Category: Blog

Driving Sustainable Change: A Look into the Insurance Industry’s Commitment to Sustainability | Blog

Embracing sustainability in the insurance industry is not just a choice, but a necessity for a resilient future. By integrating Environmental, Social, and Governance considerations into their practices, insurers can mitigate risks and foster long-term value for customers, shareholders, and the planet.

Sustainability has been a pivotal issue for years, but the recent conditions induced by the storm of the COVID-19 pandemic’s economic effects and the escalating climate change impacts across the world have increased pressure on industries across the globe to be aware of their Environmental, Social, and Governance (ESG) footprint. The financial services sector has not been behind in the race to drive the global sustainability agenda, largely driven by the BFS industry in the past. However, over the past few years, the insurance industry, being a key player in this sector, has also recognized the importance and urgency of embracing various practices in its operations to contribute to a sustainable planet. By integrating sustainability into various aspects of their operations, insurers are not only mitigating risks associated with climate change and environmental degradation but also fostering long-term resilience and contributing to a more sustainable future. This blog will explore how the insurance industry is driving the sustainable change through technological investments, product innovation, business processes, and disclosures.

With the increasing pressure from regulatory authorities, customers, employees, shareholders, and other market participants, insurance enterprises are striving to incorporate various aspects of sustainability into their business. Insurance firms are embracing sustainable change in a variety of ways, including through their investments, underwriting choices, and the structure of their insurance products, as well as using their own office buildings and making the vehicle fleet available to executives and staff. By integrating ESG considerations into their risk management, product design, internal operations, long-term strategies, and workforce management, many insurance firms have already started their journey toward becoming purpose-driven organizations and have begun to integrate sustainability with their core businesses.

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Exhibit 1: A look at various internal and external ways to incorporate sustainability

Incorporating sustainability in workforce management and internal processes has been the first step in creating sustainable change for most insurance enterprises. However, with the high awareness and responsibility in the play, insurers are now also increasingly moving toward adding sustainable insurance products in their catalog that address environmental and social challenges to become champions in the maturity continuum [Exhibit 2]. For instance, insurers offer green insurance policies at lower premium rates to incentivize environmentally friendly practices and offer coverage for renewable energy installations, energy-efficient buildings, and sustainable agriculture. Similarly, parametric insurance products provide rapid and efficient payouts in the event of natural disasters, helping communities recover faster and build resilience against climate change impacts. These innovative products not only protect clients against risks but also encourage sustainable change behaviors and contribute to a greener future.

Another impactful way in which insurers can increase their top line while promoting sustainability is by incorporating sustainability criteria into their investment policies, divesting from environmentally harmful industries, and investing in renewable energy projects. These actions not only align with the insurers’ values but also offer potential financial returns while mitigating climate-related risks.

Exhibit 2: Sustainability maturity continuum for insurance enterprises

Insurers need to prepare for sustainable change with the right technology and data architecture to achieve their sustainability goals, maintain transparency, and stay ahead of the regulatory disclosures requirements.

Insurers have been leveraging consulting partners to help them define their roadmap and strategies to achieve their sustainable agenda. But one of the biggest challenge  insurers face in this pursuit is the lack of robust data architecture to provide an understanding of the current ESG footprint, such as carbon emissions, energy consumption, energy mix, and employee well-being. As more insurer enterprises move toward becoming sustainability champions and provide transparency and disclosures to the regulatory bodies and other stakeholders, there will be increased opportunity for data and analytics providers to partner with the insurers to help them align their insurance portfolios with sustainability goals and manage ESG-related risks.

Additionally, collaboration with technology and IT service providers can help insurers build new products and solutions by leveraging cutting-edge technologies such as data analytics, AI, cloud computing, AR/VR, and blockchain that can boost the sustainability agenda along with unlocking fresh opportunities for generating revenue. Moreover, using technologies such as green/sustainable cloud to minimize operating expenses and carbon footprint while optimizing energy demand, predictive/prescriptive maintenance of equipment using IoT to limit energy and materials waste, and processing claims efficiently and sustainably by uploading photos and videos of damage through an AR/VR interface are some of the ways insurers can leverage technology to achieving their internal sustainability initiatives as well.

