Tag: Generative AI

Indian IT Firms Face a Tough FY24 with All Round Pressure on Revenue & Margin | In the News

The Indian IT services industry has faced a tough financial year in FY24 with hope for a better fiscal year starting April 1. Tepid revenue growth rate, pressure on margin, low hiring, fall in headcount, disruption coming from generative AI, leadership changes at the top level, and sound deal pipeline characterized the ongoing financial year.

“Large deal pipelines are full, however, predicting the timing of their closing is becoming increasingly difficult,” Peter Bendor Samuel, CEO of Everest Group, told Bizz Buzz.

Read more in Bizz Buzz.

Cutting Through the Noise: Why Now is the Time to Invest in Next-gen Technologies | In the News

In the realm of boardroom conversations, buzzwords like generative AI (gen AI), data lakes, predictive analytics, and automation frequently surface. However, there’s a noticeable disparity between the prevalent talk on these topics and the actual scenarios business leaders face.

For example, the “chatter” might suggest that companies are already fully harnessing the potential of data lakes; however, according to the Global CFO Survey by Everest Group, investment in this technology is still in its infancy.

Read more in Nasdaq.

 

 

Gen AI and Retail: How the Industry is Harnessing Disruptive Transformation | In the News

Generative AI (gen AI) is spurring organizations across different sectors to fundamentally reimagine their approach to digital transformation. Retailers are exploring gen AI use cases across a wide range of functions, from new product discovery and personalization to streamlined fulfillment and enhanced services.

Everest Group’s Generative AI in CXM survey report revealed that 55% of enterprises view enabling personalization as a key driver of gen AI adoption, while 16% are investing over US$10 million toward gen AI initiatives in the next 12 to 18 months.

Read more in Total Retail.

How Will Next-gen Technologies Be Financed in CXM Delivery? | LinkedIn Live

LinkedIn Live

How Will Next-gen Technologies Be Financed in CXM Delivery?

View the event on LinkedIn, which was delivered live on Thursday, March 14, 2024.

In 2024, technology will likely be a significant differentiator in customer experience (CX) services, offering overall improved customer experiences and cost rationalization of CX services offered. Forward-thinking enterprises are questioning how new technologies such as generative AI (gen AI) will be commercialized and how it will impact CX services. 🌐

Watch this LinkedIn Live discussion with Everest Group’s David Rickard, Partner, Kunal Verma, Vice President, and Rahul Barwe, Vice President, to learn about emerging technologies’ impact on CX services and how they can be leveraged for commercial gain. 📈🔍

During this engaging LinkedIn Live, we discussed:

✅ The recent technologies being included in CX outsourced deals
✅ The impact of these technologies on pricing models for CX services
✅ How to commercialize Gen AI solutions

Meet the Presenters

Barwe Rahul
Vice President
Everest Group
Rickard David
Partner
Everest Group
Verma Kunal
Vice President​
Everest Group
Aniruddha edited

Five Tactics for Technology Service Providers to Guard Profit Margins Against Generative AI Impact | Blog

Technology service providers are committing to gen AI-related benefits to clients without a clear path to realization, which will negatively impact their deal margins. Uncover five strategies providers can use to optimize the productivity benefits of gen AI without denting profit margins in this blog.

The notion that generative AI (gen AI) can negatively impact technology service providers’ profit margins is counterintuitive. Service providers have assumed leveraging gen AI would improve margins by amplifying productivity and efficiency. Unfortunately, this has not been the case.

Most technology service providers commit to delivering gen AI-driven productive gains to clients. However, they will struggle to achieve these benefits in the short term due to the highly contextual and probabilistic nature of gen AI tools and their niche impact on specific tasks. This is hard to guarantee in solutioning.

Consequently, service providers must adopt other methods to realize these productivity benefits. This often involves a combination of people and intellectual property (IP) assets that cannot be charged to clients, hurting near to mid-term profitability.

Let’s look at the following five options that CEOs and CFOs of technology service providers have to address this issue:

