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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.

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 Trends – A Bot’s Perspective on How the Promising Technology will Impact BPS | Blog

February 9, 2023

What better way to find out how ChatGPT will impact the Business Process Services (BPS) market than to ask the trained chatbot itself this question? According to its answers, the future looks promising. But obstacles still need to be overcome. Learn about the latest ChatGPT trends in this second part of our series.

Since OpenAI released ChatGPT for public testing in November 2022, ChatGPT has generated a lot of buzz. Based on initial impressions, the technology holds great promise to enhance and revolutionize many industries, including customer experience, healthcare, logistics, banking, and education, among others.

With all the attention, it’s natural to wonder how ChatGPT will impact the BPS market. And how better than to hear it straight from the bot? So, our analyst logged in on a session with ChatGPT and had a very direct and long conversation. Here’s what we learned:

Figure 1A Snippet from a conversation with ChatGPT

ChatGPT’s potential to enhance customer experience is fairly well known. It has shown the promise to improve current conversational Artificial Intelligence (AI) solutions and make them sound more human-like, which can significantly change how these services are delivered.

It is already capable of understanding natural language with high accuracy, and with enough training, it can start with taking on simple tasks at contact centers. ChatGPT also can track customer preferences and provide real-time insights that can unlock new opportunities for enterprises.

Exploring ChatGPT trends beyond experience

We were interested in understanding its impact beyond customer experience in other major areas such as back-office, content moderation, and finance and accounting, so we asked ChatGPT.

Below is a summarized finding of how ChatGPT can revolutionize six key areas, according to the conversation. (And we have no reason to believe it might have been exaggerating, unlike, say, an analyst writing something similar).

Back-office: Can automate back-end processes such as data entry, record keeping, and reporting, freeing up employees for more value-adding work
Content moderation: Can assist with content moderation by automatically detecting and flagging potentially harmful or inappropriate content, improving efficiency and accuracy compared to manual moderation
Human resources: Can automate repetitive tasks such as candidate screening, resume filtering, and scheduling interviews, freeing up HR staff for more value-adding work. It can provide quick and accurate responses to candidate inquiries, improving the overall candidate experience and making the hiring process more efficient. Another use is virtual interviewing, making it easier for HR to conduct interviews with candidates located in different locations
Financial and accounting: Can automate tasks such as invoice processing, expense reporting, and budget tracking, freeing up finance staff for more value-adding work
Supply chain: Can assist with supply chain management by providing real-time visibility into inventory levels, shipment status, and other supply chain data, enabling companies to make data-driven decisions and optimize their supply chain
Procurement: Can automate procurement tasks such as vendor management, purchase order creation, and invoice processing, helping procurement teams work more efficiently and effectively

The answers show the technology can potentially have positive repercussions across major areas within BPS. With such huge potential, ChatGPT is expected to impact talent as well. While demand may decline for low-skill jobs such as data entry and transactional customer service, ChatGPT will require new skills such as AI and data analysis, creating new job opportunities in areas such as conversational AI design and deployment. As enterprises adopt ChatGPT and other AI technologies, developing new skills and staying up-to-date with industry trends and advancements will become increasingly important for employees.

While the technology is certainly promising, several factors must be considered for successful implementation, including ethical and legal considerations (such as data privacy and algorithmic bias), integration with existing systems, quality of training data, human oversight, and ongoing development and improvement.

ChatGPT has the potential to significantly impact various areas within BPS. While challenges exist, careful planning and considering factors such as data privacy and ethical implications can lead to successful implementation and ongoing improvement. With careful investments, planning, and further technological advancement, ChatGPT can reach its full potential before too long.

For the first part in our series, see ChatGPT – Can BFSI Benefit from an Intelligent Conversation Friend in the Long Term? To discuss ChatGPT trends, please reach out to Sharang Sharma.