Exhibit 3: Utilizing cutting-edge technology to drive sustainable change

The insurance industry has recognized the urgent need to embrace sustainability and is taking significant steps to drive positive change. By integrating sustainability into investments, leveraging technological innovation, offering sustainable products, adopting environmentally responsible business processes, and promoting transparency through disclosures, insurers are playing a crucial role in addressing global sustainability challenges. As the industry continues to evolve, the integration of sustainability practices will become even more critical, enabling insurers to manage risks effectively, foster resilience, and contribute to a more sustainable future for all.

For more details on how the insurance industry is moving toward driving sustainable change and insuring a sustainable tomorrow, please refer to our report Insuring a Sustainable Tomorrow: How the Insurance Industry is Driving Positive Change.

Everest Group Talent Demand Growth Index | India IT Services | Blog

Welcome to our monthly India IT services talent demand index. We are excited to bring you this comprehensive analysis, powered by Talent Genius™, our AI-powered insights platform purpose-built to guide IT and Business Process Services location and workforce decisions. To gain a deeper understanding of the capabilities of Talent Genius and learn how to book a demo, watch this quick 2-minute video, Introducing Talent Genius™.

Monthly India IT services talent demand tracker

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Here is our in-depth analyses of the India IT services industry demand:

June 2023 update

The demand for IT services in India showed further recovery and grew by 15% compared to May 2023. For the first time in the last six months, demand also showed growth on a year-on-year basis (21% growth compared to June 2023). At a segment level, both IT ADM and IT infrastructure segments witnessed 14-month high demand levels in June 2023, with IT infra talent demand growing 40% on a year-on-year basis.

The growth trend, which started in May, is solidifying and was consistent across all cities, though the extent of recovery varied. Chennai saw a modest recovery, whereas Mumbai saw a significant spike in demand. We believe the demand surge in Mumbai may not be entirely due to net new demand but could be due to talent management/attrition challenges arising from the hybrid/in-office model and the need to back-fill resources.

The demand from service providers continues to grow, and we believe there is more focus on hiring laterals this year compared to the previous year, which saw a significant uptick in campus hiring. This increase could also be due to multiple large deals that are at play in the market and providers hiring in anticipation of winning large business in the medium term.

May 2023 update 

The demand for IT services in India showed a recovery in the month of May, growing by 34% compared to the previous month and staying flat compared to 2022. This spike compared to March and April could be attributed to buyers placing demand ahead of the summer in key onshore geographies, which tend to be slower from a business perspective. The increase in demand was consistent across both tier-1 and tier-2/3 cities; however, the recovery was much steeper for tier-1 cities (growing 14% YoY) compared to tier-2/3 cities (shrinking by 20% on a YoY basis). Among the tier-1 cities, all showed an uptick in demand; however, Pune set a demand record of a 17-month high. The service provider segment, while it showed recovery compared to the previous month, on a YoY basis, registered a 7% decline in demand. On similar lines, BFSI and technology & communications verticals continue to show a declining demand trend on a YoY basis. 

April 2023 update

The demand for IT services in India further shrunk by 17% in April, reaching a 16-month low, and declined by 29% on a year-on-year basis. The impact of the anticipated global economic slowdown is clearly visible in the latest demand trends. 

The declining trend is consistent across both tier-1 and tier-2/3 cities. Among tier-1 cities, Chennai, followed by Delhi-NCR, witnessed the highest decline. Tier-2 cities saw an even higher decline on a year-on-year basis at 32%. At this point, the demand for IT services talent in India is almost 50% of the demand in January 2022. However, this trend needs to be observed over a slightly longer period. If this trend continues for a few more months, the already reduced attrition numbers are likely to come down further. 

Being the first month of the new fiscal year for many leading India-heritage service providers, this indicates a not so good start to the year 2023-24, and declining talent demand is deeply correlated to reduced business growth.

March 2023 update

After five consecutive months of demand growth/stability, the demand for IT services in India dropped significantly (21%) in March and by 36% on a year-on-year basis. The declining trend in March was consistent across all tier-1 cities, though Mumbai witnessed the lowest decline among all tier-1 cities. 

The demand in tier-2/3 cities also reduced by 26% on a year-on-year basis. This overall declining trend is expected as Q1 2022 witnessed a significantly higher demand due to attrition and talent wars faced by the industry, and with the current economic environment, most companies are not in an expansion mode.  

Stay tuned for regular monthly updates as we monitor the landscape of the India IT services industry demand market. We’ll continue to provide the latest insights and trends, so you stay well-informed on locations and workforce developments.

