Welcoming the AI Summer: How Generative AI is Transforming Experiences | Webinar

June 6, 2023

On-demand Webinar

Welcoming the AI summer: How Generative AI is Transforming Experiences

Generative AI (GAI) technology has been around for nearly half a century. But recent developments in the maturity of AI models, faster computation power of systems, and availability of high-quality training data are redefining the technology in 2023.

While tech giants like Microsoft, Google, and Meta fight to dominate the GAI landscape, leading experience providers like Adobe, Salesforce, and Oracle are entering the market with significant investments.

In this on-demand webinar, Everest Group’s experts will highlight the use cases and potential of GAI technology in crafting experiences, its limitations and risks in terms of full-fledged commercial adoption, and the industry’s predicted response.

Our speakers discuss:

How can enterprises leverage GAI to unlock business value, and what are the current use cases?
What is the role of GAI in experience design?
What challenges in the experience ecosystem is GAI helping to address?
What is the future potential of GAI technology?
How can service providers and enterprises leverage GAI for enhanced efficiency and productivity?

Who should attend?

CMOs
CIOs
CTOs
Heads of customer experience
Heads of marketing

Nisha Krishan

Practice Director

Nitish Mittal

Partner

Sharang Sharma

Vice President

Generative AI – Redefining the Experience Design and Development Process | Blog

May 12, 2023

Generative Artificial Intelligence (GAI) holds the potential to revolutionize the experience design and development process by creating unique personalized marketing content. Read on to learn about the opportunities, challenges, and implications of GAI for enterprises and service providers.

You can also hear about the use cases, the limitations and risks, and the industry’s predicted response in our webinar, Welcoming the AI summer: How Generative AI is Transforming Experiences.

From rule-based systems merely capable of automating set functions to deep learning algorithms that can accurately comprehend natural human language nuances, Artificial Intelligence (AI) undoubtedly has come a long way.

Today, AI is at a juncture where its capabilities are no longer restricted to automating repetitive tasks. Generative AI – the latest version of this technology – has taken the industry by storm this year by entering the arena of human creativity.

While GAI is flooding the market with a plethora of unique use cases, it particularly has the potential to disrupt the experience design and development process by optimizing the content supply chain and streamlining the UX/UI design process. Let’s explore this further.

What is Generative AI?

Everest Group defines Generative AI as a variant of AI technology based on deep learning Generative Adversarial Networks (GANs) and Transformer models, having the ability to provide convincingly unique content in the form of text, imagery, video, audio, and synthetic data.

Although the technology has been around for the last five decades, it has recently gained momentum due to advancements in hardware computation power, maturity of AI models, and availability of high-quality contextualized training data sets.

Exhibit 1: Definition and evolution of GAI technologyPropelled by investments from giants such as Microsoft, Google, and Amazon, the market is witnessing a huge influx of start-ups focused on consistently identifying and operationalizing new Generative AI use cases.

Picture2 1 — Exhibit 2: Start-ups pioneering unique use cases in the GAI space

How can GAI help marketers?

As personalization becomes the centerpiece of every marketing strategy, the never-ending demand for real-time contextualized content puts a lot of pressure on creative teams. This is where GAI comes in. Be it content creation or user interface/user experience (UI/UX) design, the technology can create a scalable creative engine for personalized marketing.

The industry is acting fast to streamline the marketing creative process by adopting GAI. Experience leader Adobe has launched the Firefly family of proprietary GAI models that enable image, audio, video, and 3D model creation through mere text prompts. On the other hand, AI leader NVIDIA has introduced the GauGAN tool that can generate realistic images from sketch drawings by artists.

GAI – The brainstorming partner for idea generation across industries

While content remains key, enterprises also are investing in GAI models in vertical markets to power industry-specific use cases to brainstorm and generate creative ideas.

The following industries are rampantly adopting GAI technology:

Manufacturing: General Motors partnered with Autodesk to use GAI to design a new seatbelt bracket that was 40% lighter and 20% stronger than the original design
Healthcare: GAI also is being applied in drug design with companies such as Insilico Medicine using its Chemistry42 GAI platform to generate novel chemical compounds for new medicines
Architecture: Architecture firm Skidmore, Owings & Merrill (SOM) has created a GAI tool called SOM Computational Design for generating design options for buildings
Retail: Levi Strauss has partnered with Lalaland.ai to design hyper-realistic AI-generated model avatars for promoting diversity in terms of body type, age, and skin color

While AI has leaped in maturity from automating unproductive repetitive tasks to generating unique content via human-led prompts, it still lacks the finesse of a human touch. Therefore, the technology can act as a co-pilot for the creatives, but it’s not yet at a stage where it can provide customer-ready outputs through prompts. Instead of instilling fears about the technology replacing humans, enterprises must embrace the magnitude of the impact it can have on workforce productivity.

