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Robotic Process Automation (RPA) is a key component of the automation ecosystem and has been a rapidly growing software product category, making it an interesting space for potential acquisitions for a while now. While acquisitions in the RPA market have been happening over the last several years, three major RPA acquisitions have taken place in quick succession over the past few months: Microsoft’s acquisition of Softomotive in May, IBM’s acquisition of WDG Automation in July, and Hyland’s acquisition of Another Monday in August.
These acquisitions highlight a broader trend in which smaller RPA vendors are being acquired by different categories of larger technology market players:
Recent RPA acquisitions timeline:
The RPA product market has grown rapidly over the past few years, rising to about US$ 1.2 billion in software license revenues in 2019. The market seems to be consolidating, with some of the larger players continuing to gain market share. As in any such maturing market, mergers and acquisitions are a natural outcome. However, we see multiple factors in the current environment leading to this frenetic uptick in RPA acquisitions:
Acquirers’ perspective – In addition to RPA being a fast-growing market, new category acquirers – meaning big tech product vendors, service providers, and larger automation vendors – see potential in merging RPA capabilities with their own core products to provide more unified automation solutions. These new entrants will be able to build pre-packaged solutions combining RPA with other existing capabilities at lower cost. COVID-19 has created an urgency for broader automation in enterprises, and the ability to offer packaged solutions that provide a quick ROI can be a game-changer in this scenario. Additionally, the adverse impact of the pandemic on the RPA vendors’ revenues, which may have dropped their valuations down to more realistic levels, is making them more attractive for the acquiring parties.
Sellers’ perspective – There is now a general realization in the market that RPA alone is not going to cut it. RPA is the connective tissue, but you still need the larger services, big tech/Systems-of-Record and/or intelligent automation ecosystem to complete the picture. RPA vendors that don’t have the ability to invest in building this ecosystem will be looking to be acquired by larger players that offer some of these complementary capabilities. In addition, investor money may no longer be flowing as freely in the current environment, meaning that some RPA vendors will be looking for an exit.
The RPA and broader intelligent automation space will continue to evolve quickly, accelerated by the predictable rise in demand for automation and the changes brought on by the new entrants in the space. We expect to see the following trends in the short term:
There are several open questions on how some of these dynamics will play out over time. You can expect a battle for the soul (and control) of automation, with implications for all stakeholders in the automation ecosystem. Questions remain:
Only time will tell how this all plays out.
But in the meantime, we’d love to hear your thoughts. Please share them with us at [email protected], [email protected], and [email protected].
OpenAI recently released the third generation of Generative Pretrained Transformer or GPT-3, the largest neuro-linguistic programming (NLP) model ever built. It’s fundamentally a language model, a machine learning model that can look at part of a sentence and predict the next word. It’s been pre-trained on 175 billion parameters in an unsupervised manner and can be further fine-tuned to perform specific tasks. OpenAI is an AI research organization founded in 2015 by Elon Musk, Sam Altman, and other luminaries. It describes its mission as: to discover and enact the path to safe Artificial General Intelligence (AGI).
GPT-3 is breaking the internet
There’s been a lot of talk around the power, capabilities, and potential use cases of GPT-3 in the AI community. As the largest language model developed to date, it has the potential to advance AI as a domain. People have developed all sorts of uses – from mimicking Shakespeare, to writing prose, to designing web pages. It primarily stood out due to:
So, this seems nifty – what next?
In addition to the flurry of standard NLP use cases that have been in existence for a while, which GPT-3 has advanced drastically, GPT-3 also has the potential to intercept the more technical and creative domains, which will lead to the democratization of such skills by making these capabilities available to non-technical people and putting business users in control, primarily by:
GPT-3 is great, but we’re not in Space Odyssey yet
The massive language model is not without pitfalls. Its principal shortcoming is that, while it’s good with natural language tasks, is has no semantic understanding of the text. It is, by virtue of its training, just trying to complete a given sentence, no matter what the sentence means.
The second roadblock to mainstream adoption of the model is the fact that it’s riddled with societal biases in gender, race, and religion. This is because the model is trained on the internet, which brings its own set of challenges given the discourse around fake news and the post-truth world. Even OpenAI admits that its API models exhibit biases, and those can often be seen in the generated text. These biases need to be corrected before the model can be deployed in any real-world scenario.
These challenges certainly must be addressed before it can be deployed for actual, enterprise-grade use. That said, GPT-3 will potentially traverse the same trajectory that computer vision made at the start of the decade to eventually become ubiquitous in our lives.