Striking the Right Chords: Composable Platforms to Orchestrate Supply Chain Platformization in the Retail and CPG Industry | Blog

Confronted with significant challenges in managing their supply chain due to fragmented software solutions and data silos, retail and consumer packaged goods (CPG) enterprises need unified platforms that support the demand for customization while maintaining agility. Learn about the benefits and components of composable platforms as well as the collaborative role ecosystem stakeholders can play to bring together the supply chain landscape in this blog.

Reach out for more information on this topic.

The retail and CPG industry supply chain is a complex web of suppliers, manufacturers, distributors, and retailers. Daily fluctuations in consumer demand patterns and the rapid growth of e-commerce and newer business models have further increased the intricacy.

Yet, half of the industry has not moved past using spreadsheets and custom-built discrete solutions to manage their operations. Based on an Everest Group study, almost 48% of retailers and consumer goods companies still track their supply chains using spreadsheets. While these solutions are powerful tools, they often lead to siloed data and disjointed processes, resulting in delays and poor supply chain visibility. Let’s explore these limitations and a better solution.

Fragmented supply chain software solutions

The supply chain is a core function not only in retail and CPG but a building block of the economic infrastructure for many other industries. However, no multi-billion-dollar end-to-end supply chain platform company exists like Salesforce in customer relationship management (CRM), Workday in Human Resources (HR), ServiceNow in IT service management (ITSM), and Oracle and SAP in Enterprise Resource Planning (ERP).

The application landscape is fragmented across different departments, such as transportation, warehousing, procurement, planning, and inventory management, with each having its own goals and limited alignment, leading to distinct silos.

Software providers also target these separate buying centers, resulting in various supply chain software categories having great diversity. Due to this heterogeneity and the lack of unified ownership, no comprehensive solution that covers the entire end-to-end supply chain is available.

Data silos across the value chain

The fragmented nature of the application landscape also creates data silos that pose significant challenges within the retail supply chain, hindering efficiency and inhibiting strategic decision-making.

According to our recent study, almost 83% of retailers struggle with data silos across various functions such as inventory management, procurement, logistics, and point of sale (POS) systems. This disconnected data landscape not only impedes supply chain visibility but also results in missed opportunities for cost savings and improved customer experience.

Need for customization

Customizing supply chain is a top demand for retail and CPG enterprises. Many companies have spent decades building software that uniquely fits their purposes.

Enterprises transforming their supply chain are either migrating or replicating these solutions to the cloud. However, they are finding out-of-the-box solutions such as Blue Yonder, SAP, Manhattan, and others do not fit the purpose in most cases. Roughly 30-50% of enterprises, even digitally mature ones, still need customization.

Moreover, the RCPG industry also requires workflow applications and other low-code applications to augment the day-to-day decision-making of different system stakeholders. For these reasons, a unified platform that supports customization while maintaining agility is crucial.

Target state of supply chain platformization

By integrating suppliers, manufacturers, distributors, and retailers on a unified platform, organizations can achieve end-to-end visibility, optimize inventory levels, reduce stockouts, and improve customer satisfaction. Real-time data analytics empower stakeholders to anticipate demand, optimize production schedules, and minimize waste.

This unified supply chain management platform should have the following five components:

  1. Orchestration – The platform should have end-to-end capabilities that not only orchestrate core business applications such as inventory management and supply chain planning but also value-add applications such as sustainability monitoring and supplier risk management, among others
  2. Composability – The platform architecture should be a composite structure of granular components interconnected by business logic and extensible as required. Components in composable platforms promote interoperability, allowing different components developed using various technologies or programming languages to work together seamlessly. This interoperability is typically achieved through standardized protocols, data formats, or communication mechanisms
  3. Scalability – The platform should be built on the cloud to provide scalability as the supply chain process scales up in volume and complexity. The platform should also have integration capabilities that support seamless data exchange and communication between on-premise systems and cloud services. This includes connectors, application programming interfaces (APIs), or middleware solutions that enable smooth data flow and interoperability between the different environments
  4. Unified data fabric – The traditional linear data value chain should be replaced by a collapsed one with structured and unstructured internal and external data all in one location. The platform should act as a single repository of all the supply chain data that is standardized and can be accessed in real-time
  5. Extendibility – The platform should provide the ability to extend existing applications as the business scales. It should have developer portals to build supply chain services/products and a marketplace for technology partners to integrate their solutions on the platform


Consolidating the current fragmented supply chain platform landscape is no easy feat and requires collaboration by hyperscalers, data cloud vendors, and enterprise application providers. Some of the players to roll out collaborative initiatives include:

  • Blue Yonder, in partnership with Snowflake and Azure, is consolidating the majority of its solutions offerings on the Luminate platform
  • Microsoft launched its supply chain platform late last year, which aims to provide platformization building blocks across Azure, Dynamics 365, Microsoft Teams, and Power Platform

Technical debt prevents many large enterprises from undergoing supply chain platformization. Our analysis of supply chain investments by retail leaders indicates the end-to-end platformization journey needs to be iterative and not a big-bang transition. It also requires a balanced approach of adopting out-of-the-box applications and building composable applications from the ground up to fit the organizational context.

