The Payment Integrity Solutions PEAK Matrix® Assessment evaluates service providers based on their capabilities, technology, and market impact within the payment integrity solutions industry. Healthcare organizations are looking for ways to optimize processes through claims editing, itemized bill review, clinical reviews, coordination of benefits, subrogation, data mining, and more.

Healthcare organizations can use this assessment to identify top-tier partners that improve performance, enhance decision-making, and chart the best path to success.

By participating in this assessment, leading providers will have increased recognition in this essential area of healthcare.

What is a PEAK Matrix® Assessment?

PEAK Matrix® assessments are Everest Group’s service to our enterprise clients. We aim to include the most relevant players to help our clients make informed sourcing decisions based on the true and complete picture of the supplier space.

Vendors leverage these assessments to market their capabilities to enterprises and their clients. In addition to being a marketing tool, participants featured on the specialized PEAK Matrix assessment receive enhanced visibility and are viewed with trust in the marketplace.

Related PEAK Matrix® Assessments

PEAK Matrix®

Guidewire Services PEAK Matrix® Assessment 2024

Learn More

PEAK Matrix®

Life Sciences Regulatory and Medical Affairs Operations PEAK Matrix® Assessment 2024

Learn More

PEAK Matrix®

Insurance Intermediaries Services PEAK Matrix® Assessment 2024

Learn More

PEAK Matrix®

Marketing Services PEAK Matrix® Assessment 2024

Learn More

In our previous blog, we discussed how the advent of generative AI in our day-to-day lives has skyrocketed in the past few years, helping individuals and companies efficiently tackle tasks through automation and reduce the time taken to complete them. 

Furthermore, new applications of gen AI for business solutions are being developed at a breakneck pace across industries such as Retail And Consumer Packaged Goods (RCPG) Retail and Consumer Packaged Goods, Banking And Financial Services, Healthcare and Life Sciences, and Human Resources , among others.  

Additionally, companies are now expecting more tangible results from the implementation of gen AI to avoid losing market share. This is true for all the previously mentioned stakeholders: technology providers, service providers, and enterprises.  

At the same time, these stakeholders must be mindful of their critical role in fulfilling the DEIB (Diversity, Equity, Inclusion, and Belonging) mandate, which includes promoting inclusive and equitable practices in gen AI development and deployment. The absence of comprehensive DEIB measures in gen AI models can have detrimental effects both internally and externally. 

Furthermore, equitable artificial intelligence (AI) learning is essential. A survey conducted by a leading consulting firm, indicates that only 10-15% of businesses have established AI roles focused on fostering diverse perspectives within their teams.  

Professionals’ lived experiences provide critical insights for mitigating bias—a truth that all stakeholders must embrace. Before exploring potential solutions, it’s important to investigate the root causes of bias, the different types of biases present, and their implications, as our analysts have done below. 

Reach out to discuss this topic in depth. 

The Case for DEIB in Gen AI:

While technology offers substantial benefits, a significant DEIB challenge persists within current gen AI frameworks, leading to adverse effects for individuals and organizations. AI algorithms – a host of which are trained on existing framework models, lack diverse perspectives, and can mirror the biases of their creators, perpetuating inequalities and harming marginalized communities.

Cultural and social biases often infiltrate these systems, resulting in flawed outputs that do not accurately reflect varied experiences and knowledge.

Some benefits of unbiased gen AI Models include:

At the same time, adopting unbiased gen AI models can significantly benefit organizations by:

• Enhancing Decision-Making: Eliminating biases allows for more accurate, objective insights, improving decision-making across scenarios

• Improving Customer Insights: Objective data analysis helps businesses better understand customer needs, facilitating targeted marketing

• Promoting Diversity in Hiring: Unbiased AI can eliminate discrimination in recruitment, supporting diverse candidates, including neurodivergent individuals

• Streamlining Operations: Reducing bias in automated processes optimizes operations, enhancing overall efficiency and productivity

• Fostering Innovation: Bias-free AI models yield more diverse and creative ideas, propelling innovation across sectors

• Improving Risk Management: Unbiased AI provides clearer, balanced assessments, aiding organizations in identifying and managing risks effectively

• Ensuring Compliance with Ethical Standards: Utilizing unbiased AI aligns with ethical norms and best practices, fostering trust and accountability

• Creating a More Equitable Workplace: By promoting fairness, unbiased AI contributes to a more inclusive environment, driving organizational growth

A deep dive into the causes and types of the bias in terms of DEIB?

Gen AI models are statistical by nature and prone to errors, especially when lacking domain expertise. Currently, a small, homogeneous group often determines the data used for training these models. Many models are built on foundational frameworks such as BERT or RooBERTa, which can carry inherent biases if not addressed from the outset.