Mitigating GAI technology risks

The technology is a game changer, but it comes with substantial challenges related to output accountability, model bias, privacy compliance, talent shortage, system integration, and the cost associated with deploying large AI models.

While Italy has banned ChatGPT and other European nations have expressed concerns about the technology, pioneers such as Adobe and Salesforce are relentlessly trying to mitigate these risks by developing plagiarism checkers, establishing compensation structures for creative professionals, upskilling talent, and adopting fair representation learning models to counter model biases.

Implications for service providers

With announcements of Accenture’s GAI Center of Excellence, Deloitte Digital’s dedicated GAI practice, Infosys embedding GAI into software development tools, and TCS developing an in-house enterprise-grade solutioning platform using GAI, service providers need to take a cue and move fast to cement a strong understanding of Generative AI functioning and the ecosystem.

Providers also have to bring top leadership up to speed on the Generative AI landscape, flesh out a detailed narrative discovering enterprise priorities, embed GAI in solution and service delivery for efficiencies and productivity, and harness GAI technology’s true potential by integrating it with business applications.

For more insights on Generative AI, contact Vaani Sharma.

5 Steps to Unlock Maximum Value from Cloud | Webinar

May 9, 2023

On-Demand Webinar

5 Steps to Unlock Maximum Value from Cloud

WATCH THE WEBINAR ON-DEMAND

In the last couple of years, we have witnessed the frantic adoption of cloud by enterprises trying to keep up with innovation. During that time, the definition of cloud value was never standardized across different stakeholder groups, and today many enterprises believe they are not realizing the expected value from cloud. This phenomenon has been exacerbated by the current macroeconomic environment, which has added further pressure on enterprises to justify all investments and maximize value.

In this webinar, our experts will explore the unique opportunity for enterprises to align the definition of cloud value and execute their cloud value realization strategies while facing a constrained macroeconomic environment.

Our speakers will discuss:

How can you define value from cloud, and what are the key elements beyond cost?
What does value realization mean for different stakeholder groups?
How can enterprises align on one consistent definition of value?
What is the role of different market participants in helping enterprises realize value?
How relevant is cost optimization as a value lever in the current recessionary environment?
What are the pragmatic steps enterprises can take to maximize value realization?

Who should attend?

CIOs and CTOs
IT/BPO strategy heads
IT/BPO department heads
Heads of outsourcing
Procurement managers
Global sourcing managers
Vendor managers
Hyperscaler BU heads
Cloud and infrastructure heads
Solution leads
Cloud architects

Zachariah Chirayil

Practice Director

Mukesh Ranjan

Vice President

Abhishek Singh

Partner

HIMSS23 Highlights: Focus on Integration, Generative AI, and Increased Emphasis on Risk Mitigation | Blog

April 26, 2023

Artificial Intelligence (AI), technology integration, and consumerization are among the key trends driving the future of healthcare, a glimpse into the horizon at HIMSS23 showed. Read on to learn takeaways from Everest Group analysts who attended the recent global healthcare conference.

More than 35,000 healthcare leaders converged in Chicago last week to share ideas, highlight investments, showcase demos, and shape the future at HIMSS23. Technology integration, value realization, and risk avoidance dominated conversations at this year’s more strategic and connected conference focused on finding solutions to urgent issues.

Here are the three main themes we saw at HIMSS23:

Integration is the key to realizing value

Integration was a major topic, as many organizations struggle to stitch together various composable platforms. While microservices have enabled precision and faster outcomes for specific use cases, these independent solutions often do not communicate with each other, which can hinder value realization. Many stakeholders we interacted with highlighted the desire to explore ways to better integrate these platforms.

Generative AI is attracting attention

Generative AI, like ChatGPT, and its potential applications is creating a lot of excitement. Major technology companies such as Microsoft and Google are leading the way in developing innovative uses for AI in healthcare, including creating new health applications. While some early examples of AI in healthcare show promise, such as voice dictation that help doctors document patient information more efficiently, how AI will address broader healthcare challenges such as staffing shortages, physician burnout, and rising costs remain to be seen.

