Does Your Business Team Speak AI?
By: Randy Dean
Artificial intelligence (AI) and machine learning (ML) are important technologies that offer the promise of maximizing enterprise performance. Whether improving marketing outcomes, making supply chains more efficient, optimizing pricing or enhancing customer service, AI systems are being developed and deployed at a breathtaking rate.
With the development of these systems comes massive demand for technical expertise. Companies need data scientists who understand how to make use of these powerful technologies. But having skilled data scientists is really just the tip of the iceberg if enterprises are going to be successful with AI. In order to truly unlock the full potential of AI models, data scientists need business insight to create the best solutions, and business operators need to understand how to translate their requirements into questions that data science can answer.
The problem? What does your AI team really know about the business and what does your business team really know about AI?
In many cases, data scientists are new to an enterprise. They bring their understanding of AI technologies but little or no experience with the dynamics of the core business that may impact their model development and the effectiveness of their solutions.
Similarly, AI is new to many enterprises and their managers and executives. The business people who collaborate with data scientists are responsible for defining AI projects, providing budget, and proving ROI yet don’t have the required understanding of the science of AI and the metrics that truly measure success. They don’t know what is possible, what to expect, and where there may be pitfalls to beware. Managers need a practical understanding of AI/ML in order to organize and run these projects effectively and translate the business requirements into solutions that can be successful.
“A recent study from analytics database company Exasol 1, found that 65% of data teams have experienced employee resistance to the adoption of data-driven methods. This is primarily because employees and managers lack a fundamental understanding of data and the positive impact that data contributes.2
The answer is upskilling your entire team. While enterprises are primarily focusing on trying to find and/or create data science resources, they are not focusing enough effort making sure the whole organization is fluent in these critical technologies.
As a longtime provider of Upskill programs for the entire enterprise, we long ago recognized this critical element of success. We're helping enterprises develop their data science proficiency across the entire organization using advanced upskill programs that transform the existing workforce into AI specialists. We deliver custom, full-time, technical programs to create data scientists as well as self-guided and mentored programs for business people, product managers, and executives to learn the critical information they need to have AI improve enterprise outcomes.
Companies like JP Morgan, Accenture, and AT&T have collectively pledged over $1.5 billion to upskill their employees to meet future work requirements. Amazon has pledged to upskill a third of its workforce. The value of upskilling isn’t just intuition. This recent survey by McKinsey shows that the highest performing companies have the best data-educated teams. And that performance gap is widening annually.
“The literal bottom line is that upskilling employees to understand data concepts pays. It may even be a requirement for long term survival.”3
The most successful executives will be those who recognize that achieving impactful, lasting results from AI also requires that the participating groups from data science, business and functional teams each share a common understanding of, and are conversant in, the critical concepts and realities of AI development and deployment.
To address this, companies like Vodafone, Levi Strauss, and Ping An have used our upskill programs to train hundreds of employees across their entire organization, from engineers to employees walking the retail floor. We help organizations identify the different roles required to effectively develop and deploy data science models in their businesses, and ensure that they get the upskilling they need so they can effectively collaborate on AI projects. By injecting this data science knowledge across the entire business, these companies are getting better results with AI - while also creating happier employees!
“Upskilling is becoming more and more important, and it creates a business advantage for us.”
-CIO Oshkosh
(CIO.com – “IT Leaders Get Creative to FIll Data Science Gaps”)
"As AI becomes increasingly critical to the enterprise, so will upskilling the entire team so that your organization is making the most of its investments in AI and your company is outpacing the competition."
1 – https://www.exasol.com/resource/data-strategy-and-culture-paving-the-way-to-the-cloud/
2 – "Upskilling in Data and Analytics is Imperative Now” (Quanthub)
3 – “Upskilling in Data and Analytics is Imperative Now” (Quanthub)
