Insight

A whole-brained approach to scaling intelligent automation

The prevailing approach to intelligent automation is IT-Led

Brad Fisher

Brad Fisher

Partner, Data & Analytics Lead, KPMG US

+1 212-909-5498

Cliff  Justice

Cliff Justice

Principal, Innovation & Enterprise Solutions, KPMG US

+1 713-319-2781


A joint survey from KPMG and HFS Research shows that just one­fifth of organizations have created integrated IT and business leadership teams to grapple with IA strategy and deployment.

The motivation is there; the money is there. But the optimism and aspiration to scale as fast as possible is at odds with the reality of executing IA effectively across the breadth of the enterprise.

17%

 

Only 17% of 600 executives surveyed say they have scaled their efforts around IA.


 

View the full infographic here


What does Whole-Brained Mean?

It’s the blend of different talents and ways of thinking—left­brained and right­ brained—into centers of excellence with perspectives and expertise that will create the right business rationalization, measurement, and incentive systems for scale of intelligent automation. It’s melding business and IT into one team with a 360° vision.

 

The C­suite needs to lead the way and make bold decisions on scaling functions across business units—and organizations must have the right in­ house talent to develop and benefit from the transformation.

According to Brad Fisher, Global Leader, KPMG Lighthouse, Center of Excellence for Data, Analytics, and AI, skills that are not prominent in the corporate world—linguists, for example, and psychologists and an assortment of right­brained people with humanities and liberal arts training—are already arriving across business units and different levels. Many of the new roles will be focused on managing AI and automation.
 


The top five AI jobs that companies need if they are to effectively build and scale their capabilities:


AI architect


The AI visionary


Measures and sustains performance of evolving models


Focuses on optimizing the role of humans in an increasingly automated world

 

 


AI project manager


Ensures that disparate teams are aligned around strategic goals


Monitors solutions to be sure they are successfully implemented


Works with teams to help optimize human-machine interactions

 

 


AI ethicist


The chief trust officer


Leverages technology to be built as unbiased forces for good


Focuses on transparency and explainability across departments

 

 


Data scientist


Data cleaning experts


Designs and applies the appropriate algorithms


Gleans meaningful insights from data

 

 


Software engineer


Takes AI from pilot phase to scalable deployment


Brings AI into production


Blends business acumen with a deep understanding of how AI works

 

Many businesses struggling to move beyond experimentation with AI haven’t planned for the people and the change elements these technology disruptions bring. They’re obsessed with the technology itself, and they forget that the only way they will realize benefits is by focusing on the people. It’s all about the people.
-Brad Fisher, Global Leader, KPMG Lighthouse, Center of Excellence for Data, Analytics, and AI

Build a critical mass of skills

Successful transformation can’t happen without ideas that have the space to percolate. Businesses need a melting pot of minds and the technologies to go with it. The left-brained and the right-brained talent in both business and IT will inspire and realize the strategy set in place by C-level leaders---and they’ll spin off disruptive ideas.

With the right skillsets in place, scaled across business functions, talent and tech will feed off each other across different areas of the business.

Learn more