Initially benefiting from a pandemic-induced digital services boom, India’s $245 billion information technology industry has been facing challenges in recent quarters as clients cut spending on discretionary projects amid inflationary pressures and global economic uncertainty. Salary expenses constitute the largest contributor to costs for IT companies, typically accounting for over 60 percent.
Wipro is reportedly considering skipping salary hikes for “top performers with higher compensation” in its largest business line during the upcoming round of salary revisions scheduled for December. The decision comes as the company grapples with various challenges, including weak client spending and fierce competition from larger rivals.
Peter Bendor-Samuel, CEO of Everest Group, notes that the additional attrition could help rebalance benches to meet demand and bring costs back into balance with demand.
Digital Interactive Experience (IX) Services – North America
In North America, enterprises are tightly interweaving the growing importance of experience design with their investments in emerging technologies such as generative AI, metaverse, and blockchain. Customers no longer view a captivating and well-tailored experience as a mere luxury; it has become an imperative. North American consumers are demanding top-notch services and craving seamless, personalized, and ethically conscious interactions with enterprises.
In parallel, businesses are recognizing that, in their quest to attract and retain top talent, creating a thoughtfully designed employee experience across the interaction touchpoints of the employee lifecycle has become vital. Moreover, experience design is extending its influence on partners, as efficient and user-friendly interfaces are becoming the linchpin for successful collaboration and mutual growth.
As the narrative evolves, North American society is prioritizing sustainability and ethical business practices. In summary, experience design, bolstered by investments in cutting-edge technologies, is not just a trend but a fundamental driver for business growth and social responsibility in North America. It profoundly shapes the future and impact of enterprises in the region, aligning their operations with the values and aspirations of a rapidly changing market.
In this report, we assess 26 providers featured on the Digital Interactive Experience (IX) Services PEAK Matrix® Assessment 2023 – North America, a comprehensive matrix that evaluates and categorizes providers on their capabilities and market impact.
In this report, we:
Assess 26 leading North American digital IX service providers and design agencies on Everest Group’s PEAK Matrix® evaluation framework
Categorize providers as Leaders, Major Contenders, and Aspirants
Evaluate providers’ key strengths and limitations
Scope
All industries
Geography: North America
The assessment is based on Everest Group’s annual RFI process for the calendar year 2023, interactions with leading IX service providers, client reference checks, and an ongoing analysis of the digital IX services market
The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.
Wipro may skip giving hikes to “top performers with higher compensation” in its largest business line in the upcoming round of salary revisions in December, according to an internal memo seen by Reuters.
Such a move might affect employee morale and lead to more attrition, according to Peter Bendor-Samuel, CEO at Everest Group. “The additional attrition will help rebalance benches to meet demand, and will help bring cost back into balance with demand,” he added.
The demand for cloud security services in the global business landscape is accelerating due to enterprises’ digital transformation mandates, rising importance of data protection, and challenges in securing hybrid multi-cloud environments. The need for effective cloud security solutions has intensified due to the expansion of cloud infrastructure, which has led to larger attack surfaces, rising cyber threats, complexities in posture management, and frequently changing regional cloud governance and security policies.
In response to stricter data protection regulations, enterprises face growing pressure to comply with data privacy laws and address increasing cybersecurity threats. The post-pandemic landscape, characterized by remote work and security vulnerabilities, has intensified cyber risks. Enterprises are prioritizing cloud security services to offer comprehensive end-to-end protection across complex hybrid multi-cloud systems. Cloud security providers are expanding their capabilities to meet these demands, emphasizing a platform-driven approach with next-generation features such as DevSecOps, automation, and zero trust. Collaborative efforts with cloud-native and third-party security providers are vital to provide sophisticated, adaptable, and globally compliant cloud security services.
In this report, we assess 18 global cloud security providers featured on the Cloud Security Services PEAK Matrix® Assessment 2023. The research will help buyers select the right-fit provider for their needs, while providers will be able to benchmark themselves against each other.
The assessment is based on Everest Group’s annual RFI process for the calendar year 2023, interactions with leading cloud security providers, client reference checks, and an ongoing analysis of the cloud security services market
The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.
Enterprises pursuing digital transformation are exploring cutting-edge next-generation technologies to gain a competitive edge, drive business model innovation, and expand their operational capabilities. However, to achieve the desired benefits without disrupting their existing operations, implementing comprehensive Quality Engineering (QE) processes for these next-generation technologies is vital. To assist enterprises in their journey toward quality transformation with the adoption of next-generation technologies, providers are investing in innovation and enhancing their capabilities in areas such as cloud, AI, IoT, blockchain, and extended reality.
In this report, we assess 35 next-generation QE service providers featured on the Next-generation Quality Engineering (QE) Services PEAK Matrix®. Each profile provides a comprehensive picture of the provider’s service focus, key Intellectual Property (IP) / solutions, domain investments, and case studies. The study will enable buyers to choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performance against each other.
