American Association for Physician Leadership

Problem Solving

Taking a Systems Approach to Adopting AI

Bhaskar Ghosh | Paul R. Daugherty | H. James Wilson | Adam Burden

December 9, 2020


Summary:

Today, some 80 percent of large companies have adopted machine learning and other forms of artificial intelligence in their core business. Five years ago, the figure was less than 10 percent. Nevertheless, the majority of companies still use AI tools as point solutions — discrete applications, isolated from the wider enterprise information technology architecture, according to our recent analysis of AI practices at more than 8,300 global companies.





Today, some 80 percent of large companies have adopted machine learning and other forms of artificial intelligence in their core business. Five years ago, the figure was less than 10 percent. Nevertheless, the majority of companies still use AI tools as point solutions — discrete applications, isolated from the wider enterprise information technology architecture, according to our recent analysis of AI practices at more than 8,300 global companies.

To scale the benefits of AI innovations, those companies need to stop thinking of AI tools and applications — such as natural language processing or computer vision — as stand-alone solutions. Otherwise, the opportunity cost could be as large as 41 percent of revenue by 2023. By comparison, leading companies that see AI as components of next-generation enterprise IT systems stand to grow revenues by as much as one-third over the next five years.

Companies building future systems are harnessing vast amounts of data, ubiquitous computing power and complementary technologies like cloud, data lakes, 3D printing, the Internet of Things and advanced workforce reskilling platforms. They are implementing AI in a systemic way that anticipates change for growth tomorrow. Here’s how your company can do the same:

REIMAGINE THE “IT STACK” FOR THE AGE OF AI. The conventional IT stack — spanning applications, data and infrastructure — has reached its practical limit. It wasn’t built for today’s complex, ever-changing world containing billions of devices, petabytes of data and decentralized AI applications scaling for millions of users. Moreover, the conventional computer processing chip is now stretched beyond capacity due to the exponential growth of AI.

Leading companies are starting to reimagine their IT stacks as boundaryless systems of complex machine, employee, consumer, partner and competitor interconnections. Cloud-enabled AI with its almost limitless power and elasticity is a mandatory foundation for boundaryless systems.

DESIGN FOR AN ADAPTABLE IT ARCHITECTURE. As each company’s portfolio of systems and partnerships grows, traditional architectures simply can’t keep pace with the sheer scale of business and technology connections. In their place, adaptable, dynamic architectures, including microservices — simple, discrete services that enable IT modularity — and serverless architectures are fostering new levels of organizational agility and scale.

Whether it’s virtual agents, natural language processing, machine learning, advanced analytics or other forms of AI, companies have a host of opportunities to transform the way they do business once their architectures make AI an integral part of the transaction flow. By finding a responsible, transparent balance between human and machine intelligence, and combining it with more basic forms of robotic process automation, adaptable systems can create value in ways that were previously impossible.

DESIGN SYSTEMS FOR HUMANS, BY HUMANS. The leading companies in our research recognize that AI now allows them to build systems that talk, listen, see and understand much the way we do. They know that tomorrow’s advantage will go to those who design systems that adjust to people — not those who continue to expect people to adjust to systems.

As systems evolve, so must the IT workforce. Companies will need multidisciplinary talent that can bridge infrastructure, development tools, programming languages, AI and machine learning. They’ll also need to combine human talent with a growing army of smart machines to create entirely new kinds of hybrid IT roles.

Copyright 2019 Harvard Business School Publishing Corp. Distributed by The New York Times Syndicate.


Bhaskar Ghosh

Bhaskar Ghosh is Accenture’s Chief Strategy Officer and a member of the firm’s Global Management Committee. He is a co-author of The Automation Advantage: Embrace the Future of Productivity and Improve Speed, Quality, and Customer Experience Through AI  (McGraw Hill, 2021).


Paul R. Daugherty

Paul R. Daugherty is Accenture’s group chief executive – technology and CTO. He is a coauthor of Radically Human: How New Technology Is Transforming Business and Shaping Our Future (Harvard Business Review Press, 2022) and Human + Machine: Reimagining Work in the Age of AI (Harvard Business Review Press, 2018).


H. James Wilson

H. James Wilson is the global managing director of thought leadership & technology research at Accenture. He coauthored multiple books including Radically Human: How New Technology Is Transforming Business and Shaping Our Future (Harvard Business Review Press, 2022) and Human + Machine: Reimagining Work in the Age of AI (Harvard Business Review Press, 2018).


Adam Burden

Adam Burden is Accenture’s chief software engineer and leads the Intelligent Software Engineering Services practice. Follow him on Twitter @adampburden .

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