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November 28, 2018
The AI-powered enterprise is a workplace revolution
By: Arnab Chakraborty and Kevin Ichhpurani

A quarter-century into the digital revolution, it’s a truism that “data is the new oil.” Few understand the real implications of that statement, however, nor how much data is replicating the story of oil: From an important adjunct to business, data is increasingly steering business, and likely creating a new class of winners and losers.

Initially the petroleum “industry” was kerosene, a new source of lighting to replace increasingly scarce and expensive whale oil. As people realized that oil was a dense, portable and useful energy source, it was refined to many more uses, including diesel power generation, home heating oil, gasoline for cars and small engines, specialty lubricants, and much more. Then followed petrochemicals, a revolution everywhere from agriculture to apparel. Companies that failed to see the future that was being created were relegated to the past.

Digital data appears to be on its own track of increasing utility, growth, and transformational application. Initially used as a cheaper way to directly record transactions and media, organizations then invested in data warehouses, seeking better ways to store and gain insight about transactional data about customers, suppliers and so on.

The rise of new data sources, whether from online information and commerce, mobility, sensors, or social media, has led to an explosion of recorded data, in particular the unstructured data that captures more of human and natural experience.

Coupled with vastly cheaper cloud-based computing and better algorithms, ambitious companies are now using data analytics and Artificial Intelligence on these digital resources to realize dramatic productivity gains and create new business. To return to the oil analogy, the cloud is the great refinery, cheaply gathering, refining, and distributing at scale.

Companies using cloud-based data and AI increasingly make it the center of their growth strategies. They understand that this new asset is almost a new industrial process, and it must be looked at very differently to be fully effective. Why?

Once you have a view of the data inside and outside the organization, you create a new level of empowerment for your people and for your business. That comes from using data to create insights and take actions that are meaningful, intelligent and personalized and, as such, deliver significant business outcomes.

That’s the whole concept of the intelligent enterprise: how organizations can harness the new capabilities that are emerging through AI, analytics and automation (what Accenture calls “applied intelligence”) and use them to make sense of all the data that they have access to today.

Like all revolutionary opportunities, there are challenges. Chiefly, how to comprehend the meaning behind all this data and get the signals from it that help decision making across multiple areas, including customer engagement, marketing and the supply chain? How to act in ways that maximize business impact? How best to cope with other effects of the AI revolution, like customers that expect personalized attention at scale, but don’t want to feel surveilled?

The answer is to determine actions that are less rigid and more flexible than in the past, while creating systems that learn from every interaction, making smarter and more impactful decisions. In other words, a workforce once defined as rigidly as a factory system must become as fluid and adaptive as an advanced cloud computing system.

This is where the Accenture Google Cloud Business Group (AGBG) is so powerful. Accenture’s deep experience working with thousands of companies worldwide on some of their toughest problems is joined by Google’s mastery of data science and M.L., along with a sophisticated cloud computing system that daily serves billions of consumers and thousands of enterprises. Together, we enable any type of organization on its journey to become an intelligent enterprise.

At a top level, Accenture helps to shape the AI transformation journey, with the power of Google’s technology stack to speed insight and drive transformation. By scaling solutions to an unprecedented level, organizations can expect to swiftly move beyond pilots to enterprise-wide innovation. And it’s this scale play that’s becoming the differentiator for the intelligent enterprise.

The Accenture Google Cloud Business Group #AGBG helps to shape the AI transformation journey, with the power of @GoogleCloud’s technology stack to speed insight and drive transformation.

 

 
 

The new enterprise dynamic functions based on self-adapting -improving teams and technologies. As a true data-native culture, learning and information sharing are highly valued. Third, and crucially, there are new responsibilities, including how to embed responsible AI into the enterprise. Throughout is the power of human/machine interaction, enabling people to achieve more.

The AGBG draws from the extensive learning at our respective companies. To take just a couple of examples, Accenture’s invoice management operations processes over 70 million invoices a year for around 2,000 clients. Once a hugely manual process of authenticating, managing and validating, we’ve used Google Cloud and its AI to completely reimagine the process, with dramatic savings in cost and time.

Google’s own AI experience extends from smart replies in email to photo sharing, to the management of energy in its data centers—in all, 7500 unique project directories using AI more than a decade of its internal AI work is now offered as easy to use products and services.

Then there is the work of transformation. Over the past couple of years, Accenture has been providing precision agriculture services with AI at the heart, using our abilities as a data native to help the client interpret drone images of agricultural farmland to assess crop conditions that would not be visible on the ground. We’re also using IoT devices to monitor soil chemical composition and weather information, and triangulating all that in the cloud with machine learning and machine vision to deliver predictive recommendations to farmers on their mobiles.

So, what should organizations be doing to realize the potential of the intelligent enterprise? That’s what we’ll be looking at in the next blogs in this series, focusing on what the intelligent enterprise looks like in different industries—starting with how retail companies can embrace the intelligent enterprise to drive profitable revenues and hyper-relevance.

Thanks for reading.

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