Consumerization of healthcare will continue to grow

Putting the patient at the center of healthcare was another recurring theme, with a focus on designing healthcare systems and technologies that are intuitive and seamless for users. The increased emphasis on user experience has been influenced by the consumer world, where these types of technologies are the norm. The coming years are likely to bring a greater focus on patient portals, wearable health solutions, and virtual care delivery technologies to improve patient/member experience.

How was HIMSS different this year?

The annual HIMSS conference returned to Chicago, with attendees noting a greater sense of urgency and action in meetings versus prior events in Orlando and Las Vegas. A large number of healthcare information and technology companies attending were focused on emerging enterprise priorities around value-based care (VBC) and interoperability.

Leaders engaged in meatier discussions focused on integration, value realization, and risk avoidance. The conversations showed that healthcare enterprises are looking for solutions to get more out of their technology, budgets, and resources in today’s challenging environment.

The large post-pandemic turnout demonstrated the appetite for in-person interaction. Event organizers focused on creating more focused opportunities for attendees to gather and have relaxed and candid conversations with friends, colleagues, and clients, which have been difficult to replicate virtually.

Overall, interacting with industry leaders influencing the next stage in healthcare technology at HIMSS23 was an illuminating experience for Everest Group analysts Abhishek Singh and Manu Aggarwal, who are available to share their insights.

Continue reading about the healthcare industry and the trends influencing decision-making by healthcare payers in our blog, The Recessionary Conundrum: What Lies Ahead for Healthcare Payers?

How to Achieve More from Less: Maximizing the Value of Applications | Webinar

April 6, 2023

On-DEmand webinar

How to Achieve More from Less: Maximizing the Value of Applications

WATCH THE WEBINAR ON-DEMAND

The macroeconomic environment is pushing enterprises to have more value-centric conversations, both internally and externally. With technology at the core of all business, IT spending is under intense scrutiny, which provokes questions such as: what is the ROI of our investments, are we getting enough value, and how can we make our IT organizations more productive?

Join this webinar as our speakers explore how service providers can help enterprises uncover more value from their IT investments. The webinar will provide insights on key regional demand themes and the impact on offshoring activity and APAC-based delivery.

What questions will the webinar answer for the participants?

What are the levers that will improve productivity?
What are the key application spend categories and the top imperatives across run and change?
How should enterprises define value from software products and use factors contributing to the cost of building products?

Who should attend?

CIOs and CTOs
Business leaders
Product managers
Applications heads
IT and technology directors

Madhurima Chopra

Senior Analyst

Ankit Gupta

Practice Director

Manukrishnan S

Senior Analyst

TCS Is a Steady Business, New CEO K Krithivasan Will See a Smooth Transition, Say Industry Experts | In the News

March 18, 2023

Tata Consultancy Services (TCS) CEO Rajesh Gopinathan was leading an already stable and steady company and transitioning to a new CEO won’t change much for the company or its business, said industry experts and analysts, while still coming to terms with the biggest top-level exit at the country’s largest IT services firm.

Chirajeet Sengupta, Partner at Everest Group, said that TCS has a very strong leadership bench and Krithivasan is a very credible leader. “What will be interesting to see is how he shapes TCS in his own vision or whether he simply continues what Rajesh and team have been doing. But overall, we are very bullish on Krithi’s appointment.”

Read more in Money Control.

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

March 1, 2023

ChatGPT’s arrival has brought much hype and speculation that it could replace several human workforce areas. While ChatGPT shows great early potential, how will it impact the “future of work” and the overall talent landscape? Read the latest blog in our series to learn more about the impact of ChatGPT and other generative Artificial Intelligence (AI) solutions on the workforce.

Since its advent, ChatGPT has taken the internet by storm, reaching a million users in under a week. No wonder it is the most talked about subject in technology and innovation. While ChatGPT has generated a lot of curiosity among netizens, the big techs are not far from the spotlight.

Microsoft has already invested billions in the technology and even integrated it into its search engine Bing. Google has officially announced “Bard,” its ChatGPT rival based on an in-house language model that is undergoing testing before being released to the public.

Chinese search engine Baidu has announced the testing of a similar tool, “Ernie Bot,” while Alibaba also confirmed working on an AI tool. Worldwide, we are witnessing rapid innovation and updates in this field, and by the time you read this blog, we might expect some more new developments.

