the Everest Group AI LLM assessment matrix or explore the full framework.
Recently, we have witnessed numerous technology providers developing their LLMs. Each model aims to outperform the others by emphasizing its larger size compared to its peers and previous iterations. However, it is rarely discussed whether having more parameters and larger datasets actually enhances the ability to deliver value across various use cases.
LLM advancements have highlighted a fascinating trend where smaller models like PaLM 2 have demonstrated superior performance despite being trained on fewer parameters than their predecessors. These compact models not only offer better performance but also deliver faster inference times and reduced processing costs. This underscores that larger models may not always be the only way to achieve the desired outcomes.
Deciding which LLM is the best fit for enterprise applications and use cases based on LLM capabilities and features is the most crucial step in developing a gen AI solution. After assessing a model for these variables, understanding how easily it can be integrated into enterprise operations is vitally important.
To address this need, the framework takes into account the feasibility of practical implementation, considering factors such as the average implementation cost based on usage and ecosystem readiness. The framework also examines the selected LLMs for potential risks that may hinder enterprise adoption.
By considering capability versus adoption ease, the framework offers enterprises a balanced approach for analyzing LLM attributes and functionalities while also accounting for the associated challenges and considerations to integration and utilization.
This framework has the potential to help developers enhance their capabilities over peers in building new LLMs tailored for specific tasks or applications by better understanding competitors’ strengths and weaknesses.
While LLM evaluation is undeniably complex and continuously evolving, this framework provides a vital starting point. As Everest Group continues to track developments in the gen AI landscape, we welcome discussing potential use cases, risk and cost considerations, and the impact of gen AI across various industries.
Please reach out to Priya Bhalla, [email protected], Vishal Gupta, [email protected], Vaibhav Bansal, [email protected], Yukta Sharma, [email protected], or Vatsalya Singhal, [email protected] to discuss generative AI topics further.
In 2023, we witnessed massive investments in generative AI, with the majority coming from the supply side. Despite the initial fervor ignited by ChatGPT, the anticipated surge in enterprise adoption is yet to come. One factor contributing to this delay is the need for real-world implementation examples to make adoption more realistic and attainable.
In this webinar, our expert analysts explored the hype vs. reality of generative AI, showcased actual production-level use cases, addressed challenges head-on, and provided a glimpse into the future of this transformative technology as we move into 2024.
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For decades, custom applications were the norm, allowing organizations to create applications designed to meet the unique requirements of the business.
With the growing popularity of citizen developers using local or no-code platforms, is there value for custom applications? Ankit Gupta, Practice Director at Everest Group, spoke with PodChats for FutureCIO to shed light on the future of custom applications.
Generative Artificial Intelligence (AI) is poised to revolutionize customer experience management (CXM) by creating personalized, empathetic, and more fulfilling experiences that drive brand loyalty and business growth. In this blog, explore examples of early generative AI adoption and learn about the benefits and challenges of this game-changing technology.
Learn more on this topic in the webinar, The Generative AI Advantage in Enterprise CXM Operations.
As contact centers shift their main focus from improving efficiency to creating impactful customer experience, generative AI is leading the charge in this new direction. Recognizing generative AI’s promise to enable the personalized, hyper-contextual interactions customers desire, enterprises are looking to invest and deploy solutions to leverage its transformative potential.
A recent Everest Group survey revealed nearly 60% of enterprises believe generative AI solutions have huge potential to disrupt the current contact center landscape. Additionally, another 37% perceive these solutions as beneficial in some areas.
By mimicking human creativity, generative AI can create nuanced and contextually relevant content. This opens a wide range of possibilities to reshape the way brands engage with customers across various touchpoints and provide the following benefits:
Enhanced customer service
Contextual marketing
Building stronger relationships
With vast potential applications, enterprises across vertical markets are already reaping the rewards of early-generation AI adoption. Let’s explore some pioneering examples:
While generative AI’s potential benefits are intriguing, addressing the inherent challenges that come with its implementation is critical. Enterprises have expressed a wide range of issues, from regulatory to accuracy, that could arise with generative AI. The top three enterprise concerns to generative AI adoption are:
The changing landscape of generative AI in CXM is a testament to the transformative power of technology. The generative AI revolution is here, and it’s poised to significantly alter the way brands interact with their customers. By responsibly and strategically embracing this technology, CXM service providers can create personalized, empathetic, and, ultimately, more rewarding customer experiences, leading to stronger brand loyalty and increased business growth.
To discuss generative AI adoption trends in CXM, please contact Chhandak Biswas, [email protected] and Rishav Kumar [email protected].
Discover how enterprises are looking at generative AI-based solutions adoption to improve CX in the webinar, The Generative AI Advantage in Enterprise CXM Operations.
By leveraging generative Artificial Intelligence (gen AI), brands can elevate influencer marketing to the next level by creating compelling content that connects more deeply with consumers. In this blog, discover how AI influencers are changing the influencer marketing market and key factors brands should consider.
In an increasingly digital world, consumers seek personalized connections and are drawn to influencers who embody relatable lifestyles and offer trustworthy recommendations. Brands recognize the potential of influencer marketing to enhance visibility, credibility, and engagement. Influencer marketing fosters genuine connections that resonate with today’s consumers and provides brands with a powerful platform to amplify their message in the crowded digital marketplace.
Let’s take a look at how consumers and brands perceive influencer marketing.
