With the advent of artificial intelligence (AI) and machine learning, we have entered the Fourth Industrial Revolution. Over the next few years, organizations that fail to adopt AI and machine learning technology should expect to be outcompeted by those that do.
What does AI adoption involve? There are three main elements: data, technology and people (otherwise known as culture or process). You may be surprised to learn that the most crucial of these is neither data nor technology. I believe that successful AI adoption is driven mainly by executives who lead a major culture change in their organization, changing the way employees think and operationalizing the technology to the benefit of the organization.
Not all organizations were born data- and model-driven enterprises, and those that aren’t must undergo a cultural transformation if they are to benefit from data science and AI technology. You may not be naturally drawn to technical language or technical innovation, but unfortunately, you can’t leave such a vital transition to those who are.
Why? Let’s examine what happens in many organizations that are attempting to lead the data-science Revolution.
Often, lower-level technical employees are charged with trying to make and lead this change. Intuitively, this makes sense. These are usually highly capable people who understand the technology and want to move their companies forward. They are certainly able to leverage the data around them using modeling techniques. The problem is that they don’t have the necessary funding or an executive sponsor ready and able to help them operationalize data science throughout the organization. They are not in a position to drive the business processes and the cultural change.
This is why the responsibility falls to executives such as yourself. You are responsible for keeping your company competitive.
If this sounds alarming, don’t worry. The truth is that large companies are ready to start leveraging machine intelligence. Yes, given the sheer size of these enterprises, the journey will be a long and intimidating one. Cultural transformation is no small matter in companies that employ between 60,000 and 2.3 million people worldwide.
Nonetheless, these companies have the data and technology infrastructure to make this transformation. The gap exists because their top executives and mid-tier management don’t yet know how to operationalize the process -- they don't know what tools they need and what playbook or strategy they should be following. Most executives and business leaders have heard a lot about machine learning and data science, but they still don’t know what this means in practical terms (i.e., how to prioritize their investments and build an environment where this initiative and their people can thrive). They need clear and actionable explanations.
The Data-Science Revolution Starts With You
As you can no doubt already tell, I’m a machine-intelligence enthusiast. In the past five years, I have trained many C-level executives at Fortune 100 and 200 companies and their international equivalents -- which have operated successfully for decades, employed thousands of people and generated billions of dollars every year -- on how to start the journey of transforming their organizations.
I particularly address top-level executives and business leaders at large corporations because I believe data science and machine intelligence are top-down initiatives. This transformation requires significant funding, large-scale cultural and operational change and senior-management leadership.
All of this must come from the top. The business leaders and executives responsible for setting strategy, bringing money to the table, and making cultural transformation happen must understand and support the initiative.