What does it mean for the talent and workforce industry?

While the utility of a generative AI like ChatGPT remains an area to explore, we expect HR and business leaders to leverage ChatGPT across various dimensions of work and talent management. The workforce industry has evolved over the past few decades, and with the advent of machine learning and AI, we can expect to see some major transformations in the coming few years.

While ChatGPT has the potential to impact talent management, it is still not a replacement for human recruiters. Instead, it can assist them by streamlining the process and making it cost-effective and efficient by automating routine tasks, improving the candidate experience, and enhancing the recruitment process.

Some functions like job screening, content development, and job pricing will see a greater impact than other roles, as illustrated below:

Current mapping of ChatGPT and similar AI across the talent management value chain

Where can ChatGPT replace human involvement in the near and long term?

ChatGPT has already proven its capability to solve math, write code and content, create poetry and literature, converse with other AI tools, and assist with business problems. Soon, generative AI tools have the potential to replace most non-automated tasks such as targeting prospects, writing sales pitches, drafting reports, writing basic code, developing financial models, analyzing data, assessing candidates, optimizing operations, etc. Although the list has no definite bounds, the possibility exists for a single generative AI replacing jobs across multiple domains such as marketing, sales, finance, operations, etc.

The potential impact of ChatGPT and similar AI across workforce areas

Key examples of generative AI adoption

Here are some of the applications for these tools in the industry:

Content creators at leading cloud services company VMware use the AI-based content creation toolJasper to generate original content for marketing – from email to product campaigns on social media
Morgan Stanley is working with OpenAI’s ChatGPT to fine-tune its training content on wealth management. Financial advisors are using it to search for existing content within the firm and design tailored content for its clients
Codeword, a leading tech marketing agency, has already hired the world’s first AI interns as an experiment to assist them with content writing, design, animation, and marketing

On similar themes, we have seen companies leveraging AI, such as Tesla building driverless cars and McDonald’s experimenting with employee-less eateries. In a few years, AI bots could replace various roles, such as customer service executives, recruiters, content writers, and even coders.

We might expect to see a single generative AI tool functioning across multiple domains (finance, HR, marketing, customer service, operations, etc.) within an organization, reducing the need for human intervention.

Blue-collar jobs were already at risk, and the success of ChatGPT further threatens several white-collar professions as well. In the long run, ChatGPT and similar AI tools can open doors to many new opportunities for AI integration, and any prediction we make has a higher risk of falling short of reality.

What challenges are associated with ChatGPT adoption?

We have already discussed the technical challenges of ChatGPT in our earlier blogs (see links at the end of this post.) Human interaction and empathetic judgment are the two major challenges for any AI tool to penetrate the talent management space. Also, limited capabilities in languages other than English and text-driven communication style restrict the use cases of generative AI in non-English speaking regions. Ethical and legal concerns also need to be addressed as the distinction between AI-generated and human-generated data blurs.

In addition, most short-term use cases of generative AI, such as chatbots, already have an alternative available in the market. It will take time for ChatGPT to further integrate into the talent market and move from an experimental basis to organization-wide implementation. Integrating a new system also requires additional investments and training that organizations need to explore.

Impact of ChatGPT on the future workforce

Amid all the hype and speculation, one thing is for sure: AI is here to stay. As humans, we need to embrace it and learn to co-exist with it. With the rise in AI adoption, the talent dynamics also are expected to change, and certain skills/roles associated with it will soar as we enter the age of AI.

Going ahead, we can expect to see higher demand for relevant technical skills. This also creates opportunities for several related skills, such as people with specific domain knowledge to train models and personnel, review content, ensure data reliability, and integrate systems based on industry needs.

Follow our next blog in the series to learn more about the type of skills/roles that will be affected and the new roles that will emerge in demand.

Below are some illustrations of the current capabilities and limitations of ChatGPT on talent-related queries. (The screenshots were taken on February 20, 2023, from India and the responses might be different for other users.)

For our previous blogs on this topic, see ChatGPT – Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term?, ChatGPT Trends – A Bot’s Perspective on How the Promising Technology will Impact BPS and ChatGPT – A New Dawn in the Application Development Process?

If you have questions about the latest trends in the talent landscape or would like to discuss developments in this space, reach out to [email protected] or [email protected].

