A recent IDC survey revealed that 62% of IT and business leaders believe their organizations will expand resiliency plans in 2021 and 2022 to support unique requirements of the pandemic. But what does that mean exactly? Traditionally, resiliency has been framed in terms of responding to business disruptions and restoring operations in a timely fashion. However, this definition of resiliency is no longer enough - it's not enough to simply respond or restore. Digital resiliency shifts the focus from responding reactively to adapting and moving forward proactively.

While most AI in use today can be classified as early-stage advanced analytics, some enterprises have built large data science teams to apply machine learning and deep learning algorithms to business processes. Many of these enterprises have built the necessary support infrastructure to train these algorithms on large data sets, deploying the resulting AI models to production to generate business insights. However, many consumer and business consumption patterns changed dramatically in 2020, causing these advanced AI models to fail or behave erratically. Many of these models that have been trained to make predictions based on historical data have not been able to deal with the data anomalies created by disruptive business conditions and changing preferences. Companies using AI for insights had a hard time making use of existing models in production.

In the first of our series exploring the top 5 drivers of business disruption in 2017, we focus on the rise of Artificial Intelligence in our daily lives. High profile figures including Stephen Hawking and Elon Musk insisted that AI should be carefully contained and controlled, whilst Ray Kurzweil stated that we can, 'protect ourselves against rogue AI' by creating safeguards. Despite the negative press, the last 12 months has seen a huge increase in investment in AI. Since 2013, funding has tripled. This relentless expansion led tech giants Facebook, Google, Microsoft, Amazon and IBM to create a partnership at the end of the year, supposedly to hash out ethical concerns.