Everest Group will continue to follow the evolution in this space. To discuss composable platforms and other supply chain management trends in the retail and CPG industry, please reach out to [email protected] and [email protected].

Learn the key technology investment priorities for retail and CPG in our LinkedIn Live session, The Future of Retail and CPG: Balancing Economics, Efficiency & Experience.

Decisions for the Future of the Office | Blog

At Everest Group, we work with a lot of companies currently wrestling with the challenge of moving people back to the office. They went from everyone working at the office or company facility to everyone working from home during the COVID-19 pandemic.

There has been a lot written about the rising sentiment in management circles for the need to return to the office, with numerous examples of CEOs proclaiming that said move is essential. However, we can also observe from vacancy rates that this movement has stalled and is being actively resisted by a wide swath of employees. Short of a major realignment in the relative power of employees vs their management, it appears that firms will have to come to an accommodation forging a partnership with their employees which accommodates the needs of both sides into a better working situation. What is clear is that firms that attempt a one-size-fits-all receive the greatest pushback, and those that craft solutions that fit departments and functions achieve the best results.

Read more in my blog on Forbes

Unlocking Success: The Vital Role of Digital Transformation Consulting in Today’s Challenging Climate | Blog

As enterprises face mounting challenges in adopting complex digital solutions, digital transformation consulting continues to grow. But economic pressures, heightened digital intricacies, and new opportunities in sustainability will impact the industry’s future. To thrive in this rapidly evolving environment, consulting firms must offer tailored solutions that deliver measurable outcomes. For more insights, read this blog.     

Reach out to us directly to learn more.

Digital transformation consulting has gained market prominence in recent years due to the demand for experts who can help organizations effectively embrace technology-driven processes and strategies. With enterprises’ constant demand for digital relevance continuing, the sector is expected to grow 8.5 to 9.5% through 2025.

Consultants have a critical role in helping guide enterprises through the why, what, and how of digital business transformation. The success of digital transformation initiatives hinges largely on identifying the right objective, determining the best strategies, and properly planning digital initiatives, which is where consultants can provide invaluable guidance and expertise.

Service providers also have opportunities to display market-leading thought leadership, influence technology decisions by becoming strategic partners, and build long-term senior stakeholder relationships through consulting. These factors make digital transformation consulting one of the most important segments of the IT industry. Analyzing this industry’s movements helps decode the overall direction of digital change.

Macro-economic conditions are pushing enterprise priorities toward operational benefits

With the increasing economic pressures, cost optimization and productivity improvement have become top-of-mind priorities for enterprises in 2023. Companies are looking to optimize operations, streamline processes, and reduce expenses. In response, consulting firms should rebalance their priorities on operational segments such as supply chain management, production, finance, Human Resources, or sales and marketing.

This shift towards operational benefits will likely impact consulting service delivery. Clients increasingly are seeking outcome-based pricing models that tie consulting fees to specific cost savings or productivity gains. To meet this demand, consultants must demonstrate a deep understanding of their client’s business processes and operations and develop customized solutions that deliver measurable results. Many large consulting houses have also leveraged lower-cost locations to address their delivery cost uptick.

Digital pragmatism is leading enterprises to eye scope and vendor consolidation

Many enterprises are struggling to see the expected returns on their digital investments and are looking to optimize their value. This has led to a surge in demand for consulting services that can help businesses rationalize their digital scope and streamline their vendor portfolios. In 2023, the number of enterprises seeking to critically rebalance or rationalize their service provider portfolio increased by 35%.

To meet this wave of digital pragmatism, professional services firms need to provide end-to-end services that can guide clients throughout the process of IT portfolio rationalization. This includes identifying areas for consolidation, developing an implementation roadmap, and providing ongoing support to ensure successful execution. By taking a more strategic approach to IT investments and vendor selection, enterprises can optimize their value and drive better business outcomes.

