Embrace AI-powered tools to remain relevant

It took businesses only 10 years to begin adapting artificial intelligence.

The first iteration of these tools used insights garnered from big data. Soon after, applications used machine learning to leverage the data in new ways, from powering location-based services to predicting customer service needs. Future-proof workers must learn to embrace AI-powered tools to adapt to a changing world.

From Big Data to Machine Learning in 10 Years

A McKinsey Global Institute (MGI) study published in 2011 described big data as “the next frontier for innovation, competition, and productivity,” highlighting multibillion-dollar growth in various sectors from implementing big-data techniques. Five years later, they followed up with a report that found that most business sectors were still not capturing the total value of big data. But there were some winners. U.S. retail and location-based services captured up to 40% and 60% of their data value, respectively.

In 2021, one of the most successful implementations of location-based data is ridesharing. The $85 billion industry will more than double by 2026. But advances in big data — as predicted in McKinsey’s follow-up report — have started shaking up other industries as well.

The Next Ten Years

So as our society becomes more data-driven, workers must learn to embrace each new wave of tools to remain relevant. As this publication matures, we will update the list with links to industry-specific articles describing existing tools and how workers can use those tools to improve their performance.

Industries with Big-Data Tools

• Customer Service
• Marketing
• Business Development
• Sales
• Medical Records
• Supply Chains.

Takeaways

1. New tools using machine learning will change the way we work
2. These tools use consensus from big data to improve outcomes
3. Workers should learn to use these tools to enhance their performance and stay relevant.