You can also watch our webinar, Top Emerging Technology Trends: What Sourcing Needs to Know in 2023, to learn more about how organizations can implement new technologies into processes and operations.

Private 5G and Wi-Fi 6: Competition or Cooperation? | Blog

February 24, 2023

While Wi-Fi 6/6E and private 5G technologies each offer advantages in different applications, these next-generation wireless networking technologies can work better together than against one another. Read on to learn how these solutions can complement each other and support enterprises’ technology transformation journeys.

Driven by massively increased device penetration and interconnectedness in recent years, combined with rising investments and research from technology and solutions providers, Wi-Fi 6/6E and private 5G technologies both offer substantial opportunities for enterprise development.

Still in its nascent phase, private 5G is beginning to take off with advancements in this technology particularly prominent across America, Europe, and Asia Pacific, especially in the US, UK, China, and South Korea.

While from a top level, both Wi-Fi 6 and private 5G offer improved network connectivity opportunities and other benefits, the technology types differ in accessibility, licensing, authentication, and use cases. Let’s compare them.

Core differences and suitability

Wi-Fi 6/6E – Generally, it is more suited for indoor, smaller-scale wireless networks. Its lower spectrum complexity and relative implementation ease make it a more accessible solution compared to private 5G. Wi-Fi 6/6E’s increased support for internet of things (IoT)-connected devices and high-density wireless traffic make it ideal for venues such as schools, stadiums, and shopping malls. Wi-Fi 6/6E also can be more easily integrated with enterprise management tools in areas such as security, visibility, and analytics
Private 5G – It is more suited to outdoor use cases on a larger and more complex scale. Autonomous vehicles, smart cities and factories, and remote healthcare are some of the leading use cases and conversation starters for private 5G at present

In the graphic below, we compare the performance and efficiency of each use case. The blue highlighted sections show the areas where the technology is better suited:

Advantages each offer

In terms of accessibility and attractiveness, Wi-Fi 6/6E technologies have some clear benefits over private 5G. The spectrum for wireless local-area network (WLAN) technology is less complex than cellular, which may be more attractive to enterprises looking to incorporate one of the technologies to improve their wireless setup.

Wi-Fi 6/6E as a product also is at a later development stage than private 5G. This means highly developed and specialized equipment already is in mass production and readily available, whereas use case specific private 5G options may not be as well-defined. These factors can make it more cost-effective for enterprises using a Wi-Fi 6/6E solution and have an improved return on investment, especially in the short term.

Private 5G’s higher complexity does bring benefits, though. For instance, it can meet the needs of more complex and intensive wireless setups than WLAN technologies and address enterprises’ data privacy concerns around internal data and security better than a Wi-Fi 6/6E network.

How can these technologies synergize?

Both Wi-Fi 6/6E and 5G can act as catalysts for enterprises’ wireless journeys moving forward, and each offer clear benefits and use cases in which they are preferable. But this doesn’t mean they are necessarily rivals. Rather, treating them as complementary solutions can bring more benefits.

Cooperation between Wi-Fi 6/6E and 5G networks can enable innovation and success with IoT growth and edge computing capabilities. Together, the networks will be able to support remote workforces more efficiently and reliably and bolster overall connectivity with speed and flexibility. Businesses engaging in multiple verticals, for example, may find it better to incorporate both options to deal with their network demands at a range of scales.

Recommendations for the short- and long-term

With that said, enterprises may find it beneficial to focus on solutions from Wi-Fi 6/6E offerings in the short term because this more developed technology can provide greater automation benefits, and is more accommodating for stricter budgets – a substantial plus in a recessionary environment.

Private 5G setups then can be incorporated in the longer term when it is better-developed, more affordable, and able to be utilized in a higher range of verticals and use cases. Private 5G-friendly use cases also will mature in the future in segments including mining, manufacturing, and Industry 4.0.

While Wi-Fi 6/6E technologies are increasingly explored in existing applications, private 5G will become prominent for conceptual and transformative use cases. As a result, enterprises, telecommunications providers, and systems integrators may seek to incorporate private 5G technologies as part of their long-term network setups.