This also highlights why digital consulting providers have been attempting to expand their footprint across overlapping opportunities among peer groups. For quite some time, the Big Three consulting firms have targeted downstream revenue with products and solutions for enterprise decision-making. Meanwhile, traditional IT services vendors are leaning on the importance of digital to engage top-brass executives and expand into upstream revenue more strategically. This all comes alongside the Big Four accounting firm’s efforts to exert dominance across end-to-end services capabilities.

DT Consulting Blog Infographic sf

This razor focus on value also forces consulting service providers to repair delivery inefficiencies. Everest Group’s Digital Transformation Consulting Services PEAK Matrix® Assessment found that costly engagements with large management consulting houses are not perceived as delivering sufficient value by most stakeholders, and organizations are receptive to working with IT service providers that have a stronger technical focus.

However, IT service providers who excel in technology expertise may fall short in delivering domain or industry expertise. The study showed clients were 10 percent less satisfied with providers’ domain/industry expertise than their technical expertise.

Winning in the “Value Market” will require consulting service providers to deliver well-rounded engagements supported by forward-thinking talent at effective price points that bring technical and domain prowess.

Sustainability will be the next game-changer in consulting

As businesses become more conscious of their environmental impact, many seek consulting services to help them develop and implement sustainable practices. Everest Group research found four out of every 10 Environmental, Social, and Governance (ESG) engagements are focused purely on consulting elements. As this trend is expected to accelerate in the coming years, sustainability will likely become a key driver for growth in the consulting industry.

Consultants are uniquely positioned to help clients navigate the complex sustainability ecosystem, working with diverse partner segments such as rating agencies, global standards organizations, data and reporting vendors, as well as independent software vendors (ISVs) and original equipment manufacturers (OEMs.) To capitalize on this trend, consulting firms need to invest in creating industry and function-focused expertise on sustainability. This includes building teams with deep domain knowledge in areas such as carbon accounting, circular economy, and ESG reporting.

Looking ahead, the consulting industry is expected to continue to undergo significant change, driven by macroeconomic conditions, digital predicaments, and sustainability. Consulting firms today must have a deep understanding of their client’s business processes, operations, and priorities. Providing customized solutions that produce measurable results will be crucial to thrive in this rapidly evolving environment.

To discuss digital transformation consulting and digital strategies, contact [email protected], [email protected], and [email protected].  Stay tuned for our perspectives on generative Artificial Intelligence’s impact on the digital transformation consulting market.

Don’t miss our webinar, Welcoming the AI Summer: How Generative AI is Transforming Experiences, to learn how enterprises can leverage Generative AI to unlock business value and about current use cases.

Analyst Relations Quarterly Newsletter | Q2 2023

Dear Analyst Relations colleagues –

We’ve all been very intrigued and a little nervous about an emerging world shaped by ChatGPT and other Generative AI (GAI) technologies. These buzz topics have clearly made their entrance into our worlds – both professionally and personally. I’m not sure how this technology will shape the fundamentals of my life and work, but I do know that I’m interested in figuring out how to make it work for me in achieving what I want to accomplish. So these next few lines reflect my thinking on how AR professionals can potentially get some value from GAI for the things they have to get done. Some strategic in nature, some operational. Here goes:

  1. Automated data collection & analysis: AI can sift through an ocean of data – from analyst reports to social media chatter to RFI requirements
  2. Sentiment analysis: AI can gauge the tone of analysts’ writings about your companies, helping save time and attain clarity more quickly
  3. AI-powered relationship management: AI can help us track and monitor relationships with analysts, identifying patterns that can help you strengthen these vital connections
  4. Chatbots for quick response: With AI chatbots, you can ensure that some categories of inquiries are answered promptly, around the clock
  5. Customized content creation: AI can assist in crafting tailored content for analysts, by firm or topic area, boosting engagement
  6. Efficient briefings management: AI can streamline the management of analyst briefings, especially post-meeting follow-ups
  7. Effective internal communication: With AI, you can distribute crucial analyst insights swiftly and efficiently within your organizations
  8. And the most exciting – complete analyst RFI responses: By integrating various data sources and applications, you can conceivably use ChatGPT can to automate responses to analyst research RFI requests. Now wouldn’t that be nice!


While the core value of AR comes from the nuanced conversations and relationships we nurture on a 1-on-1 basis, the power of AI for AR may lie in its ability to free you from routine tasks so you can focus on strategic planning, relationship building, and how best to apply insights from research to help with creative problem-solving for your organization.