What are your thoughts about GPT-3? Please share with us at [email protected] and [email protected].
Companies currently invest a lot of money in target markets to generate potential customers’ interest in products and services. But after they achieve a sale, they often frustrate customers by not providing effective customer service support. A poor customer experience can erode the company’s brand and reputation and destroy the company’s opportunities to increase revenue through new purchases by those existing customers. Obviously, these are significant problems, especially in today’s highly competitive environment with customers’ quick pace in buying decisions. Let us now explore the solution.
A sustained focus on digital, agility, and advanced technologies is likely to prepare enterprises for the future, especially following COVID-19. Many enterprise leaders consider IT infrastructure to be the bedrock of business transformation at a time when the service delivery model has become more virtual and cloud based. This reality presents an opportunity for GBS organizations that deliver IT infrastructure services to rethink their long-term strategies to enhance their capabilities, thereby strengthening their value propositions for their enterprises.
GBS setups with strong IT infra capabilities can lead enterprise transformation
Over the past few years, several GBS organizations have built and strengthened capabilities across a wide range of IT infrastructure services. Best-in-class GBS setups have achieved significant scale and penetration for IT infrastructure delivery and now support a wide range of functions – such as cloud migration and transformation, desktop support and virtualization, and service desk – with high maturity. In fact, some centers have scaled as high as 250-300 Full Time Equivalents (FTEs) and 35-45% penetration.
At the same time, these organizations are fraught with legacy issues that need to be addressed to unlock full value. Our research reveals that most enterprises believe that their GBS’ current IT infrastructure services model is not ready to cater to the digital capabilities necessary for targeted transformation. Only GBS organizations that evolve and strengthen their IT infrastructure capabilities will be well positioned to extend their support to newer or more enhanced IT infrastructure services delivery.
The need for an IT infrastructure revolution and what it will take
The push to transform IT infrastructure in GBS setups should be driven by a business-centric approach to global business services. To enable this shift, GBS organizations should consider a new model for IT infrastructure that focuses on improving business metrics instead of pre-defined IT Service Line Agreements (SLA) and Total Cost of Operations (TCO) management. IT infrastructure must be able to support changes ushered in by rapid device proliferation, technology disruptions, business expansions, and escalating cost pressures post-COVID-19 to showcase sustained value.
To transition to this IT infrastructure state, GBS organizations must proactively start to identify skills that have a high likelihood of being replaced / becoming obsolete, as well as emerging skills. They must also prioritize emerging skills that have a higher reskilling/upskilling potential. These goals can be achieved through a comprehensive program that proactively builds capabilities in IT services delivery.
In the exhibit below, we highlight the shelf life of basic IT services skills by comparing the upskilling/reskilling potential of IT services skills with their expected extent of replacement.
Exhibit: Analysis of the shelf life of basic IT services skills
In the near future, GBS organizations should leverage Artificial Intelligence (AI), analytics, and automation to further revolutionize their IT capabilities. The end goal is to transition to a self-healing, self-configuring system that can dynamically and autonomously adapt to changing business needs, thereby creating an invisible IT infrastructure model. This invisible IT infrastructure will be highly secure, require minimal oversight, function across stacks, and continuously evolve with changing business needs. By leveraging an automation-, analytics-, and AI-led delivery of infrastructure, operations, and services management, GBS organizations can truly enable enterprises to make decisions based on business imperatives.
If you’d like to know more about the key business transformation trends for enterprises in IT infrastructure, do read our report Exploring the Enterprise Journey Towards “Invisible” IT Infrastructure or reach out to us at [email protected] or [email protected].
IVA market growth will accelerate post-pandemic as enterprises strive to overcome recession with focus on automation, customer experience
The global Intelligent Virtual Agent (IVA) market stood at US$300 million-US$350 million in 2019, exhibiting about 42% growth year on year, according to Everest Group. The firm projects a dip in demand in 2020 due to the COVID-19 pandemic but expects the IVA market to post strong growth going forward, achieving as much as a 70% compound annual growth rate (CAGR) through 2022. In fact, Everest Group has boosted this estimate by 13-22%, anticipating that enterprises will place greater emphasis on cost reduction and improving business continuity in the post-pandemic period.
IVA solutions are a key enabler of automation in the front office, currently being used primarily for customer support as well as IT and help desk functions due to their large volumes of repetitive queries. These functions account for more than 80% of the IVA market today. Banking, insurance, and telecom industries account for the highest adoption of IVA and continue to exhibit impressive growth, particularly given the maturity of contact centers within these industries.