In this report, we deliver:
Everest Group’s services PEAK Matrix® evaluation of 35 QE service providers
The characteristics of Leaders, Major Contenders, and Aspirants in the provider landscape
Providers’ key strengths and limitations
Scope
All industries and geographies
The assessment is based on Everest Group’s annual RFI process for calendar year 2023, interactions with leading next-generation QE service providers, client reference checks, and an ongoing analysis of the quality engineering services market
The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.
In the current healthcare landscape, patient engagement platforms play a vital role. They serve as a crucial link between patients and healthcare providers, promoting proactive healthcare management. As consumers increasingly demand personalized and accessible healthcare services, these platforms give patients real-time access to their medical information, telehealth options, and appointment scheduling. This not only enhances the patient experience and satisfaction but also plays a vital role in optimizing healthcare resources and improving outcomes. Furthermore, within a rapidly evolving digital health ecosystem, patient engagement platforms are essential in ensuring compliance with regulatory requirements and data security, contributing to healthcare businesses’ overall efficiency and success.
In this report, we assess 19 patient engagement platform providers featured on the Patient Engagement Platforms PEAK Matrix®. The study will enable buyers to choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performance against each other.
In this report, we:
Assess the market trends for patient engagement platforms
Examine enterprise sourcing considerations
Study providers’ key strengths and limitations
Scope
Industry: healthcare
Geography: global
The assessment is based on Everest Group’s annual RFI process for the calendar year 2023, interactions with leading patient engagement platform providers, client reference checks, and an ongoing analysis of the patient engagement platforms market
The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.
Life Sciences Next-generation Customer Engagement Platforms (CEP)
Since the pandemic, industries worldwide have shifted their investment priorities to focus on delivering personalized Customer Experience (CX), and the life sciences commercial function is no exception. To stay resilient and keep pace with the evolving landscape, the life sciences industry has begun embracing technology to differentiate itself for end users. However, enterprises face challenges with legacy data infrastructure and fundamental technology tools such as Customer Relationship Management (CRM), content management systems, and marketing tools that lack experience-focused functionality. As a result, enterprises are enhancing CRM platforms by partnering with niche platform providers to develop CX-centric solutions that enable omnichannel engagement, deliver the right messaging, unlock real-time customer analytics, etc., resulting in improved business performance and a competitive edge. Consequently, many next-generation customer engagement tools and platforms are bridging the gap between traditional CRMs and contemporary CX platforms.
In this report, we assess 23 life sciences next-generation Customer Engagement Platform (CEP) providers featured on the Life Sciences CEP PEAK Matrix®. The study will enable buyers to choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performance against each other.
In this report, we:
Examine the provider landscape for CE platforms and products
Assess 23 life sciences CEP providers on several capability and market success-related dimensions
Scope
Industry: life sciences
Geography: global
The assessment is based on Everest Group’s annual RFI process for the calendar year 2023, interactions with leading life sciences CE platform providers, client reference checks, and an ongoing analysis of the life sciences customer experience platforms market
The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.
The adoption of generative AI technology poses four major types of threats to enterprises: data privacy and security, reliability and explainability, responsibility and ownership, and bias and ethics. By assessing current risk levels andimplementing practices, tools, and systems to manage these challenges, enterprises can realize the most value from this transformative technology. Learn more about evaluating generative AI risk to gain an edge in this blog. Learn more about our Generative AI Risk Assessment.
Generative Artificial Intelligence (AI) has captivated popular imagination like nothing else, promising a future filled with endless possibilities. For the first time, this technology can create art, synthesize human voices, and generate human-like responses to questions.
Open AI’s ChatGPT triggered the mainstream adoption of generative AI, racking up more than 100 million monthly active users within just two months of its launch. Today, more than 300 startups are developing various generative AI-related applications.
Enterprises globally have recognized generative AI’s emergence as a watershed moment and are scrambling to identify the best way to leverage its capabilities. Numerous use cases across industries and functions have already emerged and are being piloted.
Many technology providers have incorporated generative AI as an integral part of their solutions, and others are forging relevant partnerships to jump on the bandwagon.
However, while many organizations are excited about long-term generative AI adoption, few fully consider the potential risks. In this blog, we will delve deeper into the importance of generative AI risk assessment.
To realize maximum value from generative AI adoption, enterprises must undertake a structured incremental approach (as illustrated in Figure 1). This framework involves prioritizing use cases, assessing adoption risks, identifying suitable providers, adapting existing operating models, providing effective governance and change management, and reviewing performance against expectations.
Figure 1: Generative AI adoption framework
Generative AI risks
Generative AI’s ease of usage has accelerated its adoption, highlighting both its value and its risks. Broadly, generative AI risks can be grouped into four categories: data privacy and security, reliability and explainability, responsibility and ownership, and bias and ethics (as shown below in Figure 2).