  1. Monetize generative AI assets: Service providers have struggled to monetize their IP and assets because they are mostly used as service enablers and differentiators. Clients do not perceive additional value and are not incentivized to pay for these assets. However, gen AI assets could change this trend. Investing in gen AI assets can significantly vary from weeks to months of effort. Monetizing these assets should go beyond implementation and support fees and focus on IP value. If service providers can demonstrate genuine value, clients will be willing to pay the cost through better service pricing, an innovation fund, or direct monetization
  2. Educate sales teams and clients about the realistic impact of generative AI: Sales teams often fear their competitors are moving faster than them. In this rush, they commit gen AI benefits to clients without involving the practice, solution, or delivery teams. Leaders should coach the sales team and engage with strategic clients to have realistic gen AI discussions. Providers should create gen AI literacy services that peel away the hype of eye-catching Big Tech productivity announcements about gen AI offerings. Educational initiatives can help moderate client expectations and limit margin erosion
  3. Transform deal-related enabling functions: Generative AI has significant potential for summarizing and querying knowledge repositories. Service providers already use it to enhance the sales function through requests for proposal (RFP) bots, translating documents, and understanding service level agreement (SLA) requirements and the nuances of client needs. Accelerating such initiatives across sales, pre-sales, delivery management, deal finance, and business reviews can lower deal-related costs and alleviate margin pressure from productivity commitments
  4. Identify the right clients: Service providers need to identify the right set of clients for committing and delivering gen AI productivity benefits. This crucial aspect of the puzzle is frequently overlooked. The selection process should be driven by data, the client’s AI maturity, and the nature of the relationship and services used. Choosing the right clients can increase providers’ margins in their gen AI service delivery adoption journey. These clients will be more supportive of letting specific units experiment with gen AI productivity benefits, provide realistic feedback, and set internal expectations
  5. Transform effort and pricing models: Service providers are struggling to transform their effort and pricing model in the wake of gen AI committed benefits. Providers continue to rely on traditional approaches mainly because they are uncertain about linking gen AI committed client benefits to effort and pricing to manage deal margins. However, this problem must be solved to prevent it from significantly denting profitability. Apparent solutions, such as delinking price from effort, value-based pricing, and outcome-based commercials, have not worked. Since clients are more accommodating to collaborate with providers in this journey, providers should reignite these conversations, educate procurement and vendor management offices, and refresh their solutioning playbooks

While account and delivery leaders are held financially accountable for managing margins, linking this specifically to gen AI-related commitments can backfire. Instead, the focus should be shifted upstream during deal bids, solutioning, and client engagement.

To share your experience and discuss the impact of generative AI on profit margins for technology service providers, contact [email protected] and [email protected].

Watch this webinar, The Generative AI Odyssey: A Year in Review and What’s Ahead in 2024, to hear our analysts discuss the hype vs. reality of generative AI, production-level use cases, and the future of this transformative technology.

Are Expectations For Gen AI Lower Than Planned? | Blog

I am coming to the conclusion that the hoped-for gen AI spending wave for both tech and tech services could be longer in developing than both the investors and companies are planning on. In a recent blog, I talked about the realization that most (perhaps as high as or above 90%) of the Proof of Concept (POC) initiatives that launched during 2023 will not make it to production in 2024. Yet, the tech firms are plowing hundreds of millions of dollars into building AI tools and building the capabilities for running them. What has changed? And where are there still opportunities for this important technology?

Read more in my blog on Forbes

Jack Madrid Sees Gen AI as Game-changer for IT-BPM Industry, Focuses on Upskilling

The Philippines sees generative AI as a game-changer for its booming information technology and business process management (IT-BPM) industry but acknowledges the need to upskill its workforce to adapt. The IT & Business Process Association of the Philippines (IBPAP) prioritizes proactive upskilling and reskilling for its workforce.

The association also plans to revisit its 2028 roadmap targets with research partner Everest Group to account for the evolving landscape.

Read more in Bilyonaryo.

IBPAP to Refresh 2028 Roadmap amid Gen AI’s Adoption | In the News

The Information Technology & Business Process Association (IBPAP) is updating its 2028 industry roadmap to align its goals with the ongoing expansion of the artificial intelligence (AI) landscape.

IBPAP, in a statement, said it is collaborating with leading research firm Everest Group in refreshing the industry roadmap and introducing an ambitious version for 2028.

Read more in SunStar.

Leveraging Gen AI to Enhance CXM: From Innovation to Implementation | LinkedIn Live

LINKEDIN LIVE

Leveraging Gen AI to Enhance CXM: From Innovation to Implementation

View the event on LinkedIn, which was delivered live on Thursday, February 29, 2024.

🌐 While we recognize the huge potential of generative AI (gen AI) in enhancing Customer Experience Management (CXM), the questions on everyone’s mind are: How do we make it work in real-world scenarios, and where do we start?

Watch this interactive LinkedIn Live session to hear from Arte Merritt, Founder of Reconify, and Everest Group analysts, Shirley Hung and Sharang Sharma. We explored the roadmap for gen AI implementation, discuss what global businesses are considering in terms of deployment, address challenges, and examine whether companies should take on this journey independently or collaboratively.🚀

During this event, we dove into questions such as:

  • 💡 Where do you start with your gen AI journey for CXM?
  • 💡 What areas should you be looking at immediately for implementation?
  • 💡 How do you co-innovate to minimize risks?

Meet the Presenters

Hung Shirley
Everest Group

Leveraging Strategic Partnerships to Unlock the Potential of Gen AI in Customer Experience Management | Blog

By strategically partnering with third-party providers, enterprises can fully harness the potential of gen AI in customer experience management. Learn insights from our latest survey on enterprise readiness for gen AI adoption and how collaborating with providers can help overcome the major obstacles.

Reach out to us for more information or to further discuss this topic.