Key Factors to Consider

Ecosystem participants have the following critical factors to consider while making decisions about private 5G and Wi-Fi 6/6E:

Business and network enterprise heads can look to proactively improve their wireless setups with a view to the longer term and the transformative technologies they plan to invest in. This can be achieved by consulting with service providers to see which technologies will better fit their industry-specific demands and use cases
Heads of systems integrators and telecommunications providers can consider the network with cloud and IT as pivotal business initiatives. More specifically, they can investigate treating Wi-Fi6/6E and private 5G options as potentially pivotal in their network decisions. This can allow them to better exploit and benefit from developing network technologies
Partnership heads of technology providers can look to extend their offerings of products and services within Wi-Fi 6/6E and private 5G and showcase their ability to meet the industry-specific use case demands of customers across different segments when partnering

While wireless network decisions often can be an afterthought, having a well-planned strategy can benefit an enterprise’s IT setup and overall business. To achieve short-term results and long-term business transformation, the C-Suite should adopt a dynamic network strategy, including next-generation technologies like Wi-Fi 6/6E and private 5G.

To discuss further, please reach out to [email protected], [email protected] and [email protected].

Check out our webinar, Top Emerging Technology Trends: Six Things Sourcing Needs to Know in 2023, for insights on how to stay ahead of emerging technology.

ChatGPT – A New Dawn in the Application Development Process? | Blog

February 17, 2023

ChatGPT, the advanced Artificial Intelligence (AI) chatbot that’s taken the world by storm, can potentially accelerate various stages in the Software Development Lifecycle (SDLC), from gathering requirements to design and testing, and also enhance developers’ productivity, among other benefits. But it still has limitations. Read on to learn more.

ChatGPT made headlines when it reached 1 million users in just five days after being unveiled in November 2022. Not only was the tech community awed, but it also has interested a wider audience, from students to industry veterans, and attracted more than 100 million users by the end of January 2023.

ChatGPT and other AI chatbots, such as DALL-E, are poised to radically disrupt multiple professions, including education and healthcare. In our ongoing coverage of this trending topic, we’ll explore how these recent developments may rapidly advance the application development process.

What is ChatGPT, and why is it creating major upheaval?

ChatGPT (Chat Generative Pre-Trained Transformer) is a chatbot built by AI firm OpenAI. It is based on Generative Pre-Trained Transformer (GPT-3) architecture, a neural network Machine Learning (ML) model that generates human-like responses to natural language text inputs. Its ability to converse like a human, answer follow-up queries, and reject inappropriate queries makes it more special than its predecessors. Its capabilities include language translation, text summarization, and text generation.

We tried our hands on ChatGPT and asked it to write a blog on itself, and the results amazed us. See the exhibit below for the blog that ChatGPT generated.

Next, let’s explore in more detail how ChatGPT could be embedded in the Software Development Lifecycle (SDLC) to create applications and the associated benefits.

The avant-garde movement in application development

While low-code/no-code and AI-assisted application development made leaps and bounds in this field, ChatGPT has the potential to step up the game even further. This potent AI tool can be used to accelerate different processes at various phases of the SDLC, leading to faster development cycles, enhanced productivity of developers, and quicker value delivery to enterprises.

Here are the potential benefits of each phase:

Requirements gathering: ChatGPT can significantly simplify the requirements gathering phase by building quick prototypes of complex applications. It also can minimize the risks of miscommunication in the process since the analyst and customer can align on the prototype before proceeding to the build phase

Design: DALL-E, another deep learning model developed by OpenAI to generate digital images from natural language descriptions, can contribute to the design of applications. In addition to providing user interface (UI) templates for common use cases, it also may eventually be deployed to ensure that the design of a given application meets regulatory criteria such as accessibility

Build: ChatGPT has the capability to generate code in different languages. It could be used to supplement developers by writing small components of code, thus enhancing the productivity of developers and software quality. It even can enable citizen developers to write code without the knowledge of programming language

Test: ChatGPT has a major role in the testing phase. It can be used to generate various test cases and to test the application just by giving prompts in natural language. It can be leveraged to fix any vulnerabilities that could be identified through processes such as Dynamic Code Analysis (DCA) and perform chaos testing to simulate worst-case scenarios to test the integrity of the application in a faster and cost-effective way.

Maintenance: ChatGPT can significantly improve First Contact Resolution (FCR) by helping clients with basic queries. In the process, it ensures that issue resolution times are significantly reduced while also freeing up service personnel to focus their attention selectively on more complex cases.

While ChatGPT has an important role to play in automating more cognitive tasks in the SDLC, users must be aware that security and privacy concerns with the current version still need to be properly addressed.

Now let’s cover a few issues with the tool.