How do you see yourself harnessing this tech to make your life a little easier and more productive?

Best Regards,

Katrina Menzigian
Vice President, Analyst Relations Engagement

From the CEO’s Office

In this video, Everest Group’s Katrina Menzigian, Vice President, Analyst Relations Engagement, speaks with Peter Bendor-Samuel, CEO, Everest Group, about GAI and what it could mean for businesses and why it’s the hottest topic in the industry. The speakers dive into the potential opportunities, the risks and how to manage those risks, and how GAI will be disruptive, but in a good way.


Everest Group’s Buyer’s Corner

Read how Everest Group supported this F100 company in transforming its strategic approach to existing and future IT Services (ITS) Outsourcing engagements by identifying opportunities for productivity and operational improvements.


Talent Spotlight

Mukesh Ranjan is a Vice President in the Information Technology Services team at Everest Group, leading research in the areas of enterprise digital transformation, cloud and traditional infrastructure, next-generation network infrastructure, digital workplace, and cybersecurity. In a recent conversation, Mukesh shared, “I aim to help clients solidify their critical decisions in the fast-changing cloud and infrastructure space. We work hard to share insights that are data-backed and well-researched.”

Mukesh is this edition’s Talent Spotlight and you can read more about him in his bio.


Analyst Relations Best Practices

Did you know you can view Everest Group’s RFI Agenda at any time? This listing of all forthcoming Everest Group RFIs can be found on our public Reports Portal. It’s a great one to bookmark to help your team better plan its workflow. The RFI Agenda is right on the landing page. You can see all the critical info, such as study title, status, RFI launch date, publication date, and links to previous reports. Check it out!


Help us improve your AR experience with Everest Group!

Please take our poll to help us learn, “What’s the overall level of effort you associate with working with Everest Group?” In exchange for your participation in our poll, you will have the opportunity to pick one of three complimentary research documents.


PEAK Matrix® | Recent Releases

Recruitment Process Outsourcing (RPO) Services PEAK Matrix® Assessment 2023

Contact Center-as-a-Service (CCaaS) PEAK Matrix® Assessment 2023

Trust and Safety Services PEAK Matrix® Assessment 2023

Life and Annuities (L&A) Insurance BPS and Third-Party Administrator (TPA) PEAK Matrix® Assessment 2023

Enterprise Blockchain Services PEAK Matrix® Assessment 2023

Workplace Employee Experience Management (WEEM) Platforms PEAK Matrix® Assessment 2023

Marketing Services PEAK Matrix® Assessment 2023

Thought Leadership

Categories of Use Cases in Sustainability Enablement | Market Insights™

Impact of ChatGPT and Similar Generative AI Solutions on the Talent Market | Blog

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Generative AI in Consulting: A New Era of Strategic Decision-Making and Digital Transformation | Blog

Generative Artificial Intelligence (GAI) has the potential to revolutionize strategic decision-making and consulting. With its power to simulate business scenarios and generate comprehensive data, GAI can be a game-changer for functions ranging from client onboarding to performance tracking. This blog explores the profound implications of GAI in digital transformation consulting, highlighting opportunities and addressing ethical and regulatory considerations.

To learn about use cases and the potential of GAI technology watch our webinar, Welcoming the AI Summer: How Generative AI is Transforming Experiences.

Consulting firms are embracing innovative approaches like GAI to enhance their value propositions. By combining human intelligence with AI capabilities, GAI is a ground-breaking technology offering an exciting future.

While challenges and investments are inevitable, early adopters stand to gain immense rewards, accelerating the industry’s growth and gaining a competitive advantage in the digital era. Continue reading to learn more.

Unleashing the power of GAI for strategic decision-making

By leveraging GAI’s capabilities, consultants can navigate the intricate labyrinth of available data, making sense of multifaceted patterns and trends that would otherwise remain elusive. With its proficiency in generating data and simulating varied business scenarios, GAI can offer strategic insights that can bolster enterprises’ decision-making processes.

These potential benefits are presented in a 3×3 framework that maps the impact and adoption rate of GAI in various consulting processes, as illustrated below:

Mapping the impact and adoption timeline of generative AI in consulting

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Navigating ethical and regulatory considerations

As we venture into the GAI era, maintaining ethical and regulatory balance is critical.