Types of DEIB bias include:

The social and business cost for business by utilizing a biased gen AI model:

Addressing these challenges is paramount for companies when accounting for the vast use cases of this technology across sectors. For example, 19% of organizations are leveraging AI to develop new products and services across the RCPG space, according to an Everest Group insight.  

Similarly, 40-45% of business leaders of mega enterprises (revenue exceeding US$ 1 billion) have reported successful implementation of gen AI across various operations in this Everest Group viewpoint. We expect this number to consistently increase in the coming years.  

If the models used for these products or services produce biased results or incorrect outcomes (an important component of ‘hallucinations’), it could negatively impact the companies’ reputations and their bottom lines. Thus, there are both direct and indirect costs associated with leveraging these models. The two key types of costs that businesses would suffer from are the following: 

Business Cost: The direct financial expenses incurred by a business, including production costs, operating expenses, and the costs of complying with regulations. These costs can be both internal and external to the business 

Social Cost: The total economic cost to society, including both direct costs borne by individuals and businesses, as well as indirect costs such as environmental damage, decreased quality of life, and social inequality 

While unbiased AI models are essential, their development and deployment can be costly. Collecting high-quality data for model training, designing and customizing AI models from scratch, and employing sophisticated techniques and specialized talent all contribute to the complexity.  

Additionally, scaling these models across large organizations or multiple geographies can introduce new biases due to variations in cultural, linguistic, and socioeconomic factors. Therefore, companies must be deliberate in identifying which products, services, or functions truly require such AI models.  

In response, some organizations have appointed Chief Diversity, Equity and Inclusion (DE&I) Officers, but this approach may be limited, as these officers typically focus on talent acquisition and retention.  

Effectively addressing AI’s DEIB impact requires input from multiple leaders, including the Chief Information Officer (CIO)/ Chief Technology Officer (CTO), Chief Product Procurement Officer (CPO), Chief DE&I Officer, and Chief Sustainability Officer, making it both resource- and cost-intensive. Furthermore, while algorithmic impact assessments are well-intentioned, they often fall short in fully capturing the broader social implications of AI models. 

To address this challenge, Everest Group has developed a framework that stakeholders can use to navigate these complexities effectively, with the overarching principle of the “Comprehensive Inclusion Framework” viewed from both an internal and external perspective. This principle is broken down into four key areas: 

• Inclusiveness emphasizes broad representation in the entire AI development lifecycle. It ensures that diverse perspectives, experiences, and needs are considered when designing, developing, and deploying AI systems 

• Impartiality ensures that AI decision-making processes are neutral, objective, and free from bias or unfair influence by continuously assessing the outputs of the model and checking for impartiality. Thus, blending in objective data driven insights 

• Equity, in the context of AI ensures that all user groups experience fair and just outcomes from AI systems, regardless of their background, demographics, or identity  

• Accessibility, focuses on making sure that AI technologies are usable and beneficial to all individuals, regardless of their socioeconomic status, disabilities, education, or geographic location 

The framework provides a comprehensive approach to integrating gen AI and DEIB policies within organizations across vertical and horizontal processes. It categorizes various policy combinations based on the level of emphasis placed on AI and DEIB and offers recommendations to achieve optimal alignment. The categories include: 

• Low DEIB Impact: DEIB efforts are not prioritized due to the lack of strong business or social cases 

• Medium DEIB Impact: DEIB efforts are focused on business and social benefits, with AI considered a tool to enhance these case 

• High DEIB impact: DEIB values are deeply integrated into organizational culture, using AI to drive inclusivity and equity throughout the business 

The current state of the market in terms of DEIB embodiment by stakeholders: 

As mentioned in our last blog post, across stakeholders, the current level of DEIB integration according to our ROLE framework is as follows: 

As gen AI increasingly influences business operations, stakeholders must prioritize DEIB in their AI development and deployment efforts.  

Tackling inherent biases and fostering fairness will not only mitigate risks but also enhance decision-making, customer insights, innovation, and workplace equity. By adopting frameworks such as Everest Group’s “Comprehensive Inclusion Framework”, organizations can effectively align their AI and DEIB strategies, ensuring long-term success and ethical compliance. 

We are actively tracking the evolution of artificial intelligence and its impact on the future of all sectors. To discuss the latest trends and their implications for brands, technology vendors, and service providers alike, feel free to reach out to Kanishka Chakraborty (kanishka.chakraborty@everestgrp.com), Meenakshi Narayanan (meenakshi.narayanan@everestgrp.com), Abhishek Sengupta (abhishek.sengupta@everestgrp.com), Abhishek Biswas (abhishek.biswas@everestgrp.com), Rita Soni (rita.soni@everestgrp.com) and Cecilia Van Cauwenberghe (cecilia.vancauwenberghe@everestgrp.com). 