Increasing sophistication and collaboration with complimentary artificial intelligence (AI) based technologies are driving IVA popularity in the market. Enterprises across industries and geographies are leveraging or plan to leverage IVA solutions for different use cases to reduce human involvement and improve customer experience (CX).
“IVA is still in the realm of early adoption today, but that is rapidly changing as enterprises realize what a tremendous opportunity they have to leverage this technology,” said Anil Vijayan, vice president of Everest Group. “IVA technology is continuously advancing and growing in sophistication well beyond rule-based chatbots. Today we see a higher level of maturity in intelligent IVA applications, which are being used for a variety of use cases including payment services account resolutions and employee onboarding, for instance. We’re also beginning to see IVA playing a key role in conversational AI ecosystems, where a collaborative set of tools—including IVA, AI, robotic process automation, learning and listening engines, analytics and more—is used to seamlessly integrate front and back office systems. Here, IVA supports more advanced use cases such as cross-selling and upselling, customer retention, and making personalized recommendations. We expect this evolution to continue, leading to reliable and delightful customer experiences while reducing human effort through automation.”
These findings are discussed in more detail in Everest Group’s recently published report “Conversing with AI – Intelligent Virtual Agents (IVA) State of the Market Report 2020.” The report includes a detailed analysis of the IVA market, including a market overview and adoption trends, solution characteristics, vendor landscape, barriers to IVA adoption and best practices, and the outlook for 2020-2021.
Evolution of the IVA Market
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About Everest Group
Everest Group is a consulting and research firm focused on strategic IT, business services, engineering services, and sourcing. Our clients include leading global enterprises, service providers, and investors. Through our research-informed insights and deep experience, we guide clients in their journeys to achieve heightened operational and financial performance, accelerated value delivery, and high-impact business outcomes. Details and in-depth content are available at http://www.everestgrp.com/.
As insurers cope with the impact of COVID-19 on multiple fronts, effective digital communication with their customers has become more important than ever. Transparent, relevant, and crisp customer communications are key differentiators. While insurers have historically relied on intermediaries to communicate with their customers, they have made significant movement toward direct-to-consumer communications; however, the pandemic has highlighted just how far they still have to go.
Insurers have to balance a wide variety of public-facing and back-office demands, challenging in any time, but especially so during a pandemic. On top of the ongoing work of claims intake and management, sales and distribution, new policy onboarding, business continuity, etc., insurers need to efficiently and effectively answer custom questions and solve problems, proactively communicate about pandemic-related initiatives (such as premium relaxations and rebates, relief programs, and flexibility around policy renewal) – essentially, support and service their policyholders in a time of great stress.
Insurers need to arm their agents with information and content, as well as a complete view of each customer, including content from a variety of sources and analytics to pull it all together and make sense of it. To do so, insurers need to collect and consolidate customer data from multiple sources, run AI-enabled analytics, and curate digital content assets for honest, empathetic, and relevant communication with customers. From there, they need to determine how to disseminate personalized content with an omnichannel approach to reach the customers in the ways best suited to their needs.
Digital experience is the key lever for insurers to pull to effectively communicate with clients and prospects, to offer the desired customer experience, and to meet the challenge posed by digital-native companies and InsurTechs. A successful digital experience strategy, driven by a fit-for-purpose product that can meet customer needs, impacts and enhances the entire customer journey, and is a strategic imperative for insurers. An effective digital experience platform can provide an omnichannel personalized experience to the end customer, offer a single view of the customer, innovate service delivery, and provide a smoother experience for agents.
At the center of the digital experience solution is the Digital Experience Platform (DXP). See Exhibit 1 for Everest Group’s vision of a DXP for insurers.
To orchestrate insurers’ digital content management needs, the DXP should offer
To meet customer expectations and maintain high levels of customer experience, the DXP needs to
To enable agents, brokers, and advisors to have meaningful customer interactions, the DXP must
To meet insurers’ technology needs, a DXP should offer
The DXPs that can curate superior customer experiences, enable both customers and agents, and provide digital enablers to drive business impact lead the pack in Everest Group’s assessment of DXP vendor landscape for insurance, illustrated in exhibit 2.
In our recently released report, Assessing Digital Experience Platforms in Insurance and Vendor Profiles 2020 – Building SUPER Insurance Experiences to Drive Differentiation and Growth, we take a closer look at digital experience trends in insurance and explore the impact of an effective digital experience strategy. The report includes a detailed analysis of 13 leading technology vendors on their DXPs’ capabilities and abilities to meet insurer needs.
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