IMC 2022 Highlights: India Mobile Conference Focuses on 5G Business Opportunities | Blog

November 17, 2022

With the launch of 5G in India last month, the 2022 Indian Mobile Congress (IMC) demonstrated many exciting possibilities for the high-speed network to deliver innovative use cases in India. Beyond the technology benefits, 5G can be leveraged to solve efficiency and optimization challenges and enable future growth for enterprises. To learn more about 5G business opportunities, read on.

India embarked on its “new digital universe” with the official unveiling of 5G technology by Prime Minister Narendra Modi at the sixth edition of the Indian Mobile Congress (IMC), Oct. 1-4 in Pragati Maidan in New Delhi. In this blog, we share some of our key takeaways from the event organized by the Cellular Operators Association of India (COAI) and India’s Department of Telecommunications (DoT).

The evolution of connectivity technologies with 5G as a platform for boosting productivity and innovation was among the key themes that emerged from this India mobile conference that drew an enthusiastic response from technology service and infrastructure providers, manufacturers, industry and government officials, academia, and the public.

Shifting narrative: from explaining technology to showcasing possibilities

While the 5G benefits of increased connectivity speed, low latency, and improved reliability are now well known, the India mobile conference highlighted several 5G-enabling technologies. These include carrier integrated 5G network (low- and mid-band); open-source technologies and architectures (O-RAN); network cloudification through Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and Multi-Access Edge Computing (MEC); small cell 5G architecture, private 5G, network slicing, and Fixed Wireless Access (FWA).

An interesting highlight of the event was the increased emphasis on showcasing the applications of 5G. Among the possible use cases spotlighted were massive and critical Internet of Things (IoT), machine-to-machine communication, collaborative robotics, autonomous driving, vehicle edge computing, metaverse and Augmented Reality (AR) powered collaboration, predictive maintenance, remote surgery, real-time analytics and decision making, cloud-based gaming, smart cities solutions, intelligent supply chain and logistics, and smart retail.

With 5G resolving connectivity problems and other building blocks like cloud, Artificial Intelligence and Machine Learning (AI/ML), and IoT now mainstream, enterprises have all the needed elements to optimize and modernize their technology landscape and capture the next wave of growth opportunities.

5G for sustainability: an emerging conversation

While 5G network equipment and components are generally expected to consume more power than the previous generation, recent equipment and software innovations aim to make products as energy efficient as possible.

Some examples of the energy-efficient technology presented at IMC included lightweight massive Multiple-Input Multiple-Output (MIMO) radios and software solutions such as traffic-aware dynamic network management solutions for energy monitoring and management that provide 5G levels of expected network performance while consuming the same amount of energy as the traditional 4G network.

5G also is expected to power the next generation of sustainability applications around Greenhouse Gas (GHG) emissions monitoring and management, optimal resource management, smart transport, and other uses. Its higher bandwidth will make it possible to connect large numbers of IoT devices over the Internet and enable faster decisions through increased connectivity speeds and low latency.

Turning possibilities into practicalities: the need for building a contextualized business case

While 5G offers numerous benefits, from optimization and efficiency to unlocking new growth avenues, the strategic business value needs to be clearly communicated to enterprises.

Currently, the 5G ecosystem is a bit fragmented, with different types of players offering their own strengths. For example, OEMs are focusing on improving the equipment and hardware; communication service providers are focused on increased speed and low latency; and system integrators (SIs) bring data, AI/ML, IoT, and cloud expertise.

To move to the next level, industry players need to combine 5G’s benefits of connectivity, reliability, and low latency with AI/ML, IoT, and cloud to build business use cases that add value to enterprises beyond just showcasing the possibilities.

Ecosystem players need to help enterprises realize that 5G is not only an improved wireless network technology but also a solution to their long-standing efficiency and optimization challenges that can enable their next wave of growth.

To further discuss the India mobile conference and how to capture the most value from 5G business opportunities, please reach out to us at [email protected] and [email protected].

Watch our webinar, What’s Ahead After a Decade of Digital Transformation?, to hear our analysts share perspectives on what’s in store for the digital transformation industry in the next ten years.

