Amidst the great debate over whether artificial intelligence (AI) will steal human jobs, there has been little discussion of how it will transform corporate cultures in new and unprecedented ways.
In the era of automation, the most successful businesses will be those that redesign their working environment and workforce around harnessing the cognitive capabilities of machines in the same way that Victorian-era industry was redesigned around harnessing the physical capabilities of steam and mechanization. AI will demand a radical culture shift because it alters the relationship between machines and humans, changing machines from passive receivers of commands into informed, sentient collaborators. In doing so, it will also transform the skills that organizations seek to find and foster in human workers. Fundamentally, AI will require human workspaces to be built around powering processes, products and services with data in the same way the Machine Age saw society reconfigured around powering machines with electricity.
Even technology giants will lose out in the modern data economy if they do not understand the need to build an "AI culture." Apple analyst Gene Munster explained that the relative failure of Siri compared to rivals such as Amazon’s Alexa is fundamentally because "artificial intelligence is not in Apple’s DNA." As a veteran of the hardware era, Apple’s corporate culture was built around commercializing physical products and the software applications that support them, whereas succeeding today requires a culture built around thinking "AI first." Apple also has a culture of privacy which clashes with the need to harvest and exploit the industrial quantities of data.
Breaking Down Business Silos
As data becomes the oil of the 21st century, every future company will either be an AI company or be overtaken by AI companies. The resulting imperative to create AI-friendly business practices will transform human roles and corporate cultures in myriad ways.
If they are to truly realize the benefits of AI, organizations will first have to build their business practices around harnessing data from across the business, replacing a culture of secrecy with one of transparency. This is because algorithms must be designed and trained with information and input from every company department, from the legal team to business and operations. Corporate data can no longer be sealed in traditional silos. Instead, a company will have to become a closely interconnected organism with information continuously shared among all the individual cells.
Consequently, many traditional job profiles will now require an understanding of how to effectively interact with AI, and of its capabilities and limitations. This is because successful use of AI demands that both the algorithm and the data are tailored to each task by the relevant human subject matter experts. Not only will businesses have to be redesigned around AI, but AI will have to be designed around each business, taking into account the specific context and constraints of the tasks it will perform. Rather than an epidemiologist scouring public health records to identify Ebola hotspots, they will instead supervise virtual machine assistants to do this. Consequently, epidemiologists will need to know how to retrain their AI assistant to operate within real-world parameters and tag the datasets that are relevant to Ebola and those that are not until the algorithm learns to distinguish between the two.
AI is a business tool and workers will need to be trained in how to interact with and use it expertly in the same way that manual workers had to be trained to use machine tools during the Industrial Revolution.
The Rise Of The Creatives
As well as transforming the job functions of machines, AI will begin to alter the job specifications of human workers, which will begin to be built around attributes that cannot be easily replicated by machines, such as creative outside-the-box thinking and interpersonal skills.
Successful companies will foster and encourage more creativity in their workforce by harnessing the analytical and predictive power of AI to test and augment new ideas. A company could brainstorm a new product idea and an algorithm could instantly scour millions of market research reports to predict how it would perform in a particular market.
AI-assisted modeling and analysis have the potential to dramatically reduce the cost and risk of creating new innovations, helping transform companies into vast digitally-assisted test beds for human ingenuity.
Redefining What It Means To Be 'Smart'
Soft skills will attain greater significance in the age of AI. For example, in the health care profession, AI will automate logical tasks such as analyzing patient symptoms, freeing doctors to spend more time talking to patients and designing personalized treatment plans molded to their life circumstances.
In this way, the job of a doctor and the culture of a hospital will evolve into one built around emotive skills. Machines may outperform humans at certain clearly-defined logical tasks but humans are superior at emotional intelligence -- empathizing, interacting with and influencing other humans. Thus AI will replace humans on individual tasks, rather than entire jobs.
As a result, AI will transform the candidate profile that recruiters in many industries are looking for.
This will revolutionize everything from hiring practices to how organizations measure success by redefining what it means to be smart. In the future, candidate aptitude and workforce performance will be measured in terms of quality of thought and human interaction rather than just knowledge and technical ability. Interviews will assess empathy, emotional engagement and lateral thinking. When once highly prized human skills can be outsourced to machines, employers will change the skills they prize in humans.
In the new economy, successful businesses will be those that design their business processes around harnessing data from every department to fuel AI, just as industry was once rebuilt around harnessing electrical power from other sources to fuel machinery.
Written for Forbes by Matt Jones, Lead Analytics Strategist at Tessella.