Collaborative AI Will Transform Business and Society
Building value-creating and socially-beneficial AI solutions is not an easy task. Individuals, organizations, and governments are overwhelmed by a large number of questions and unknowns.
Let us dig deeper into what keeps AI from full-scale adoption.
In a study called “The Future of Employment: How Susceptible Are Jobs to computerization?”, Carl Benedikt Frey and Michael A. Osborne of Oxford University concluded that up to 47 percent of U.S. jobs risk being automated by 2050.
It is true that AI will automate a large chunk of jobs. However, it is also true that it is and will continue creating many new jobs.
These new jobs will require updated skill-sets and the only way to keep up and stay relevant in the job market is to befriend with continues learning.
Earlier this year, I interviewed Martin Ford, Futurist and New York Times bestselling author about the threat of job automation and inequality. Martin points out that,
I do think it’s absolutely true that themost important skillanyone can learn for this future that we’re facing is how to keep learning, how to adapt, and how to do that very effectively and with great enjoyment.
The impact of AI on inequality, job automation, and skills of the future.
And this social glue is essential to unleash the full potential of AI and solve meaningful problems in business and society. Technology that is not been used has no value and AI relies on customers and users that feed it with constant data.
One reason is people still focus on doomsday scenarios, like killer robots and massive job automation. In a recent global customer survey released by Pegasystems Inc., about 25% of respondents worried about robots taking over the world. In addition, data privacy concerns and a lack of understanding of what the AI is doing with the data result in low adoption rates.
Not exactly — High-Quality Data is the new oil.
Getting access to user and customer data is a difficult task due to previously mentioned trust-issues. But even if an organization sits on a huge amount of data, this does not yield a competitive advantage immediately.
Data governance, data cleaning, and the difficulties of integrating multiple datasets remain a big challenge to increase the quality and create value.
Another big challenge is the skill gap. A recent survey by EY has shown that 48% of current challenges in Europe with new technology are due to a lack of people. Organizations respond through training their teams or outsourcing development. However, even the big tech giants have a hard to keep up with the progress and related talent needs.
You might be familiar with this. In many organizations, business executives and the IT department speak different languages.
