Tag: automation

Deconstructing the Future of Work | In the News

Four-day weeks, on-demand pay, “rural” talent, digital workers… in recent times, we’ve heard these ideas accompanied by seemingly teleological questions about work as a construct.

The timing is understandable given the confluence of factors at play – the rise of digital, labor pyramid issues, and the after-effects of a global pandemic, including a desire for more meaning in work and convenience through remote work. After years of navel-gazing, society is finally waking up to the fact that our jobs, the way we do them, the time we spend, and the very fundamentals of the nature of work itself are perhaps incongruent with the world we now live in.

This realization opens up the very promising possibility of re-examining and perhaps reconstructing work for the new era. But, beyond the clarion call, what exactly does it entail, how do we understand the future of work, and how do we design for it? Fundamentally, we can break it down into three distinct components: the how, the where, and the who.

Read the full article on Business Reporter

Intelligent Automation in the UK Public Sector | In the News

COVID-19 required government departments to pull off a rapid shift to digital while at the same time managing a public health crisis. Many turned to robotic process automation (RPA) to quickly redesign their business processes and tackle the administrational backlogs that accumulated as workers were confined to their homes.

Anil Vijayan, Partner at Everest Group, says that governments’ hesitation to innovate has slowed IA adoption. “The idea of job losses, whether real or imagined, also prevents an aggressive push towards automation,” he said.

Read more in Tech Monitor

Best Low Code Development Platforms PEAK Matrix® Assessment 2022

Best Low Code Development Platforms

Low-code application development platforms are narrowing the gap between continuous business needs and the IT function’s limited bandwidth, especially after the pandemic. However, the industry faces an acute talent shortage, and there is a need to improve developer productivity. A subsequent rise in talent costs is also compelling organizations to cater to application development requirements internally, wherever possible, rather than looking out in the market.

Enterprises have just started using low-code solutions and successful adoption depends on selecting the right provider and platform for their needs, keeping in mind the trade-off between the cost and accompanying benefits.

Best Low Code Development Platforms: What is the Scope?

  • The assessment is based on Everest Group’s RFI process, interactions with leading low-code platform providers, client reference checks, and ongoing analysis of the low code development platform market
  • The assessment includes all industries and geographies

What is in this PEAK Matrix® Report:

This research presents detailed assessments of 14 platform providers featured on the Low-code Application Development Solutions PEAK Matrix® and categorizes them as Leaders, Major Contenders, and Aspirants based on their capabilities and offerings.

LEARN MORE ABOUT LOW-CODE APPLICATION DEVELOPMENT PLATFORMS

Our Thinking

5 Advanced Analytics and AI Market Trends
Market Insights™

5 Advanced Analytics and AI Market Trends

Analytics Offers Significant Opportunities Across Front-, Mid-, and Back-office
Market Insights™

Analytics Offers Significant Opportunities Across Front-, Mid-, and Back-office

Advanced Analytics is Increasingly Vital in Revenue Cycle Management Operations
Market Insights™

Advanced Analytics is Increasingly Vital in Revenue Cycle Management Operations

Comparing Traditional and Augmented Data Management Models
Market Insights™

Comparing Traditional and Augmented Data Management Models

What is the PEAK Matrix®?

The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.

LEARN MORE ABOUT TOP SERVICE PROVIDERS

Artificial Intelligence Service Providers PEAK Matrix® Assessment 2022

Top Artificial Intelligence Service Providers

Artificial Intelligence (AI) has become a crucial component in enterprises’ digital transformation journeys. In the past few years, enterprises have started adopting AI at a faster pace for better resilience, cost-effectiveness, and employee productivity. They also understand the importance of explainable and responsible AI adoption to create an inclusive, fair, and bias-free process.

To achieve these objectives, enterprises are reaching out to providers to help them navigate through their talent, capability, and data management challenges, while also ensuring a customer-sensitive and conscious AI adoption approach. Consequently, providers are increasing their investments to assist enterprises in gaining value from their AI initiatives.

DOWNLOAD THE FULL REPORT Artificial Intelligence (AI) Services PEAK Matrix® Assessment

Artificial Intelligence Service Providers: What is the Scope?

  • All industries and geographies
  • This assessment is based on Everest Group’s annual RFI process for the calendar year 2021, interactions with leading AI service providers, client reference checks, and an ongoing analysis of the AI services market

What is in this PEAK Matrix® Report:

In this research, we provide detailed profiles and assessments of 20 IT service providers featured on Everest Group’s AI Services PEAK Matrix®. Each profile provides a comprehensive picture of the provider’s service focus, key Intellectual Property (IP) / solutions, domain investments, and case studies.

LEARN MORE ABOUT Artificial Intelligence Service Providers

Our Thinking

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

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Building Web 3.0 Business for Clients: Opportunities for Strategy, Technology, and Consulting Providers

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How to Clear Up Industry Cloud Confusion and Choose the Right Solution

Challenges to AI-ML Model Development
Market Insights™

Challenges to AI/ML Model Development

What is the PEAK Matrix®?