If you found this blog interesting, check out our blog focusing on Building Purpose-Driven Generative AI (gen AI) – Why We All Have A Role To Play In The Future Success Of The Gen AI Ecosystem  | Blog – Everest Group, which delves deeper into the subject of gen AI. 

This is the first of a new series of blogs, with plenty more to come in 2024 and 2025! 

Today, most enterprises either want to adopt this game-changing technology or are looking to build their own gen AI capabilities, but at what cost? Reach out to us to discuss this topic further with our expert analysts.

Billions of dollars have now been invested into building and leveraging gen AI, with the hope that it will improve business operations with unprecedented productivity improvements.

Similarly, on the information technology (IT) services side, many service providers have begun investing in proprietary gen AI solutions to pass on the associated efficiencies to their clients, all while identifying new use cases during delivery. While the offering of gen AI-driven productivity was considered a differentiator for providers in 2023, this has become a table stake in the past two to three quarters. Despite all of this, a big question remains: “Is the providers’ proposition aligning with client expectations regarding ROI?”

In this blog, we delve deeper into the current expectations in IT outsourcing deals.

Demanding more from gen AI: enterprises raise the bar:

With a varying degree of success from the proof of concepts (POCs), enterprises now expect service providers to clearly demonstrate a visible return on investment before approving fresh investments. Enterprises are now expecting clear call outs on both capabilities, as well as true efficiencies from their gen AI solutions.

In this regard, some of the leading providers have started to highlight specific details as a part of their gen AI solution value proposition, such as:

1. Quantifying productivity: What are the incremental productivity gains over the deal term?
2. Cost benefits: How would the improvement in productivity translate into noticeable cost benefits? This should take into consideration the reduction in the overall Total Contract Value (TCV) of IT outsourcing deals, both with and without the gen AI proposition
3. Intangible benefits: How will the gen AI solution lead to an enhanced user experience? For example, highlighting potential reduction in the meantime to resolve (MTTR) or improvement in customer satisfaction (CSAT) scores

Please note that with the advent of new technologies like Agentic AI, the cost implications and the productivity benefits are also expected to increase in the future.

The gen AI return on investment (ROI) dilemma: Is it worth the hype?

Despite the allure of gen AI, executives are under increasing pressure to justify its seemingly hefty price tag. Demanding an ROI of at least 2-2.5x, they’re wary of projects that fizzle out after initial proofs of concept due to the soaring costs and its unclear benefits.

To address these concerns, enterprises are demanding greater transparency and more accountability from providers, scrutinizing costs associated with resources, infrastructure, data, and large language models (LLMs).

There are also concerns around the associated capital expenditure. In response to these demands, providers are strategically positioning gen AI as a long-term value proposition by amortizing the upfront costs over the contract period. In most cases, especially in competitive IT services opportunities, we are also observing a few leading providers proposing gen AI solutions as an investment from their side.

To safeguard the interests of both parties, contracts are now evolving to include detailed discussions on risk, regulatory compliance, commercial impact, and implementation costs. Periodic benchmarking clauses are also being negotiated to ensure ongoing accountability and prevent unforeseen expenses.

Everest Group partners with both enterprises and leading IT service providers on mandates related to pricing strategies, productivity gains, and pricing impact related to gen AI.

If you found this blog interesting, check out our virtual event, Gen AI Unhyped: How It Is Evolving and How to Plan for Success.

To discuss this topic in more detail or for a detailed analysis, contact us at benchmarking@everestgrp.com, or please contact prateek.gupta@everestgrp.com and anubhav.jain@everestgrp.com.

Everest Group’s PEAK Happy Hour in DFW

Thursday, April 18, 2024 |
5 – 7 p.m. CDT

Please join us for a happy hour with Everest Group. The evening will be an opportunity to network with industry peers in the DFW area.

Join us to catch up, exchange ideas, and make new acquaintances!

This invitation-only event will be held on Thursday, April 18, 2024, from 5  to 7 p.m. at Haywire at the Whiskey Lounge Fireplace, 5901 Winthrop Street, Plano, Texas 75024.

Our Hosts

Amy Fong
Partner


Jimit Arora
Managing Partner


Shirley Hung
Partner


Eric Simonson
Managing Partner

Register to RSVP

Catch Krishna Charan, Vice President at Everest Group, during this LinkedIn Live session to discover insights into building a sustainable talent strategy. They will discuss how by maximizing resources, organizations can successfully navigate through periods of lull in demand.

Register

Krishna Charan
Vice President, Everest Group
Fernanda Aultman
Senior Director of Customer Experience at Pontoon Solutions
Rachel Quisenberry
Talent Acquisition Operations Leaders at Cummins Inc.
Bob Zebrowski
Director, External Workforce Programs at Sanofi North America

Price Benchmarking

LEARN MORE ABOUT OUR PRICING SERVICES