Five possible roadblocks to ChatGPT adoption

Privacy and security – Privacy and security are concerns with the current tool. As it learns from each query, keying in any sensitive data would have drastic repercussions on enterprises. Amazon has reportedly warned employees to not put confidential data on ChatGPT, fearing security concerns
Limited knowledge – ChatGPT currently is not connected to the internet and has limited knowledge of the world and events after 2021, meaning the code it generates will not be in line with the latest security patches
Potential Bias – While OpenAI has added guardrails against bias in responses, users can occasionally get around this by rephrasing their questions or asking the program to ignore its guardrails
Inaccurate responses – ChatGPT responds to queries based on the patterns it learned from the training dataset and also can generate fictitious responses that cannot be verified for accuracy. Although the tool is still evolving, inaccuracy in responses can be a major hindrance to its adoption
Energy Consumption – As an advanced AI-based tool, ChatGPT takes a huge amount of computing power to process the information, leading to high energy consumption and carbon emissions. With environmental, social, and governance (ESG) becoming a key mandate across geographies, enterprises may be apprehensive about large-scale adoption

The way forward

ChatGPT is seeing rampant adoption among the developer community, and as it gains further traction, enterprises need to ensure suitable governance models are in place. Service providers need to collaborate with tech players like OpenAI and DeepMind to proactively shape the market and build capabilities for efficient application development.

As details unfold on how this technology will revolutionize the application development process, enterprises and service providers need to closely monitor this space and make proactive investments – clearly, the cost of missing out is too great.

For our other recent blogs on how ChatGPT will impact various industry sectors, see Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term and ChatGPT Trends – A Bot’s Perspective on How the Promising Technology will Impact BPS.

We’ll investigate the implications of ChatGPT for the technology services industry in more detail in a follow-up blog.

To discuss how ChatGPT will impact the application development process, please reach out to [email protected], [email protected], or [email protected].

ChatGPT – Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term?

February 2, 2023

With the advent of chatbots reaching human-like sentience and mannerisms, and banks being at the forefront of adopting conversational Artificial Intelligence (AI), the question arises whether ChatGPT threatens the likes of Google, other AI platforms, and the non-critical workforce in the technology and services industries. While its promise remains high, will the banking, financial services, and insurance (BFSI) sector unearth ChatGPT’s full potential? Read on to find out.

ChatGPT has taken the internet by storm and has become a trending sensation overnight. This AI-powered innovative chatbot has taken the world for a spin and is generating a big buzz among millions of professional users experimenting with it. Microsoft has also invested billions in the tool.

But what is ChatGPT? Developed by OpenAI, it is a generative language model that has been trained over large volumes of text to generate human-like responses. Like a search engine, it curates answers for queries but is designed to answer in a more conversational flow that goes beyond chat and delivers a richer experience with an intelligent chatbot. The AI engine generates solutions for all sorts of queries, including R, Python, and VBA codes.

Let’s explore ChatGPT’s potential to impact the future of AI and its usage in the technology and services industry, particularly by financial institutions, banks, and insurers.

What makes ChatGPT approachable and different to use?

The amount of data used to train the GPT model
Human-like interaction
Versatility and variety of responses
Low data input requirements
Highly scalable
Adjustable coherence and adaptability

What does it mean for banking and financial services?

Banks can use ChatGPT in several ways to enhance their operations and customer experience. Here are a few examples:

Assistive chatbots: ChatGPT can be used to build natural language-based chatbots that can assist customers with common inquiries, such as account balances, transaction history, and bill payments. The chatbot also can guide customers through more complex processes like applying for a loan or a credit card. It also could help increase agent efficiency by aggregating requests by type to the appropriate departments
Automation of simple and repetitive tasks: ChatGPT, along with other conversational AI models, can be used to automate simple and repetitive tasks, such as customer service interactions, order processing, and data entry. This can increase efficiency and lower costs for service providers and their clients
Customer service: ChatGPT can assist the human agent in answering customer questions, improving efficiency and response time, and providing more accurate and detailed information. This can improve customer service and satisfaction and employee onboarding
Marketing: Banks can use ChatGPT to analyze customer data and build personalized marketing campaigns that target specific customer segments. It also can generate personalized responses to customer inquiries by fine-tuning the model to a specific client, enabling it to generate tailored responses to their needs
Decision Making: With the right database connections and integrations, ChatGPT can be used to analyze data to generate insights that can be used in decision making
Learning and development: ChatGPT can be used as a learning and development tool. It can be trained with a company’s pre-existing data to create learning tools and modules and as an onboarding tool for new employees

Current mapping of ChatGPT to the BFS BPS value chain

Current use cases of ChatGPT in banking and financial services (BFS) and business process services (BPS) operations are limited. Building capabilities around conversational AI and incorporating ChatGPT into offering portfolios can help BFS and BPS firms unlock innovation. Enterprises such as Microsoft, AWS, and Meta are developing their capabilities internally or through partnerships with conversation AI specialists.