3 Tips for Managing Perpetual Change from Software-defined Operating Platforms

October 4, 2022

Over the past seven years, almost all large companies made substantial progress in implementing digital transformation across a wide variety of functions. At the core of those enormous investments and efforts was building software-defined operating platforms, which put companies on a trajectory to fundamentally change how they operate their business. However, studies show many companies (70%) failed or underperformed against their digital transformation objectives. In this blog, I’ll discuss three tips for how to avoid that outcome and, instead, reap the significant benefits of software-defined operating platforms.

Read on in Forbes

Digital Transformations: 5 Emerging Trends in the Intelligent Process Automation Market

August 4, 2022

The pandemic’s effects on the digital landscape are long-lasting. Businesses are evolving to rely on the intelligent process automation market (IPA) to promote growth and keep up with competitors. Read on to learn more about five growing IPA trends.

In a world becoming increasingly reliant on technology, financial services organizations are digitizing and automating more processes to keep up with the competition. The intelligent process automation market, growing by about 20% across all fields, is now becoming ubiquitous.

IPA is defined as automation in business processes that use a combination of next-generation automation technologies — such as robotic process automation (RPA) and cognitive or artificial intelligence (AI)-based automation, including intelligent document processing and conversational AI. Solution providers are offering solutions across RPA, Intelligent Document Processing (IDP), and workflow/orchestration, as well as crafting innovative solutions such as digital Centers of Excellence (CoE) and investing more in as-a-Service offerings.

In our recent Intelligent Process Automation (IPA) – Solution Provider Landscape with PEAK Matrix® Assessment 2022 report, our analysts ranked IPA technology vendors and looked at the market for IPA solutions. Based on the research, the growth of IPA technology and reliance will expand to around 25% over the next three years.

Five intelligent process automation market trends enterprises should know

The question of how to become faster, more efficient, and more resilient is the focus for just about any organization undergoing digital transformation. Very often, the answer to this question is at least, in part, intelligent process automation. In the near future, we can see five emerging IPA trends:

IPA will get smarter

A greater proportion of cognitive elements is finding its way into the intelligent process automation market. About 60% of new automation projects involve more advanced cognitive tools such as IDP, conversational AI and anomaly detection. As the maturity of AI-based solutions increases, cognitive automation will be in greater demand. All-round adoption of IPA will be fueled by providers entering new geographies and organizations starting IA initiatives.

IPA will be more scalable

Although many organizations are trying to adopt intelligent process automation, the real question is if it can be scaled up or, in other words, if it can be brought across the organization. To help enterprises scale automation, solution providers are investing in expanding their partner ecosystem, strengthening technology capabilities, and enhancing their services portfolio.

Providers are also expected to help enterprises scale up through more effective change management and CoE set-up strategies. Aided by the prevalence of process intelligence solutions to form robust pipelines and orchestration tools to facilitate holistic automation, enterprises are better equipped now to move away from siloed applications of IA to scaled-up automation implementations.

Citizen development will grow

Many organizations are experimenting with what they can do with citizen development, especially with the current talent shortage. Citizen-led development also holds the power to disrupt the current state of building automation and addresses the issue of talent availability. Solution providers are expected to invest in citizen development and low-code/no-code technologies enabling business users to build automation, consequently also addressing the talent shortage in the market.

Solution and technology providers are also expected to invest substantially in developing the low-code/no-code capabilities of their platforms to enable business users with limited technical exposure to build automation solutions on their own. A few solution providers are implementing citizen development programs in their own organizations and are planning to leverage the learnings to develop effective governance programs for enterprises.

IPA service providers will bring IPA solutions packages to the market

Packaged solutions are gaining traction in the IPA market due to their ease of implementation and quick Return on Investment (RoI). Solutions for F&A are the most prevalent in the market. These solutions will need training on particular data sets to make them functional for a particular process, but they will speed up implementation. Providers are expected to take conscious steps toward promoting sustainable AI by developing solutions complying with environmental, social, and governance (ESG) parameters. They are also investing in AI solutions that are transparent about their working and usage of data.