Quick cut to the gen AI disruption – where cutting-edge technology meets influencer creativity. With its capability to produce creative text formats, images, and videos, gen AI brings a new opportunity to this market. It has the potential to empower influencers to craft compelling content at scale that uniquely resonates with followers.
Influencers now find themselves equipped with innovative means to captivate audiences, experiment with storytelling formats, and consistently produce engaging content that reflects the pulse of their followers.
Callout: “A survey of consumers across the UK and the US found a majority (60 percent) prefer creator content designed using gen AI. An additional poll of content creators found most (81 percent) reported more favorable audience engagement with content designed using AI technology.”
Let’s look deeper at how gen AI is being used in influencer marketing.
The use of AI influencers in marketing is a relatively recent development that has gained significant traction. High-profile brands such as Prada, Versace, Red Bull, and Tinder have all activated AI influencers for social media promotions. Although the results driven by AI influencers are similar to those of human creators, the key difference lies in creating a relatable brand presence in consumers’ minds.
In the graphic below, we compare the skill levels of human and AI influencers in important areas:
With their complementing skills, virtual and human influencers can create engaging content at different ends of the same spectrum. As gen AI becomes more prevalent in the influencer industry, balancing authenticity and AI-generated content will be crucial to maintaining genuine connections.
While the intersection of gen AI and influencer marketing presents a transformative landscape for brands to connect with their target audience, a few areas of concern still need to be addressed, including:
As influencer marketing evolves, the future is oriented toward adopting an omnichannel and full-funnel strategy. This entails brands leveraging influencer content across diverse marketing channels, from connected television (CTV) ads to opportunity-to-hear (OTH) display ads. By taking this approach, brands can establish influencer-led paid media and integrate it with commerce, removing steps in the customer journey and ultimately driving faster conversions.
To discuss the growing role of AI influencers in the influencer marketing market, contact [email protected] and [email protected].
Join our webinar, The Generative AI Advantage in Enterprise CXM Operations, to learn how enterprises are looking at generative AI-based solutions adoption to improve customer experiences.
DALLAS, January 18, 2024 — If chief information officers (CIOs) have their way in 2024, expect to see more enterprises making adoption of generative artificial intelligence (gen AI) a strategic priority with an aim to move past small pilots to scaled implementations. This forecast summarizes the sentiments of more than 50 CIOs interviewed by Everest Group in collaboration with Yates Ltd. The survey also revealed that improving the velocity of existing operations is the primary motivation driving enterprise gen AI initiatives.
The interviews conducted with global CIOs between October 23, 2023, and January 24, 2024, also underscore that gen AI is more than a passing trend, having successfully penetrated early enterprise adoption thresholds. Nearly 83% of global enterprises are either actively testing their capabilities through pilot programs or have already adopted gen AI for one or more production-grade use cases.
Key Findings from the Survey:
The full report of findings — “Capturing the Generative AI Pulse: An Exploration of the CIO Mindset” — identifies the current state of enterprise generative AI adoption and the key challenges in scaling AI initiatives. The report also showcases three waves of generative AI adoption levels for enterprises and provides guidance to help enterprises advance in their generative AI adoption journey. Download the full report.
“Unquestionably, gen AI hype dominated 2023, but our survey indicates that it is more than a passing trend,” said Abhishek Singh, partner at Everest Group. “Our research clearly documents that most organizations are in what we call ‘Wave 1’ or the pilot phase of gen AI adoption; however, in 2024 and 2025 we fully expect more organizations to advance to the ‘Wave 2’ phase of production-grade deployments.
“Although enterprise adoption of gen AI is far from its anticipated peak, enterprises continue to experiment with unique use cases in a wide variety of industries, ranging from high-tech and financial services to healthcare and retail,” continued Singh. “As more of these initiatives document measurable impact, we’ll see adoption and full-scale implementation of gen AI accelerate considerably.”
Everest Group maintains that this shift from Wave 1 to Wave 2 will demand that enterprise leaders cultivate data-driven cultures and invest in digital and data maturity. Successful transitions will also require a comprehensive approach that incorporates technological advances, organizational readiness and ethical considerations.
“Gen AI is transforming senior executives’ perspectives on efficiency, growth and competitive advantage, and will revolutionize their operational strategies,” stated Charlotte Yates, the founder and CEO of Yates Ltd. She emphasized the need for a forward-thinking blueprint in Wave 2 to effectively implement gen AI use cases: “This blueprint should address a wide range of opportunities, risks, and investments in platforms, operating models, organization design, governance, strategic partnerships and culture.”
Yates is an IT and business consultancy that partners with senior executives to create the strategy, blueprints, financial mechanisms and execution plans to drive and achieve transformation. Our clients gain measurable cost savings, new capabilities, and the ability to outperform their competition. Our areas of focus include enterprise networks, software, managed services, end user services and automation. Services include strategy, sourcing, program execution, change management, communications and governance. Yates Ltd. is a WBENC-certified woman-owned business.
Everest Group is a leading research firm helping business leaders make confident decisions. We guide clients through today’s market challenges and strengthen their strategies by applying contextualized problem-solving to their unique situations. This drives maximized operational and financial performance and transformative experiences. Our deep expertise and tenacious research focused on technology, business processes, and engineering through the lenses of talent, sustainability, and sourcing delivers precise and action-oriented guidance. Find further details and in-depth content at www.everestgrp.com.
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