The following four considerations must be taken into account:

  • Data privacy – As GAI models rely heavily on data, sensitive data could be involved in a consulting scenario. Consulting firms must ensure robust data governance policies and procedures are in place, including measures for data anonymization and secure data handling
  • Algorithmic bias – GAI models, like all machine learning models, are only as good as the data they are trained on. If the training data contains biases, the AI models can inadvertently perpetuate these biases, leading to unfair or even harmful outcomes. To mitigate this, consulting firms must regularly audit their AI models, ensuring any biases are detected and corrected promptly
  • Transparency or explainability – Clients may mistrust AI’s opaque decision-making processes, especially when AI’s recommendations significantly influence strategic decisions. To overcome this challenge, consulting firms should consider adopting explainable AI technologies that can shed light on the “black box” of AI, enhancing transparency, and building trust
  • Regulatory compliance – Adhering to varying regulatory standards across regions and sectors is imperative. Consulting firms need a comprehensive understanding of relevant regulations in their jurisdictions and ensure that they adhere to these rules

The future of consulting

Integrating GAI into consulting can reshape the industry’s skill requirements, service offerings, and delivery models. The table below provides a glimpse of these potential changes:

Aspect Current State Potential Future State with Generative AI Key Changes Business Impact
Skills Heavily relies on human expertise and analysis Greater need for data science, AI expertise, and understanding of AI in a business context Development of AI-related skills, especially understanding and managing AI tools and algorithms Enhanced data-driven decision-making, improved efficiency, more sophisticated analysis
Service offerings Traditional consulting services Expanded offerings with AI-powered services such as predictive analysis, scenario generation, and more Addition of AI-enabled services to the portfolio, transforming the way consulting services are designed and delivered Diversified service offerings, potential for new revenue streams, increased competitive edge
Delivery models Primarily human-led engagements Hybrid model with AI augmenting human-led engagements, enabling more efficient and impactful delivery Transition to a blended delivery model with AI augmenting human expertise, redefining the consultant’s role Increased client engagement, enhanced value delivery, improved scalability
Client engagement Personalized, but time-intensive interactions AI-enabled personalization in real-time, optimizing engagement through AI tools like chatbots and virtual assistants Implementation of AI in client interactions, necessitating changes in engagement strategies Enhanced client experience, real-time interactions, increased client satisfaction
Data analysis Manual data analysis, potentially time-consuming and error-prone AI-powered data analysis, providing accurate insights quickly and efficiently Incorporation of AI tools in data analysis, enhancing speed and accuracy Improved insights, faster decision-making, increased reliability
Business development Traditional methods of identifying and pursuing opportunities AI-enabled opportunity identification and business development strategies Adoption of AI tools for market research, lead generation, and opportunity analysis More effective business development, increased revenue, higher growth potential
Continuous learning and improvement Based on feedback and personal experience AI-facilitated learning from every engagement, leading to continuous improvement of consulting methodologies Integration of AI tools for feedback analysis and learning, enhancing the consulting approach Continual improvement, staying relevant, higher client satisfaction

Positive outlook for generative AI in consulting

Adopting GAI in consulting can be a game-changer, offering a competitive edge and driving industry growth by delivering superior value. However, remember these potential rewards are not without risks. Firms must consider the significant investments in technology and skills development, as well as navigate the intricate ethical and regulatory landscape.

As digital transformation consulting firms set sail on their journey to integrate GAI into their operations, proactively understanding and adopting these advanced technologies can set them apart. By navigating the challenges and capitalizing on the immense potential of Generative AI in consulting, firms can seize the opportunity to lead in this new era of digital transformation consulting.

To discuss Generative AI in consulting, contact [email protected], and mailto:[email protected].

Don’t miss our virtual event, The Possibilities for Generative AI in Sourcing, to learn about opportunities to integrate generative AI into sourcing processes.

Generative AI in Clinical Development: Unlocking Possibilities and Addressing Challenges | Blog

The prospects for Generative AI in clinical development look encouraging. GAI can help speed drug development, improve protocol design, personalize treatment, and bring other benefits. However, the industry must be aware of the risks and responsibly operate GAI. Read on to learn more.

Contact us directly to discuss this topic further.

Given the lengthy, labor-intensive, and expensive process of bringing a new drug to market and conducting a clinical trial, clinical development stakeholders are constantly searching for technological solutions to automate workflows, streamline operations, reduce site and patient burden, and accelerate trial timelines.

Leveraging cutting-edge technology, Generative Artificial Intelligence (GAI) may unlock new horizons and revolutionize the entire clinical development value chain. Let’s explore this further.