IPA service providers will pre-build connectors to legacy and other systems

There are a host of technologies, including RPA, conversational AI, process mining, and process orchestration in the IA ecosystem. Very often these IA solutions need to talk to the various other systems. Many IPA service providers are driving innovation and crafting new solutions to keep pace with the fast-moving IPA market and create a more holistic integration process. One such method is offering enabling capabilities like pre-built connectors for a faster and less complex implementation.

If you would like to learn more or discuss the intelligent process automation market and IPA trends, reach out to [email protected].

Learn how the healthcare industry is utilizing intelligent automation, digitalization, and telehealth as fundamental driving forces to transform and evolve in the webinar, How Intelligent Document Processing Is Transforming the Healthcare Industry.

Composable Commerce: For Composing the Best-of-Breed Customer Experience

July 20, 2022

From monolithic to MACH architecture, the next evolution in digital experience is here – composable commerce. Similar to building with Lego Blocks, this modular approach allows enterprises to create unique models by selecting “best-of-breed” digital commerce components. Learn how composable commerce is optimizing all aspects of the online shopping experience and what tech providers are pioneering solutions in this rapidly rising area.

Digital commerce growth leads to composable commerce

Just as the COVID-19 pandemic has been a catalyst in accelerating digital platform adoption among enterprises, modern consumers’ purchasing habits have dramatically changed due to frequent lockdowns and increasing online purchasing convenience.

According to a United Nations Conference on Trade and Development (UNCTAD) report, the average share of internet users who made purchases online increased from 53% before the pandemic to 60% across 66 countries following its onset in 2020/21.

The shopping experience has evolved from brick and mortar stores to online and moved to unified commerce – an amalgamation of offline and online channels with an ever-evolving myriad of customer touch points such as social commerce, video commerce, and now metaverse, etc.

Emerging business models such as Digital to Commerce (D2C), new and interactive channels, and advancements in technology, especially Artificial Intelligence (AI) and Augmented Reality/Virtual Reality (AR/VR), have fueled digital commerce’s growth. In response, the underlying digital commerce architecture principles have also morphed to meet the pace of change in digital-native customer expectations.

What is composable commerce, and how will it unlock business value?

Up until a few years ago, monolithic architecture-based platforms were the de facto choice for any digital commerce storefront. These big and chunky solutions providing standard out-of-the-box features for all customers offered a “one-size-fits-all” approach. Enterprises had to be content with these standard features and were required to spend huge budget and time on customizations to meet their business requirements.

However, major issues with scalability, complexity, longer time to market, and budget made this implementation approach less useful for modern commerce businesses where staying abreast of technological advancements, customer centricity, and nimbleness are of utmost priority.

The next major evolution in digital commerce architecture is MACH (microservices-based, API-first, cloud-native, and headless) architecture enabled enterprises. This approach will overcome the shortcomings of monolithic architecture and responsively and dynamically adapt to customer expectations.

Taking a step forward from MACH architecture, the era of composable commerce has dawned. Composable commerce – a modular approach to implementing digital commerce – uses interchangeable building blocks, leveraging the MACH Architecture framework. It offers enterprises the choice to select “best-of-breed” digital commerce components such as Product Information Management (PIM), Customer Relationship Management (CRM), pricing, etc., and is similar to Lego Blocks where users can create unique models. These composable components are the specific solutions provided by third-party vendors.

While the microservice approach breaks down the digital commerce modules into individual building blocks, composable commerce enables the linkage of these microservices to realize a specific business value. Composable commerce utilizes Packaged Business Capabilities (PBCs), a fully functional, independent component serving a defined business capability. These are used as building blocks for “composing” the unique platform. Each PBC can consist of several microservices. These PBCs can be individually replaced or modified without impacting the entire platform.

Thus, composable commerce has shifted the focus toward business-centricity. Composable commerce is built for an organization’s unique operating models, strategic priorities, and customer focuses. Businesses can select essential functionalities for their requirements and “compose” them into a custom application built for their digital commerce platform. This allows enterprises to focus on the relevant PBCs for their business that are sometimes unavailable in the traditional and bulky monolithic platform’s “out-of-the-box” features.