Figure 2: Generative AI risk categories
Let’s look at how these risks typically manifest and some examples:
Data privacy and security: Regulatory fallout from undisclosed data collection and retention is a key issue with generative AI models. This stems from the practice of developing AI models that can address a broad range of topics, rather than training data for a specific purpose. Further concerns include employees inadvertently sharing confidential enterprise data through user prompts or training data. In some cases, unfiltered prompts may allow employees access to data beyond their purview. From a cyber threat perspective, generative AI raises the risk of data breaches through malware, phishing, and identity theft
Samsung employees pasted confidential source code into ChatGPT to look for errors and optimize the data, inadvertently adding it to ChatGPT’s training data pool that can possibly be accessed by others.
Reliability and explainability: The quality and representativeness of training data greatly influence the accuracy of output produced by generative AI models. Deficiencies in the training data manifest as errors in generated content that may have serious legal ramifications beyond eroding customer trust. Furthermore, in the absence of required information, generative AI models may even fabricate information to answer a question. This leads to a false sense of expertise and can mislead the average user. Without a confidence score that estimates the likely accuracy of the generated content or some other equivalent mechanism, enterprises will need to develop and operationalize fact-checking of AI-generated content
During Microsoft’s Bing chat demo, the search engine was asked to analyze earnings reports from Gap and Lululemon and in comparing its answers to the actual reports, the chatbot missed some numbers and made some up.
Responsibility and ownership: The legal ownership of a piece of content produced by generative AI raises complex questions. Does it belong to the enterprise that licensed the generative AI product or the company that owns the generative AI product? Moreover, do individuals or organizations whose content was used to train the AI model partially own any subsequent content produced by the AI? These legal quandaries currently lack clear answers. An evident problem is generative AI producing output that contains distinct and identifiable pieces of Intellectual Property (IP) owned by others. This can lead to potential legal fallout for the entity that deployed the generative AI model. Enterprises need to work with their legal teams to evolve their IP management amid widespread generative AI adoption
“Zarya of the Dawn” is a graphic novel written by Kris Kashtanova who used an AI based image generation software called Midjourney to create illustrations for the novel. After having initially given full copyright protection for the novel, the US Copyright Office later restricted the copyright to only the text and the arrangement of the illustrations and not the illustrations themselves. The justification provided was that copyright protection could only extend to human creators.
Bias and ethics: An AI trained on biased data will propagate those biases, potentially leading to the generative AI producing discriminatory and stereotypical content. Failing to identify and preemptively remove such content through effective moderation can lead to severe reputational and legal ramifications for the enterprise and the generative AI provider.
Widespread generative AI adoption has the potential to ramp up carbon emissions from training and operating AI models. This can have significant implications for an enterprise’s Environmental, Social, and Governance (ESG) goals
In a study conducted by Bloomberg on Stable Diffusion (an AI-based text-to-image software), the rendering of more than 5,000 images for people with high- and low-paying jobs was full of racial and gender stereotypes. The results indicated men and individuals with lighter skin tones accounted for most high-paying roles.
How can enterprises assess their risk exposure to generative AI?
While the risks emanating from generative AI usage are notable, its benefits are too significant for enterprises to ignore. Consequently, enterprises that can leverage generative AI’s strengths while effectively mitigating its risks will outperform their peers. To effectively draw up a risk management plan for generative AI, enterprises need to first assess their current risk exposure to generative AI.
Everest Group has developed a multi-dimensional risk assessment framework (see Figure 3) to help enterprises take stock of their current risk profile for generative AI adoption. This framework is deployed through a tool that comprises 21 questions spanning the four risk categories mentioned above.
Figure 3: Everest Group’s generative AI risk assessment framework
Responses provided by the enterprise across the four categories are weighted and aggregated to arrive at a risk score (see Figure 4).
Figure 4: Generative AI risk assessment outcomes
Evaluating the risk exposure from generative AI is a necessary step to successfully implement and leverage generative AI to create value for customers. Incorporating appropriate risk management practices, tools, and mechanisms in the generative AI ecosystem can instill the confidence needed to take bigger bets, create differentiation, and fully harness this transformative technology.
Israeli surveillance systems, supposed to be the best in the world, failed to detect the recent attack by Hamas. This has raised doubts about the system’s reliability.
Kumar Avijit, Practice Director at Everest Group, said considering the recent shortcomings of Israeli tech in confrontations with Hamas, nations like India that are investing or considering the acquisition of similar technologies might reconsider their stance.
Despite all the hype around generative AI, Indian IT firms are yet to see any big spending coming in this space, which will be able to push up revenue growth.
“We have seen discretionary spend reduced significantly driven by a pause to allow the tech abstention after the COVID boom and economic uncertainty. Although there is a lot of talk about generative AI, this has not translated into significant spending yet,” Peter Bendor Samuel, CEO of Everest Group, told Bizz Buzz.