GAI works by training underlying large language models (LLMs) on huge datasets containing billions of parameters. For example, ChatGPT is built on GPT-3, a model trained with over 175 billion parameters, far exceeding prior LLMs.

GAI outperforms conventional AI by not only analyzing and interpreting existing data but also generating text, images, audio, video, and other content. The latest innovation, GPT-4, takes this a step further by introducing multi-modality, allowing it to process non-text inputs like images and generate high-quality outputs.

The potential for generative AI in clinical development 

In the clinical development field, the opportunities with GAI are simply too big to ignore. It has the power to accelerate drug development, enhance patient engagement, improve protocol design, personalize treatment approaches, generate synthetic data, and much more.

Let’s take a closer look at the potential applications in clinical development to better understand the role that GAI can play in this domain:

  • Patient recruitment and screening: By scanning a plethora of health and medical records, GAI can reduce the recruitment funnel and better identify suitable patients for clinical trials. The outcome of these interactions can be fed to a validated digital biomarker for the desired indication. This, in turn, can accelerate patient recruitment and improve diversity ratios
  • Synthetic data generation: Synthetic datasets that closely resemble real-world patient data help researchers with limited data or no control group in randomized controlled trials (RCTs). GAI can help conduct simulations, test hypotheses, and accelerate the time to market. With the regulatory push in favor of synthetic control arms, GAI can be instrumental in generating synthetic data
  • Protocol authoring: GAI can optimize the process of authoring protocols for clinical trials. It has the ability to scan through vast amounts of scientific literature, past trial histories, and databases and generate insights on the appropriate endpoints, dosage, patient population, treatment arms, and analysis procedures
  • Patient engagement: AI-driven by LLMs can analyze patients’ medical history data and preferences and create personalized content. GAI-powered digital avatars can significantly improve patient engagement by providing personalized communication and educational information that ensures patients are included in the process and remain engaged and informed
  • Real-time decision-making: During a trial, GAI can continuously monitor patient conditions (through data coming from wearables and sensors) and provide real-time support to investigators and researchers. This may entail preventive interventions, dosage modifications, improving medication adherence, and early detection of adverse events
  • Study Data Tabulation Model (SDTM) transformations: SDTM involves mapping clinical data to a standard structure for regulatory submissions. GAI can analyze data from multiple sources and generate mappings that meet SDTM standards. This use of GAI would provide validation and quality controls, and automate repetitive tasks, expediting the whole process

Figure 1: Prominent use cases and the potential impact of Generative AI in clinical development in the near future

While GAI is generating buzz across industries, like any new technology, its benefits come with challenges. Pharmaceutical enterprises must be aware of the following risks and biases so they can be prepared to address them:

  • Data quality and bias: GAI relies on the quality of training data for generating meaningful outcomes. The data used to train the models can have biases that can lead to disparities in patient recruitment and treatment recommendations. New AI models may not be well-suited to handle diverse languages, dialects, and cultures effectively
  • Data security and privacy: A crucial consideration for using Generative AI in clinical development is patient data security. Ensuring compliance with the ambiguous regulations for digital technologies and AI in clinical development is complicated. AI models should comply with existing regulations like the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR) and be prepared for potential upcoming ones
  • Ethical considerations: The use of GAI raises ethical questions, especially in using patient information to train the models. Patient data must be handled with strict confidentiality, and consent must be given at all times before using it to train any model
  • Accountability: GAI cannot be held accountable for inaccurate treatment recommendations or a mistake in the protocol design. Completely relying on automated systems raises liability concerns and makes determining accountability challenging
  • Sustainability: GAI models are trained on billions of parameters that require extensive computational resources often managed at large-scale data centers. As the use of GAI models and queries continues to grow, the carbon footprint also rises

Over-reliance on AI models without human intervention for decision-making can lead to unwanted consequences. Domain experts, clinicians, and researchers must be present to validate the outputs and use GAI responsibly while having minimal environmental impact.

Technology advances have always brought disruptions, and GAI is no exception. GAI can revolutionize data management processes and become an invaluable tool in clinical development. By better understanding its risks and biases, pharmaceutical enterprises can use GAI responsibility and reap its full benefits – making GAI’s future in clinical development look promising.

To discuss the future of Generative AI in clinical development, contact Anik Dutta, Nisarg Shah, and Madhur Kakade.

Learn more about the use cases and potential of GAI technology in our webinar, Welcoming the AI Summer: How Generative AI is Transforming Experiences.

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