Below are some benefits of composable commerce that enterprises can realize.

The number of PBC vendors providing functionalities such as loyalty, promotions, search, reviews and ratings, analytics, etc., is rapidly growing. Enterprises have the flexibility to choose the best vendor for their platform, considering their individual business and technical requirements. They can manage multiple brands and varying business models, leveraging the same composable commerce stack to stay nimble in response to market changes. Complex business can be launched and managed more efficiently using composable commerce.

Technology providers are already pioneering composable commerce solutions

Technology providers have extensively started working on solutions to enable enterprises to get on board the composable commerce bandwagon. Below are some examples:

Spryker has launched the cloud-native “App Composition Platform,” which gives enterprises seamless access to third-party services and best-of-breed digital commerce vendors
Virto’s Atomic Architecture™ allows customers to get a composable, flexible, manageable, customized, and easily-updated digital commerce architecture that is fully adaptable to market challenges
Elastic Path’s Composable Commerce Hub is an open exchange of composable commerce solutions for digitally-driven brands that want to seamlessly create complete digital commerce experiences for their business
Fabric provides a configurable and composable commerce solution to rapidly deploy and scale unique brand experiences, product offerings, and services
Infosys Equinox is powering Nu Skin to compose unique and delightful digital journeys across ever-evolving channels
Avensia’s composable commerce solution Avensia Excite is built on commercetools. Avensia Excite uses Contentful for CMS, Inriver for PIM, and Apptus eSales for search engine

Composable commerce outlook

While MACH architecture had set a strong foundation for modern digital commerce architecture, composable commerce is the next logical iteration in the digital commerce business model to meet rapidly changing customer expectations and the growing number of touch points. Composable commerce adoption will continue to witness a rise as enterprises plan to move away from the traditional approach of implementing digital commerce solutions. More and more niche third-party vendors are emerging faster than before, providing ample choice for enterprises to craft and “compose” their digital commerce stack.

If you have questions about digital commerce, please reach out to Nisha Krishan ([email protected]) and Aakash Verma ([email protected]).

Stay tuned for insights on the digital commerce platform market from our recently launched inaugural Digital Commerce Platform PEAK Matrix^® Assessment.

Selecting the Right Low-code Platform: An Enterprise Guide to Investment Decision Making | Blog

July 15, 2022

Enterprise adoption of low-code platforms has been invigorated in recent years by its potential to drive digital transformation. This fast-rising platform solution offers promise to democratize programming with today’s talent shortage and help companies develop applications and enhance functionalities faster. While the opportunities are clear, charting a path to successful adoption is ambiguous. Learn the 4Cs approach used by best-in-class enterprises for selecting and adopting the right-fit low-code platforms in this blog.

As many as 60% of new application development engagements consider low-code platforms, according to Everest Group’s recent market study. Driven by the pandemic, the sudden surge in demand for digital transformation accelerated low-code annual market growth to about 25%. Considering its potential, low code is appropriately being called the “Next Cloud.”

Interest by investors also has accelerated, further driving R&D spend for new product development. Funding activities in 2022 to companies featuring low code in their profiles already amounts to $560 million across 40 rounds.

Platform providers are responding to these elevated expectations with equal fervor by building platforms with deep domain-specific expertise, while others are providing process-specific solutions for enterprises’ customization requirements.

While these markets have resulted in a proliferation of low-code platforms to choose from, it also has led to confusion and inefficiencies for enterprises. As more and more enterprises explore the potential of these platforms, IT leaders are faced with numerous questions and concerns such as:

“How do I select the platform that can address my current and future requirements?”

“Which platform will work best in my specific enterprise IT landscape?”

“How can we optimize the investment in this technology?”

“How do I compare the pricing structures of different low-code platforms?”

“How do we ensure governance and security of the IT estate with these new tech assets?”

Adoption journey and evaluation parameters for low-code platforms

In addition to the high-priority use cases that initiate the adoption, enterprises should consider the platform’s scalability potential, talent availability for support and enhancement, and integration with the broader IT landscape to make the right selection.