The PEAK Matrix® provides an objective, data-driven assessment of service and technology providers based on their overall capability and market impact across different global services markets, classifying them into three categories: Leaders, Major Contenders, and Aspirants.

LEARN MORE ABOUT Top Service Providers

The Rise of Machine Learning Operations: How MLOps Can Become the Backbone of AI-enabled Enterprises | Blog

We’ve seen enterprises developing and employing multiple disparate AI use cases. But to become a truly AI-enabled enterprise, many standalone use cases need to be developed, deployed, and maintained to solve different challenges across the organization. Machine Learning Operations or MLOps offers this promise to seamlessly leverage the power of AI without hassle.

Everest Group is launching its MLOps Products PEAK® Matrix Assessment 2022 to gain a better understanding of the competitive service provider landscape. Discover how you can be part of the assessment.

Learn how to participate

With the rise in digitization, cloud, and internet of things (IoT) adoption, our world generates petabytes of data every day that enterprises want to mine to gain business insights, drive decisions, and transform operations.

Artificial Intelligence (AI) and Machine Learning (ML) insights can help enterprises gain a competitive edge but come with developmental and operational challenges. Machine Learning Operations (MLOps) can provide a solution. Let’s explore this more.

While tools for analyzing historical data to gain business insights have become well-adopted and easier to use, using this information to make predictions or judgment calls is a different ball game altogether.

Tools that can deliver these capabilities based on programming languages such as Python, SAS, and R are known as data science or Machine Learning (ML). Popular deep learning frameworks include Tensorflow, Jupyter, and PyTorch.

Over the past decade, these tools have gained traction and have emerged as attractive options to develop predictive use cases by leveraging vast amounts of data to assist employees in making decisions and delivering consistent outcomes. As a result, enterprises can scale processes without proportionately increasing employee headcount.

Machine Learning varies from traditional IT initiatives as it does not take a one-size-fits-all approach. Earlier data-scientist implementation teams operated in silos, worked on different business processes, and leveraged disparate development tools and deployment techniques with limited adherence to IT policies.

While the benefits promised are real, replicating them across geographies, functions, customer segments, and distribution channels, all with their own nuances, called for a customized approach across these categories.

This led to the development of a plethora of specialized models that individual business teams had to be kept informed of as well as significant infrastructure and deployment costs.

Advances in ML have since driven software providers to offer approaches to democratize model development, making it possible to now create custom ML models for different processes and contexts.

MLOps to the rescue

In today’s world, developing multiple models that serve different purposes is less challenging. Enterprises who want to successfully become AI-enabled and deploy AI at scale need to equip individual business teams with model deployment and monitoring capabilities.

As a result, software vendors have started offering a DevOps-style approach to centralize and support the deployment requirements of a vast number of ML models, with individual teams focusing only on developing models best suited to their requirements.

This new rising methodology called MLOps is a structured approach to scaling ML across organizations that brings together skills, techniques, and tools used in data engineering and machine learning.

What’s needed to make it work

Technical Capabilities Required for MLOps

MLOps assists enterprises in decoupling the development and operational aspects in an ML model’s lifecycle by bringing DevOps-like capabilities into operationalizing ML models. Technology vendors are offering MLOps to enterprises in the form of licensable software with the following capabilities:

  • Model deployment: In this important stage, the ability to deploy models on any infrastructure is important. Other features include storing an ML model in a containerized environment and options to scale compute resources
  • Model monitoring: Tracking the performance of models in production is complex and requires a carefully designed performance measurement matrix. As soon as models start showing signs of declining prediction accuracy, they are sent to the development team for review/retraining
  • Collaboration and platform management: MLOps solutions offer platform-related features such as security, access control, version control, and performance measurement to enhance reusability and collaboration among various stakeholders, including data engineers, data scientists, ML engineers, and central IT functions

Additionally, MLOps vendors offer support for multiple Integrated Development Environments (IDEs) to promote the democratization of the model development process.

While various vendors offer built-in ML development capabilities within their solutions, connectors are being developed and integrated to support a wide array of ML model file formats.

Additionally, the overall ML lifecycle management ecosystem is rapidly converging, with vendors developing end-to-end ML lifecycle capabilities, either in-house or through partner integrations.

MLOps can promote rapid innovation through robust machine learning lifecycle management, increase productivity, speed, and reliability, and reduce risk – making it a methodology to pay attention to.

Everest Group is launching its MLOps Products PEAK® Matrix Assessment 2022 to gain a better understanding of the competitive landscape. Technology providers can now participate and receive a platform assessment.

Learn how to participate

To share your thoughts on this topic, contact [email protected] and [email protected].

Request a briefing with our experts to discuss the 2022 key issues presented in our 12 days of insights.

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