Industries leading in innovation investments are becoming early adopters of ChatGPT. Microsoft is reportedly investing US$10 billion in OpenAI and plans to introduce it along with its Azure OpenAI service bundle in the Bing search engine. This furthers Microsoft’s stake in the market, where it already has a working partnership with OneReach.ai, one of the market’s leading conversation AI providers, since 2019.

Current capabilities still have hurdles to overcome

Although ChatGPT appears to have multiple uses and strengths, some limitations include:

Biased and inconsistent output: Content generated by ChatGPT depends on the trained data, making it prone to biases. It is difficult to achieve the same level of consistency in output generated. Cases requiring more context and complexities may lead to biased and inconsistent output. When training for complex operations such as trade reconciliation, exception management, and know your customer (KYC) remediation, the subject matter experts (SMEs) must be well-versed with minute details, which can’t be guaranteed when using ChatGPT
Standardized data requirement: ChatGPT cannot process different file types or extract information from them. A lot of consumer data is often received in varied file types and formats that require intelligent operations to skim through and sort, which is beyond ChatGPT’s current text-based data capabilities
Largely text driven: Its text-based generated content can fall short of expectations for the coming generation of users that desire more visual stimulation. Dashboards and descriptive analytics have become a basic requirement of all transaction-intensive industries that ChatGPT cannot fulfill
Limited ability to handle sensitive customer information: ChatGPT may not have the necessary security and privacy measures to handle sensitive customer information, such as account numbers or personal identification numbers. With the ever-evolving compliance norms varying across industries, it doesn’t yet have the capability or the secure framework to process, analyze, and interpret KYC or transaction data
Outdated information: ChatGPT’s information database is limited to data up until 2021 and can result in outdated opinions and facts. Deals, news, and updates in recent years aren’t recorded. For a constantly-evolving industry like BFS, where new deals and contracts dictate the capital markets, this makes the source of information unreliable
Ethical concerns: As artificial intelligence improves, the lack of proper credit for AI-generated content is becoming more widespread. The distinction between content created by AI and content created by humans is becoming less clear, causing confusion, mistrust, and ethical dilemmas
System Integration issues: Incorporating new technology with outdated systems can be difficult due to potential incompatibilities and differing protocols or data formats. This can decrease efficiency, add complexity, and impair interoperability

Where will the future take ChatGPT?

While ChatGPT’s future looks promising, it is too early to say the product will revolutionize banking and financial services. Before it gets integrated into banking products, it needs to overcome several hurdles, including:

Responding to competition from rising financial technology (FinTech), regulatory technology (RegTechs), and other AI/Machine Learning (ML) service providers
Meeting regulatory, compliance, and cybersecurity requirements
Catering first to front-office requirements for low-critical queries and then for more complex queries and back-office operations that have not yet been explored
Maintaining high operational efficiency, accuracy, and customer satisfaction
Expanding variation in output categories
Overcoming the lack of recent factual data

Though ChatGPT use cases are promising, it is still a machine learning model that needs modifications to be used in real-world applications. The model would have to consume specific industry data to build domain depth and be programmed to manage contextual nuances for various tasks. Its ultimate success would depend on end customers’ user experiences.

While the road is being paved for innovation, ChatGPT still has a long way to go before making strides into banking and financial services.

To further illustrate the nature of results and drill down on the capacity of ChatGPT, below are some screenshots for financial crime and compliance queries (platforms, codes, advisory):

If you have questions about banking and financial services trends or would like to discuss developments in this space, reach out to [email protected], [email protected], and [email protected].

Also, download our Navigating the Regulatory Tightrope via End-to-End Solutions – Financial Crime and Compliance (FCC) State of the Market 2022 report to explore key trends. Stay updated by following the latest research on Banking and Financial Business Process Services.

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