A Framework for Enterprise Artificial Intelligence Adoption

June 25, 2019

Artificial Intelligence (AI) is no longer a technology of the future – it’s recent popularity and the prevalence of machine learning makes the adoption and implementation of AI capabilities possible. But how can your organization adopt AI in a meaningful way, at the enterprise level, to achieve measurable results? This white paper demonstrates our framework to help organizations adopt and implement AI pilots to solve complex business problems and data challenges that require sophisticated techniques.

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Testing Software

Testing Software has worked closely as an outsourcing service with the development teams of different software development companies over the past five years. Testing Software has been using formal processes for ‘test plan’ creation and execution which has improved their quality of products and services by implementing the best testing practices into their software life cycle.

OTHER WHITEPAPERS
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Powering Contact Center Transformation by using Intel AI

whitePaper | September 23, 2022

According to the research published by Microsoft3 on Global Customer Service, 58% of customers feel the importance of Customer Experience (CX), and 61% stopped doing business with a brand due to poor CX and go for different brands.

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Scaling AI inManufacturing Operations:A Practitioners’ Perspective

whitePaper | January 8, 2020

AI in manufacturing is a game-changer. It has the potential to transform performance across the breadth and depth of manufacturing operations. However, the massive potential of this new Industrial 4.0 era will only be realized if manufacturers really focus their efforts on where AI can add most value and then drive the solutions to scale.

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HFS Enterprise AI Services Top 10

whitePaper | January 12, 2020

“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”

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Modern IT Management With AIOps

whitePaper | September 13, 2022

Companies are going digital, whether their IT infrastructure is ready or not. Digital transformation initiatives like migrating to cloud promise speed, adaptability and reduced costs to effectively respond to today’s real-time, customer-focused world.

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Implementing AI in business challenges and resource

whitePaper | November 10, 2019

Large enterprises need to implement AI solutions quickly and efficiently, but many don’t have the right people, process and technology. Firms can accelerate progress to AI maturity through use of a robust workbench, an operating model built on a data science-led pyramid of skills, and pre-built solutions when data complexity and talent scarcity are too big a challenge.

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Forrester Pulse: The State of Channel Partner Incentives 2020

whitePaper | July 21, 2020

Back in 2016, the most popular app download on Christmas Day was Fitbit, dominating Apple’s App Store. The rapid adoption of Fitbit and other wearable fitness trackers has underpinnings in psychological motivation theories. Realtime data monitoring provides a powerful incentive that is capable of changing human behavior. Since 2016, the wearable technology market has continued to evolve, including the acquisition of Fitbit by Google, which was announced in November 2019.

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Spotlight

Testing Software

Testing Software has worked closely as an outsourcing service with the development teams of different software development companies over the past five years. Testing Software has been using formal processes for ‘test plan’ creation and execution which has improved their quality of products and services by implementing the best testing practices into their software life cycle.

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