Additionally, low-code platforms are intended to address the requirements of the IT function as well as business stakeholders. Considering the drivers, expectations, and requirements of both when making the selection is essential. A collaborative decision-making set-up with the central IT team and key Line-of-Business (LoB) leaders is critical for a successful platform selection. Let’s explore the 4Cs to low code success.

4Cs to low code success

The key steps to ensure successful low-code platform selection and adoption are:

Contemplate: Initiate platform adoption by a set of high-priority use cases but plan for scalability at the enterprise level during platform selection
Collaborate: Bring together the central IT group to lead the selection and adoption effort and meaningfully involve the LoB stakeholders
Compare: Start with business and tech drivers, expectations, and requirements from both IT and business to prioritize and rank platforms and select the best-fit platform
Customize: Make small and incremental enhancements post-adoption to broaden the platform’s scope without disrupting daily operations

This approach can provide a roadmap for enterprises with distinct outcomes. We have witnessed enterprises either adopting the best-fit approach resulting in a platform portfolio or leveraging a single platform as a foundation for an enterprise-grade innovation engine.

For instance, the Chief Technology Officer (CTO) of a leading bank in the US invested in establishing a low code Center of Excellence (CoE) that uses different platforms for process automation, IT Service Management (ITSM), and enabling point solutions for business users.

On the other hand, a large US commercial insurer built its entire end-to-end multi-country app on a single low-code platform. This comprehensive, business-critical application managing claims, billing, and collection is accessible by all underwriters and service personnel.

Next, we explore how to best compare platforms based on their offerings and capabilities. The tables below illustrate the top five business and technology-oriented parameters to consider when evaluating platforms, along with their relevance and enterprise expectations.

Technology parameters for low-code platform selection

Factors associated with the platform’s technical robustness are of key importance to IT decision-makers. Integration and UI/UX capabilities are at the top of enterprise’s technology priorities when comparing multiple platforms.

For instance, Appian ships with 150-plus Out-of-the-Box (OOTB) connectors. Appian SAIL, a patented UI architecture, takes declarative UI definitions to generate dynamic, interactive, and multi-platform user experiences. It also makes the applications more secure, easy to change, future-proofed, and native on the latest devices.

Business parameters for low-code platform selection

Assessing these parameters is important to understand whether low code can be sustained and scaled long-term and if it addresses the business users’ expectations. Pricing and security constructs are at the top of the list for businesses looking to adopt a low-code platform.

Let’s consider Salesforce as a case-in-point. Salesforce has security built into every layer of the platform. The infrastructure layer comes with replication, backup, and disaster recovery planning. Network services have encryption in transit and advanced threat detection. The application services layer implements identity, authentication, and user permissions. In addition, frequent product updates that help it to align its product offering with changing market demands put Salesforce as one of the go-to platforms for all the CRM needs of enterprises.

Low-code platform outlook

The plethora of options makes it difficult for enterprises to zero down their investments on a particular low-code platform. Enterprises must also leverage their network of service partners for guidance in this decision-making process.

Talent availability for implementation and enhancement support is critical to keep in mind during the platform selection. For the same reason, multiple system integrators are now taking the route of inorganic growth to bolster their low-code capabilities.

This is the time to hop on the low-code bandwagon and establish low code as the basis for enterprise digital transformation.

Everest Group’s Low-Code Application Development Platforms PEAK Matrix^®Assessment 2022 provides an overview of the top 14 platforms based on vision, strategy, and market impact.

To share your thoughts and discuss our research related to low-code platforms, please reach out to [email protected] and [email protected].

Metaverse and ScienceTech: Will These Virtual and Real-world Markets Compete?

July 4, 2022

Metaverse is the buzz these days. While Metaverse provides an embodied virtual-reality experience, ScienceTech fuses technology and science to solve real problems of humanity. Who will win in the battle for relevance, investments, and talent? To learn more about these virtual and real-world market opportunities and what actions technology and service providers should take, read on.

