The promise of AI has teased us for decades, yet only a brave few have attempted to convert the promise of machine intelligence into reality.
So what’s different today? After 50-plus years of incubation, AI capabilities have finally reached a critical mass.
A surge in the scope and scale of major research and pilot initiatives
Advancements in infrastructure, particularly compute processing power, which have improved speed, data availability and scale at reduced cost
Massive investments by key players, such as Google, Amazon, Microsoft and Facebook
Intelligent automation enables businesses to harness AI capabilities NOW.
In our recent study, we learned that nearly all of the respondents regard AI, which includes big data/analytics, as the top driver of business change between now and 2018.
A new economy—a digital economy—is emerging from the red hot furnace of technological innovation. An economy based on platforms and algorithms and “things” and “bots” is taking shape and in the process generating huge new money from ideas that represent the future.view pdf
As the digital data that surrounds us grows exponentially, it will power advanced forms of artificial intelligence that, over time, will augment human capabilities to make us smarter, more productive and effective in our personal and professional lives.view pdf
As we move toward an increasingly digital future, the ability to blend the virtual with the physical world is not only an accepted norm, but has utilitarian applications. A case in point is holographic technology, which is on the cusp of transforming business in new and heretofore unimagined ways.view pdf
Simply stated, AI enables machines to reason and perform tasks in ways that humans do. By combining smart algorithms with automation software,A new age machines can find answers to business challenges with heretofore unrealized speed and precision that augment and extend human capabilities.
AI capabilities encompass everything from personalized, real-time customer interactions (i.e., conversational AI) to persistent operations, freedom from error-prone, repetitive tasks and virtual predictive and diagnostic applications. We see AI evolving, from today’s systems that “do,” to tomorrow’s systems that “think,” “learn” and, ultimately, “adapt.”
By embedding AI and the Internet of Things into their enterprise applications, consumer-facing organizations can cultivate lasting and profitable customer relationships with hyper-personalized offers and services that deliver on the promise of digital.
Applied AI is solving both social and business problems: everything from how we’re educated, fed, transported, insured, and cared for — to what we buy, where we do business, and who we choose to trust. It’s spurring new business models that are generating remarkable growth and profitability — and can improve the top line to increase revenue, as well as the bottom line to reduce costs.
Self-driving cars, on a large scale, are many years away. But how, in the meantime, can we help solve the problem of car accidents? With 90% of vehicle crashes the result of human error, the potentially larger, and more immediate impact… Is where Applied AI enhances the driver’s ability to perform, and helps protect both him and those around him.
When it comes to potential floods, AI is enhancing our lives, with economic benefits. There’s nothing artificial about that intelligent, next-generation forecasting system.
Cognizant is helping a major consumer finance company that provides personal and auto loans by applying AI to their customer interactions. The technology evaluates complaints with a goal of improving the customer help desk experience. Think of it as intelligent software that detects what I’m angry about based on what and how customers say.
Businesses will benefit from making the most of the AI opportunities positioned between systems of record and systems of engagement—leveraging intelligent automation through a do, think and learn framework.
The progression from “do, think, learn” and ultimately “adapt” will continue to evolve and play an important role in the automated business ecosystem.
Some examples include:
Some examples include:
Some examples include:
Ultimately, this category will evolve to “systems that adapt,” enabling a rich partnership between humans and software bots.
As digital agents increasingly represent their human owners, online platform providers must upgrade their technology infrastructure to accommodate new ways of product search and discovery as well as rethink their business models to stay relevant in the impending autonomous business era.
By seeing intelligent automation through a ‘do, think, learn’ and ultimately ‘adapt’ framework, businesses can begin bene ting from this powerful set of technologies now.
Chatbots don’t need to impersonate humans; to boost business outcomes and deliver superior experiences, they must quickly deliver responses that speak directly to individual human needs and continuously learn so they can apply meaningful responses to these unique requirements over time.
The proliferation of household data from sensors and smart devices, plus advances in data analytics, present compelling opportunities for property and casualty insurers to reduce and mitigate losses, improve underwriting, enhance the personalization of products and services, and enrich customers’ digital experience.
Cognitive computing is emerging from the shadows and rapidly impacting our professional and personal lives, illuminating a future where humans and machines will coexist to enable businesses to make faster and more informed decisions, improve operational performance and enhance organizational productivity.
By correlating analytics data across the IT lifecycle, enterprises can design and implement a level of testing that improves predictive mechanisms and anticipates ever-changing business needs. Big data analytics and AI, which create what we call “systems of intelligence,” are the engines powering digital transformation.
At digitally-savvy companies, chatbots are already deeply involved in customer-facing interactions. Customers like them because they can get their questions and concerns addressed quickly without having to first download an app. Companies like them for their potential cost savings, better customer service and retention, and ability to cross sell — all without having to invest in yet another app.
Leadership behaviours forged over the last century clearly need updating for the digital age. Our recent research reveals three key roles for leadership as data, AI, algorithms and the science of “meaning making” dominate business for the foreseeable future.
Kyle Brown - September 25, 2017
Prasad Chintamaneni - June 26, 2017
Raja Renganathan - May 3, 2017