Generative Artificial Intelligence (gen AI) is emerging as a game-changer in customer experience management (CXM) by offering the potential to personalize customer interactions, enhance operational efficiency, and provide a competitive edge. As enterprises adopt gen AI, third-party providers have an increasingly vital role. Let’s explore this further.

Current demand for gen AI

Demand for gen AI solutions is skyrocketing among enterprises across industries. According to a recent Everest Group survey of top executives and CXM leaders of 200 enterprises worldwide, nearly 75% believe gen AI will significantly impact their CXM strategies within the next two years.

Enterprises highlighted personalized interactions, cost reduction, and operational efficiency as the top three drivers for gen AI adoption.

  • Personalized customer interactions: Gen AI can produce customized content, product recommendations, dynamic pricing, and marketing campaigns tailored to individual customer preferences, enhancing customer satisfaction and loyalty
  • Increased efficiencies and automated CXM processes: Gen AI can empower customer support agents with intelligent tools such as agent assist, next-best-action recommendations, language translation, and accent neutralization. These tools enhance productivity, reduce response times, and enable agents to focus on more complex and value-added tasks. Using gen AI to automate routine tasks and repetitive processes can further boost operational efficiency
  • Reduced cost: By automating repetitive tasks, streamlining processes, and enabling advanced data and analytics capabilities, gen AI adoption can increase operational efficiency and productivity, optimizing cost

Current enterprise capabilities

Despite growing gen AI demand, the technology is still nascent. Most enterprises and service providers are investigating gen AI operations use cases or piloting solutions to test feasibility. Given the technology’s evolving nature, enterprises currently face or will likely encounter challenges in adopting and implementing it effectively.

Our survey asked enterprises about their readiness to adopt gen AI to identify significant areas where enterprises need specialized support. Below are the results of the preparedness of enterprises across industries and key parameters:

Picture1 2

EXHIBIT 1, Enterprise readiness for gen AI by industry, Source: Everest Group (2023)

Challenges in gen AI implementation

Based on the readiness levels and significant challenges identified by enterprises in the survey, the following overarching issues for enterprises emerged:

  • 55% of enterprises reported a shortage of the right talent pool, including AI/ML engineers, data scientists, and software developers needed to integrate gen AI with existing tools and create agent interfaces
  • 56% of enterprises highlighted the scarcity of high-quality training data required for training and testing models
  • Between 45-50% of enterprises expressed concerns about computing power required for gen AI adoption and their ability to scale
  • Regulatory compliance concerning the fairness of the output, data security, and privacy, and misuse of the models also stood out as significant issues for enterprises

How can enterprises navigate these challenges?

The gaps in enterprise capabilities identified in our survey underscore the need for strategic partnerships to ensure successful implementation. While executing gen AI in-house offers greater control over the development and implementation process and allows enterprises to tailor solutions to specific needs, it requires significant internal expertise and resources that may be limited. Outsourcing gen AI implementation can provide access to specialized knowledge and resources, accelerating the implementation process and reducing the time to market for these solutions.

Our survey revealed that nearly 89% of the enterprises are looking to either outsource the implementation of gen AI in customer experience management to specialized AI companies or contact center providers or follow a hybrid approach involving in-house and outsourced development.

Picture2 1

EXHIBIT 2, Implementation plan for Gen AI solutions within CXM, Source: Everest Group (2023)

The top three areas where enterprises are seeking service providers’ support are:

  • Building gen AI solutions and enhancing technical capabilities: Enterprises need partners who can help train gen AI models on enterprise data, customize foundational models to build tailored solutions, and set up necessary computational systems to run these solutions
  • Integrating gen AI solutions with existing technologies: Enterprises need partners who can create necessary bridges to integrate gen AI with existing business intelligence tools, providing a more comprehensive view of customer interactions
  • Supporting and complimenting in-house teams: Enterprises need partners who can support in-house technical teams, aid in maintenance, troubleshoot activities, and supervise the functioning of gen AI solutions

Future outlook

Gen AI has the potential to revolutionize CXM, enabling enterprises to deliver personalized, efficient, and innovative customer experiences. However, successfully adopting and implementing gen AI requires overcoming expertise, data quality, and change management challenges. Strategic alliances with third-party providers can bridge these gaps, providing enterprises with the necessary industry-specific knowledge, resources, and guidance to unlock the full potential of gen AI.

Third-party providers have a crucial role in helping enterprises translate the perceived potential of gen AI into practical applications. These partners can help enterprises identify specific CXM use cases where gen AI can deliver tangible benefits, develop gen AI strategies, design and implement solutions, and provide ongoing support to ensure successful gen AI adoption.

Read Everest Group’s Generative AI in CXM: Assessing Enterprise Readiness for this Disruptive Transformation to better understand gen AI in Customer Experience Management and how providers can help enterprises adopt gen AI. If you have questions or want to discuss digital CX strategies and solutions, contact Anubhav Das at [email protected] or Mohit Kumar at [email protected].

Don’t miss our LinkedIn Live, How Will Next-gen Technologies Be Financed in CXM Delivery?

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