While they once seemed far out, the Metaverse and ScienceTech are here now. As part of our continued Metaverse research, let’s explore these emerging technologies and whether they will collide or coexist.

ScienceTech brings together technology and science to improve the real world by enhancing living standards and improving equality. It combines technology with physical sciences, life sciences, earth sciences, anthropology, geography, history, mathematics, systems, logic, etc.

Meanwhile, the Metaverse is an emerging concept that uses next-generation advanced technologies such as Augmented Reality (AR)/Virtual Reality (VR), digital assets, spatial computing, and commerce to build an immersive, seamless experience.

Over the past few months, Metaverse has become a hot topic not only in technology circles but also among enterprises. As providers pump billions of dollars to create the landscape and value realization becomes clearer, Metaverse will grab increasing attention from enterprises, providers, and market influencers.

Its serious market potential can be seen by the collaboration of industry participants to define standards to interoperate Metaverse platforms and ecosystems. Everest Group is witnessing great interest in our Metaverse research and our recent webinar Web 3.0 and the Metaverse: Implications for Sourcing and Technology Leaders generated unprecedented client inquiries.

ScienceTech has been around for many years but has been mostly experimental with limited revenue and growth. Technology and service providers have been reluctant to meaningfully scale this business because of its complexity, significant investment requirements, and high risk of failure.

However, the pandemic has changed priorities for enterprises and individuals, making ScienceTech more critical to solving real-life problems. The cloud, an abundance of data, better manufacturing processes, and a plethora of affordable technologies have lowered the cost of enabling and building these offerings.

Competition between Metaverse and ScienceTech

Below are some of the areas where these two emerging fields could conflict:

Relevance

Many cynics have decried Metaverse as one more fantasy of BigTech trying to take people further away from reality. This cynicism has gained pace in light of the disruptive global pandemic. The make-believe happy world driven by a heavy dose of virtual reality takes the focus of humanity away from the pressing needs of our time.

While not well defined, ScienceTech is generally perceived as being different from pure play. Some of its ideas have been around for many years such as device miniaturization, autonomous systems, regenerative medicine, and biosimulation. The core defining principle of ScienceTech is that science researched, validated, and hypothesized themes are built through technology. The relevance of ScienceTech may appear far more pressing to many than the make-believe virtual world of Metaverse.

Investment

The interesting competition will be for investments. Last year, venture capitalists invested over US$30 billion in crypto-related start-ups. As the Web 3.0 and Metaverse tech landscape becomes more fragmented and crowded, investors may not want to put their money into sub-scaled businesses. This can help the ScienceTech space, which is not well understood by investors, but offers a compelling value proposition.

Talent

Technology talent is scarce and ScienceTech talent is even scarcer. Although Metaverse vendors will continue to attract talent because they can pay top dollar, ScienceTech vendors can offer more purpose and exciting technologies to niche talent. In the internet heydays, people bemoaned that bright minds were busy clicking links instead of solving world problems. Metaverse may have that challenge and ScienceTech can benefit from this perception. GenZ job seekers want to work in areas where they can impact and change the world, and ScienceTech can provide that forum.

What should technology and service providers do?

Both Metaverse providers and ScienceTech companies will thrive and share quite a few building blocks for technologies, namely, edge, cloud, Artificial Intelligence (AI), and data. Multiple technology and trends will not battle. Moreover, these two markets serve different purposes and Metaverse and ScienceTech will coexist. Technology and service providers will need to invest in both segments, and capture and shape the market demand.

Providers need to prioritize where to focus efforts, investments, partnerships, and leadership commitment. A different people strategy will be needed because skilling technology resources on science and vice-versa will not work. They will need to select specific focus areas and hire people from multiple science domains. The R&D group will have to change its constituents and focus on science-aligned technology rather than just Information and Communications Technology.

To be successful, providers also will have to find anchor clients to underwrite some offerings, collaborate to gain real-life industry knowledge, and engage with broader ecosystems such as academia, government, and industry bodies to build market-enabling forums.

To learn more about our Metaverse research and discuss your experiences in these emerging areas, contact [email protected] or contact us.

Visit our upcoming webinars and blogs to learn more about upcoming technologies and trends.

Low-code Market Realities: Understanding Common Myths to Avoid Costly Mistakes

June 23, 2022

Despite their growth, low-code platforms are still surrounded by much confusion. Many enterprises incorrectly believe that real developers don’t need low code, anyone can do it, and it’s only for simple problems. To debunk three common myths in the low-code market, read on.

With its increasing importance, low-code platforms are also subject to several myths and misunderstandings. As with every evolving technology, enterprises have many questions about optimally using these platforms.

Based on our conversations with multiple enterprises confirming the lack of understanding about the low-code market, we tackle the common misperceptions below:

Myth #1: Low-code platforms are meant for use by citizen developers

The term low code generally evokes the impression of an HR manager who, tired of following up with the IT team multiple times, decides to create a leave approval workflow application. While this impression is not incorrect, professional developers and enterprise IT teams are key stakeholders in the low-code ecosystem as well.

Professional developers increasingly use low-code platforms to improve their efficiency. Some of these platforms can provide code quality alerts and Artificial Intelligence (AI)-powered recommendations, not to mention custom solutions that require minimal tuning.

The built-in DevOps capabilities in these platforms also encourage a culture shift from the commonly used waterfall model among users. For example, supply chain management software provider Nimbi significantly reduced developers in their team from 40 to 24 when they switched to OutSystems from traditional platforms.

We strongly believe central IT teams have a meaningful role in the ecosystem to provide effective oversight and governance, in addition to strategizing the use of the best low-code platforms at the enterprise level. In the absence of centralized governance, low-code platforms may proliferate across the organization leading to aggravation of the shadow IT issues and higher spend.

Myth #2: Low-code development does not require technical skills

As much as we may want to believe, low-code platforms are not a panacea to the ongoing talent crisis. Misleading promises by certain technology vendors have created a common impression that any user can develop any application using low-code platforms. However, low-code development does not imply zero technical skill requirement.

Most low-code platforms enable the extension of their capabilities through traditional programming languages like Java and C#. Off-the-shelf solutions have their limitations, and most applications need custom logic at some point. Typical job descriptions for low-code developer profiles outline technical qualifications like JavaScript, HTML5, and CSS3, alongside Continuous Integration (CI) and Continuous Delivery (CD) pipeline tools like Jenkins.

Thus, it is unrealistic to expect an army of business users to step in and take over all application development-related needs from the IT organization. Low-code development remains a role with a highly demanding skillset across various technologies.

Myth #3: Low code cannot be used for enterprise-grade development

Many enterprise leaders and service providers believe that low-code platforms are only suitable for small-scale department-level needs. However, our conversations indicate that low-code platforms are being rapidly adopted for critical applications used by millions of users. Here are some examples of how low code is solving complex IT problems around the world:

A large US commercial insurer has built its entire end-to-end multi-country comprehensive, business-critical application that manages claims, billing, and collection on Appian
One of the largest consumer goods companies in the world built a huge global application for financial management on Microsoft Power Platform

As we witness the adoption of low-code platforms garnering pace, a lot of myths and misunderstandings need to be cleared up about low code versus traditional development. Technology providers and service partners play a key role in helping their clients navigate the abundant options to orchestrate a carefully crafted low-code strategy and select the best low-code platforms.

At Everest Group, we are closely tracking the low-code market. For more insights, see our compendium report on various platform providers, the state of the low-code market report shedding light on the enterprise adoption journey, and a PEAK Matrix assessment comparing 14 leading players in the low-code market.

To share your thoughts and discuss our low-code market research, please reach out to [email protected], [email protected] or [email protected].

You can also attend our webinar, Building Successful Digital Product Engineering Businesses, to explore how enterprises are investing in next-generation technologies and talent and the most relevant skillsets for digital product engineering initiatives.

Announcing our inaugural conference: Everest Group Engage, The Pragmatic Edge: Designing Your Future. Learn more.

Category: Automation